Imersão_de_Dados_Alura_01.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Imersão de Dados Alura 01",
      "provenance": [],
      "collapsed_sections": [
        "ERfHwgWUUgca",
        "pytn4L583yby",
        "GH6CWr9YuF5M",
        "gvR4HeStufjz",
        "ThHot0ntulaR",
        "Z8X_3qC7uvDl",
        "Ub_QV_-1wmnw",
        "kPECPV-63SLR",
        "0kbV4J498wym"
      ],
      "toc_visible": true,
      "authorship_tag": "ABX9TyOkWvhTN1Qugxm/UHIqmqHN",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/guidsantos/ImersaoDadosAlura/blob/main/Imers%C3%A3o_de_Dados_Alura_01.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ERfHwgWUUgca"
      },
      "source": [
        "#Aula 01\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pytn4L583yby"
      },
      "source": [
        "##Código"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7hi5YvaGhf4l",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "outputId": "de387a5b-07cf-43c7-9850-f2e2c0dec808"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "\n",
        "dados = pd.read_csv(url_dados, compression = 'zip')\n",
        "dados"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "KQs2CWanrqFQ",
        "outputId": "4c272b97-a1fd-434f-a8e9-8ffeb6e52a8d"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eBQdH3W8rrhg",
        "outputId": "711a1aa3-6650-4558-c396-b2ef79158906"
      },
      "source": [
        "dados.shape"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(23814, 877)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pEkrAXagrsbm",
        "outputId": "3d69cd2c-1f08-4833-9ac7-9a830e45ee96"
      },
      "source": [
        "dados['tratamento']"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           com_droga\n",
              "1           com_droga\n",
              "2           com_droga\n",
              "3           com_droga\n",
              "4           com_droga\n",
              "             ...     \n",
              "23809       com_droga\n",
              "23810       com_droga\n",
              "23811    com_controle\n",
              "23812       com_droga\n",
              "23813       com_droga\n",
              "Name: tratamento, Length: 23814, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JR_Gl56mrwue",
        "outputId": "5b9c6596-8e1e-446f-b96b-ff10a880a907"
      },
      "source": [
        "dados['tratamento'].unique"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method Series.unique of 0           com_droga\n",
              "1           com_droga\n",
              "2           com_droga\n",
              "3           com_droga\n",
              "4           com_droga\n",
              "             ...     \n",
              "23809       com_droga\n",
              "23810       com_droga\n",
              "23811    com_controle\n",
              "23812       com_droga\n",
              "23813       com_droga\n",
              "Name: tratamento, Length: 23814, dtype: object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aiOjej3rrzrc",
        "outputId": "115594b2-1f78-474e-bbb2-eb7c168efe01"
      },
      "source": [
        "dados['tempo'].unique()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([24, 72, 48])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "47WpOod8r4ha",
        "outputId": "640ea662-1329-432e-e045-6e871e0f5aa9"
      },
      "source": [
        "dados['dose'].unique()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['D1', 'D2'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5zh6munRr7Bi",
        "outputId": "e6e2e2f7-d51e-48f9-958d-eb7d852bb587"
      },
      "source": [
        "dados['droga'].unique()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['b68db1d53', 'df89a8e5a', '18bb41b2c', ..., '573c787a2',\n",
              "       'b2fe3eca7', 'dd4a96d16'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MLNWwlhzr-lI",
        "outputId": "af9f3250-a370-4abc-fa9a-a9d61eca8b89"
      },
      "source": [
        "dados['g-0'].unique()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1.062 ,  0.0743,  0.628 , ...,  0.3942,  0.666 , -0.8598])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uvkSQBrbsAvy",
        "outputId": "fe7f9906-46c3-49b1-a2e3-51ade7a77837"
      },
      "source": [
        "dados['tratamento'].value_counts()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       21948\n",
              "com_controle     1866\n",
              "Name: tratamento, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "exOYZ3pxsFJi",
        "outputId": "e59d3a96-2256-4b7a-927e-a52c8e535868"
      },
      "source": [
        "dados['dose'].value_counts()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    12147\n",
              "D2    11667\n",
              "Name: dose, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JDhDUAk2sG70",
        "outputId": "f95b72d8-6159-428e-f1a0-2939b46132b9"
      },
      "source": [
        "dados['tratamento'].value_counts(normalize = True)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       0.921643\n",
              "com_controle    0.078357\n",
              "Name: tratamento, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "6DJcAioKsHwA",
        "outputId": "1bafc8cf-503f-498f-f4b5-4166558b45b7"
      },
      "source": [
        "dados['tratamento'].value_counts().plot.pie()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f35bae7ffd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "YGF_smZYsKM2",
        "outputId": "de0f7f32-026a-4b8f-d551-d8eed62cc482"
      },
      "source": [
        "dados['tempo'].value_counts().plot.pie()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f35baf41f90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "nokOM2DGsMQV",
        "outputId": "4c3c05be-a76d-4093-bf25-9417852430f8"
      },
      "source": [
        "dados['tempo'].value_counts().plot.bar()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f35bb032f50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "mf4k3Q_ZsQcX",
        "outputId": "23e2dbe9-612f-4d8f-cd6d-7f50ae130666"
      },
      "source": [
        "dados_filtrados = dados[dados['g-0'] > 0]\n",
        "dados_filtrados.head()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>id_001bd861f</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>746ca1f5a</td>\n",
              "      <td>2.0440</td>\n",
              "      <td>1.7000</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>5.9440</td>\n",
              "      <td>-2.1670</td>\n",
              "      <td>-4.0360</td>\n",
              "      <td>3.6950</td>\n",
              "      <td>1.4530</td>\n",
              "      <td>0.9724</td>\n",
              "      <td>-2.4380</td>\n",
              "      <td>5.1340</td>\n",
              "      <td>-4.6600</td>\n",
              "      <td>5.7960</td>\n",
              "      <td>4.9700</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>2.4790</td>\n",
              "      <td>-3.8010</td>\n",
              "      <td>-1.0230</td>\n",
              "      <td>5.3110</td>\n",
              "      <td>-0.5660</td>\n",
              "      <td>-4.4450</td>\n",
              "      <td>1.2210</td>\n",
              "      <td>1.3750</td>\n",
              "      <td>0.3932</td>\n",
              "      <td>0.3392</td>\n",
              "      <td>4.3510</td>\n",
              "      <td>5.7540</td>\n",
              "      <td>-1.6590</td>\n",
              "      <td>5.3000</td>\n",
              "      <td>5.6050</td>\n",
              "      <td>5.5320</td>\n",
              "      <td>3.7860</td>\n",
              "      <td>0.9197</td>\n",
              "      <td>1.9310</td>\n",
              "      <td>2.4870</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.8904</td>\n",
              "      <td>2.0590</td>\n",
              "      <td>0.5052</td>\n",
              "      <td>0.6890</td>\n",
              "      <td>0.5340</td>\n",
              "      <td>0.5135</td>\n",
              "      <td>0.6507</td>\n",
              "      <td>0.9838</td>\n",
              "      <td>0.4532</td>\n",
              "      <td>-0.3212</td>\n",
              "      <td>0.2662</td>\n",
              "      <td>0.6864</td>\n",
              "      <td>1.6300</td>\n",
              "      <td>1.3810</td>\n",
              "      <td>0.0061</td>\n",
              "      <td>0.2908</td>\n",
              "      <td>0.2598</td>\n",
              "      <td>0.1266</td>\n",
              "      <td>-0.3526</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>-1.1030</td>\n",
              "      <td>1.3650</td>\n",
              "      <td>1.0610</td>\n",
              "      <td>0.4034</td>\n",
              "      <td>1.0880</td>\n",
              "      <td>-0.4230</td>\n",
              "      <td>0.4013</td>\n",
              "      <td>0.1726</td>\n",
              "      <td>0.7464</td>\n",
              "      <td>0.9418</td>\n",
              "      <td>0.1855</td>\n",
              "      <td>1.1720</td>\n",
              "      <td>0.8325</td>\n",
              "      <td>0.6486</td>\n",
              "      <td>0.8090</td>\n",
              "      <td>1.5880</td>\n",
              "      <td>2.4670</td>\n",
              "      <td>0.0357</td>\n",
              "      <td>0.1351</td>\n",
              "      <td>-0.3179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "6  id_001bd861f  com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n",
              "7  id_0020d0484  com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GH6CWr9YuF5M"
      },
      "source": [
        "##Desafio 01 - Investigar por que a classe tratamento é tão desbalanceada?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qUJfudh0sjT_"
      },
      "source": [
        "#Desafio - 01\n",
        "dados_com_droga = dados[dados['tratamento'] == 'com_droga']\n",
        "dados_com_controle = dados[dados['tratamento'] == 'com_controle']"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "_kOUA1acsy42",
        "outputId": "04a7c175-e548-4f27-ddb3-585f0665bcc0"
      },
      "source": [
        "dados_com_controle.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>id_008a986b7</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.4860</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>0.5281</td>\n",
              "      <td>-0.0022</td>\n",
              "      <td>-0.2334</td>\n",
              "      <td>-0.6607</td>\n",
              "      <td>0.6459</td>\n",
              "      <td>-0.0109</td>\n",
              "      <td>1.0120</td>\n",
              "      <td>-0.0864</td>\n",
              "      <td>-0.3817</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>0.9435</td>\n",
              "      <td>0.6296</td>\n",
              "      <td>0.3864</td>\n",
              "      <td>0.1420</td>\n",
              "      <td>0.9834</td>\n",
              "      <td>0.4189</td>\n",
              "      <td>0.7980</td>\n",
              "      <td>-0.2132</td>\n",
              "      <td>0.7651</td>\n",
              "      <td>-1.2410</td>\n",
              "      <td>0.0747</td>\n",
              "      <td>-1.5750</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.0840</td>\n",
              "      <td>0.6705</td>\n",
              "      <td>-0.7517</td>\n",
              "      <td>-0.2756</td>\n",
              "      <td>-1.0920</td>\n",
              "      <td>-0.8683</td>\n",
              "      <td>0.3021</td>\n",
              "      <td>-0.3164</td>\n",
              "      <td>-0.2074</td>\n",
              "      <td>0.4587</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2189</td>\n",
              "      <td>-0.5262</td>\n",
              "      <td>-0.2982</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>-1.0040</td>\n",
              "      <td>-0.6726</td>\n",
              "      <td>-0.0321</td>\n",
              "      <td>-0.5398</td>\n",
              "      <td>-0.7518</td>\n",
              "      <td>0.0370</td>\n",
              "      <td>0.7213</td>\n",
              "      <td>-0.3466</td>\n",
              "      <td>0.2354</td>\n",
              "      <td>-0.4432</td>\n",
              "      <td>-0.1020</td>\n",
              "      <td>-0.9391</td>\n",
              "      <td>-1.1970</td>\n",
              "      <td>0.1365</td>\n",
              "      <td>-0.9264</td>\n",
              "      <td>0.5828</td>\n",
              "      <td>-0.7379</td>\n",
              "      <td>-0.4354</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>-0.3771</td>\n",
              "      <td>-0.6525</td>\n",
              "      <td>-0.4169</td>\n",
              "      <td>-1.0640</td>\n",
              "      <td>-0.3331</td>\n",
              "      <td>-0.5761</td>\n",
              "      <td>-0.3085</td>\n",
              "      <td>-0.1866</td>\n",
              "      <td>0.7629</td>\n",
              "      <td>0.3288</td>\n",
              "      <td>-0.9915</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.4979</td>\n",
              "      <td>0.5281</td>\n",
              "      <td>-0.9245</td>\n",
              "      <td>-0.9367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>id_009d8340f</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.4471</td>\n",
              "      <td>-0.0839</td>\n",
              "      <td>-0.3864</td>\n",
              "      <td>0.3196</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>-0.3156</td>\n",
              "      <td>-0.1187</td>\n",
              "      <td>1.1610</td>\n",
              "      <td>0.5838</td>\n",
              "      <td>-0.2996</td>\n",
              "      <td>-0.3995</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>0.2969</td>\n",
              "      <td>-0.2785</td>\n",
              "      <td>0.9678</td>\n",
              "      <td>-0.1409</td>\n",
              "      <td>1.0850</td>\n",
              "      <td>-0.0656</td>\n",
              "      <td>-0.6502</td>\n",
              "      <td>0.3527</td>\n",
              "      <td>0.1998</td>\n",
              "      <td>0.0975</td>\n",
              "      <td>0.0563</td>\n",
              "      <td>-0.3578</td>\n",
              "      <td>-0.0657</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.6573</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>1.2380</td>\n",
              "      <td>-0.4994</td>\n",
              "      <td>-0.8140</td>\n",
              "      <td>0.2567</td>\n",
              "      <td>-0.8155</td>\n",
              "      <td>1.1180</td>\n",
              "      <td>-0.2501</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.5214</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>-0.5903</td>\n",
              "      <td>0.1332</td>\n",
              "      <td>-0.3517</td>\n",
              "      <td>-0.3276</td>\n",
              "      <td>-0.4955</td>\n",
              "      <td>0.1359</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>0.5725</td>\n",
              "      <td>-0.1126</td>\n",
              "      <td>-0.0874</td>\n",
              "      <td>1.2220</td>\n",
              "      <td>-0.0641</td>\n",
              "      <td>0.0246</td>\n",
              "      <td>-0.5659</td>\n",
              "      <td>-0.7402</td>\n",
              "      <td>1.1170</td>\n",
              "      <td>-0.0612</td>\n",
              "      <td>-1.3040</td>\n",
              "      <td>-0.4025</td>\n",
              "      <td>0.3760</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>0.8064</td>\n",
              "      <td>-0.0170</td>\n",
              "      <td>0.3092</td>\n",
              "      <td>0.2671</td>\n",
              "      <td>0.3311</td>\n",
              "      <td>-0.4572</td>\n",
              "      <td>0.4795</td>\n",
              "      <td>0.3939</td>\n",
              "      <td>0.7665</td>\n",
              "      <td>0.7932</td>\n",
              "      <td>-0.6804</td>\n",
              "      <td>-0.0435</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>0.2000</td>\n",
              "      <td>-0.4326</td>\n",
              "      <td>0.9364</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "25  id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38  id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40  id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "47  id_008a986b7  com_controle     48   D2  ... -0.4979  0.5281 -0.9245 -0.9367\n",
              "63  id_009d8340f  com_controle     24   D2  ...  0.0949  0.2000 -0.4326  0.9364\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "snDWUx0jtgeb",
        "outputId": "cc5cabcd-e697-49cd-c8e1-481172c3b09b"
      },
      "source": [
        "dados_com_controle['droga'].unique()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['cacb2b860'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "T1Xmzyc8s0SJ",
        "outputId": "e500c0d2-9252-47c3-9c54-d5c6a1523c63"
      },
      "source": [
        "dados_com_droga.head()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DGFJgzMNtofN"
      },
      "source": [
        "Os dados estão desbalanceados, pois existem um número menor de tratamentos com controle que correspondem as variáveis possíveis para os testes, e elas são realizadas com uma única droga de controle. \n",
        "Assim para cada tratamento com controle, pode existir varios tratamentos com droga que iram utilizar daquele controle para validar-se\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gvR4HeStufjz"
      },
      "source": [
        "##Desafio 02 - Plotar as 5 últimas linhas da tabela\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "cFqboHUWuh3h",
        "outputId": "857b579f-7630-4fe5-c314-bcb8be6d3cf1"
      },
      "source": [
        "dados.tail(5)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ThHot0ntulaR"
      },
      "source": [
        "##Desafio 03 - Proporção das classes tratamento.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ub2frgRuunO0",
        "outputId": "bb348e23-b081-41c2-fc3f-9a0373837182"
      },
      "source": [
        "dados['tratamento'].value_counts(normalize = True)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "com_droga       0.921643\n",
              "com_controle    0.078357\n",
              "Name: tratamento, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KuFgG_YjwaLk"
      },
      "source": [
        "Temos 92,16% de tratamentos com droga e 7,83% de com controle"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z8X_3qC7uvDl"
      },
      "source": [
        "##Desafio 04 - Quantas tipos de drogas foram investigados.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E2ZPHf6su9bF",
        "outputId": "fef7aac1-cacf-4460-b3ad-c112af6a539a"
      },
      "source": [
        "todas_drogas = dados['droga'].unique()\n",
        "len(todas_drogas)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3289"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7sMGwwDJwTDq"
      },
      "source": [
        "Foram investigadas 3289 drogas, sendo uma de controle\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ub_QV_-1wmnw"
      },
      "source": [
        "##Desafio 05: Procurar na documentação o método query(pandas)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z-YU3BrPxAWS"
      },
      "source": [
        "[Link para documentação do método query do pandas](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html?highlight=query#pandas.DataFrame.query)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "z-VZNYJ7wpVQ",
        "outputId": "795bda3d-155c-4374-aa6a-ba4b7ed4790d"
      },
      "source": [
        "#Exemplo utilizando para procurar dados com tempo = 72\n",
        "dados.query('tempo == 72').head()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>id_002452c7e</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>89dea2045</td>\n",
              "      <td>-0.2875</td>\n",
              "      <td>0.0322</td>\n",
              "      <td>-0.8863</td>\n",
              "      <td>-0.0016</td>\n",
              "      <td>-0.7471</td>\n",
              "      <td>-0.3890</td>\n",
              "      <td>-0.7827</td>\n",
              "      <td>-0.1934</td>\n",
              "      <td>0.7227</td>\n",
              "      <td>0.0086</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.8161</td>\n",
              "      <td>1.3800</td>\n",
              "      <td>-0.1154</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>0.0607</td>\n",
              "      <td>0.2425</td>\n",
              "      <td>0.9784</td>\n",
              "      <td>-0.3517</td>\n",
              "      <td>-0.9382</td>\n",
              "      <td>-0.4164</td>\n",
              "      <td>-0.5645</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>-0.3545</td>\n",
              "      <td>0.5206</td>\n",
              "      <td>0.0446</td>\n",
              "      <td>0.2734</td>\n",
              "      <td>0.9901</td>\n",
              "      <td>-0.0668</td>\n",
              "      <td>-1.2280</td>\n",
              "      <td>0.9931</td>\n",
              "      <td>-0.0938</td>\n",
              "      <td>-0.6165</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.8438</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.0407</td>\n",
              "      <td>0.6523</td>\n",
              "      <td>0.4882</td>\n",
              "      <td>0.3049</td>\n",
              "      <td>0.6439</td>\n",
              "      <td>0.4413</td>\n",
              "      <td>-0.3652</td>\n",
              "      <td>0.7670</td>\n",
              "      <td>-1.0200</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>1.2780</td>\n",
              "      <td>0.4764</td>\n",
              "      <td>0.9367</td>\n",
              "      <td>-0.2893</td>\n",
              "      <td>-0.3778</td>\n",
              "      <td>0.7664</td>\n",
              "      <td>0.1937</td>\n",
              "      <td>-0.3739</td>\n",
              "      <td>0.6929</td>\n",
              "      <td>-0.4707</td>\n",
              "      <td>0.3359</td>\n",
              "      <td>0.4557</td>\n",
              "      <td>-0.4657</td>\n",
              "      <td>-0.8399</td>\n",
              "      <td>0.7681</td>\n",
              "      <td>0.7488</td>\n",
              "      <td>-0.4314</td>\n",
              "      <td>-0.0011</td>\n",
              "      <td>-0.0923</td>\n",
              "      <td>0.4200</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.7286</td>\n",
              "      <td>0.4684</td>\n",
              "      <td>-0.1541</td>\n",
              "      <td>0.8135</td>\n",
              "      <td>1.4680</td>\n",
              "      <td>0.6648</td>\n",
              "      <td>0.0651</td>\n",
              "      <td>-0.0125</td>\n",
              "      <td>0.2600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>id_002d31e2c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>e0cd5c091</td>\n",
              "      <td>0.4242</td>\n",
              "      <td>1.7040</td>\n",
              "      <td>-1.3230</td>\n",
              "      <td>-0.3163</td>\n",
              "      <td>-0.4642</td>\n",
              "      <td>-2.3810</td>\n",
              "      <td>-1.5020</td>\n",
              "      <td>2.1530</td>\n",
              "      <td>-3.9850</td>\n",
              "      <td>-0.1544</td>\n",
              "      <td>-0.5791</td>\n",
              "      <td>0.8062</td>\n",
              "      <td>0.6718</td>\n",
              "      <td>0.7429</td>\n",
              "      <td>-0.1395</td>\n",
              "      <td>0.7811</td>\n",
              "      <td>-1.0100</td>\n",
              "      <td>-0.9855</td>\n",
              "      <td>-0.3426</td>\n",
              "      <td>-0.5196</td>\n",
              "      <td>2.4430</td>\n",
              "      <td>-2.9220</td>\n",
              "      <td>-0.5350</td>\n",
              "      <td>-1.9320</td>\n",
              "      <td>-0.7978</td>\n",
              "      <td>1.2350</td>\n",
              "      <td>0.3175</td>\n",
              "      <td>-1.2190</td>\n",
              "      <td>-0.7790</td>\n",
              "      <td>2.0250</td>\n",
              "      <td>0.0553</td>\n",
              "      <td>0.0283</td>\n",
              "      <td>-1.0960</td>\n",
              "      <td>1.9580</td>\n",
              "      <td>0.7969</td>\n",
              "      <td>...</td>\n",
              "      <td>-4.9920</td>\n",
              "      <td>-0.7784</td>\n",
              "      <td>-0.6036</td>\n",
              "      <td>-9.3750</td>\n",
              "      <td>-0.3599</td>\n",
              "      <td>-9.4480</td>\n",
              "      <td>-1.9610</td>\n",
              "      <td>-4.5770</td>\n",
              "      <td>1.3830</td>\n",
              "      <td>-5.3030</td>\n",
              "      <td>-6.8870</td>\n",
              "      <td>-6.9820</td>\n",
              "      <td>-9.6940</td>\n",
              "      <td>-0.9179</td>\n",
              "      <td>-1.0980</td>\n",
              "      <td>-5.4480</td>\n",
              "      <td>-3.2580</td>\n",
              "      <td>-8.8170</td>\n",
              "      <td>-5.3500</td>\n",
              "      <td>-3.5200</td>\n",
              "      <td>-9.8590</td>\n",
              "      <td>-7.1280</td>\n",
              "      <td>-4.8040</td>\n",
              "      <td>-2.8130</td>\n",
              "      <td>-2.2400</td>\n",
              "      <td>-3.3210</td>\n",
              "      <td>-7.6230</td>\n",
              "      <td>-1.9890</td>\n",
              "      <td>-0.3294</td>\n",
              "      <td>0.2611</td>\n",
              "      <td>-5.9590</td>\n",
              "      <td>-0.6440</td>\n",
              "      <td>-0.3461</td>\n",
              "      <td>-4.9490</td>\n",
              "      <td>-1.1380</td>\n",
              "      <td>-5.2000</td>\n",
              "      <td>-8.1330</td>\n",
              "      <td>-4.3170</td>\n",
              "      <td>-6.2390</td>\n",
              "      <td>0.9477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>id_003603254</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>3cda750b5</td>\n",
              "      <td>-0.4694</td>\n",
              "      <td>-1.5180</td>\n",
              "      <td>-2.0430</td>\n",
              "      <td>0.5750</td>\n",
              "      <td>0.5077</td>\n",
              "      <td>0.2880</td>\n",
              "      <td>-0.3198</td>\n",
              "      <td>-0.6101</td>\n",
              "      <td>0.1249</td>\n",
              "      <td>0.4362</td>\n",
              "      <td>-0.6237</td>\n",
              "      <td>0.5495</td>\n",
              "      <td>-1.3170</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>-1.1790</td>\n",
              "      <td>0.5008</td>\n",
              "      <td>-0.0821</td>\n",
              "      <td>0.1371</td>\n",
              "      <td>-0.2100</td>\n",
              "      <td>0.1626</td>\n",
              "      <td>1.4410</td>\n",
              "      <td>-0.4535</td>\n",
              "      <td>0.4796</td>\n",
              "      <td>0.5551</td>\n",
              "      <td>-1.4560</td>\n",
              "      <td>-0.2305</td>\n",
              "      <td>-0.7454</td>\n",
              "      <td>0.6339</td>\n",
              "      <td>-0.1980</td>\n",
              "      <td>-0.7012</td>\n",
              "      <td>-0.0882</td>\n",
              "      <td>-0.7792</td>\n",
              "      <td>-1.3130</td>\n",
              "      <td>0.9740</td>\n",
              "      <td>0.6500</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2869</td>\n",
              "      <td>-0.8081</td>\n",
              "      <td>0.7787</td>\n",
              "      <td>-2.3180</td>\n",
              "      <td>-0.1749</td>\n",
              "      <td>-1.5440</td>\n",
              "      <td>-0.2516</td>\n",
              "      <td>0.0398</td>\n",
              "      <td>-1.0300</td>\n",
              "      <td>-1.2490</td>\n",
              "      <td>-1.4980</td>\n",
              "      <td>0.6580</td>\n",
              "      <td>-1.2280</td>\n",
              "      <td>-0.3264</td>\n",
              "      <td>-0.4176</td>\n",
              "      <td>0.4094</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-1.5150</td>\n",
              "      <td>0.7748</td>\n",
              "      <td>0.1379</td>\n",
              "      <td>-0.9742</td>\n",
              "      <td>-0.4860</td>\n",
              "      <td>-1.8320</td>\n",
              "      <td>-0.2079</td>\n",
              "      <td>-1.5640</td>\n",
              "      <td>0.0375</td>\n",
              "      <td>-1.0310</td>\n",
              "      <td>1.0830</td>\n",
              "      <td>-1.5510</td>\n",
              "      <td>-0.5745</td>\n",
              "      <td>-1.4650</td>\n",
              "      <td>-0.3515</td>\n",
              "      <td>-0.3931</td>\n",
              "      <td>-0.5623</td>\n",
              "      <td>-1.0300</td>\n",
              "      <td>-1.3360</td>\n",
              "      <td>-1.3790</td>\n",
              "      <td>-0.4393</td>\n",
              "      <td>-0.0259</td>\n",
              "      <td>0.9765</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "1   id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "4   id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "10  id_002452c7e  com_droga     72   D2  ...  0.6648  0.0651 -0.0125  0.2600\n",
              "14  id_002d31e2c  com_droga     72   D1  ... -8.1330 -4.3170 -6.2390  0.9477\n",
              "18  id_003603254  com_droga     72   D2  ... -1.3790 -0.4393 -0.0259  0.9765\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "Ktp2bhFHyPCQ",
        "outputId": "88c27431-1d26-4ab5-e4cd-6f8b9764e25c"
      },
      "source": [
        "#Exemplo para procurar dados que fazem tratamento com controle\n",
        "dados.query('tratamento == \"com_controle\"').head()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>id_008a986b7</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.4860</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>0.5281</td>\n",
              "      <td>-0.0022</td>\n",
              "      <td>-0.2334</td>\n",
              "      <td>-0.6607</td>\n",
              "      <td>0.6459</td>\n",
              "      <td>-0.0109</td>\n",
              "      <td>1.0120</td>\n",
              "      <td>-0.0864</td>\n",
              "      <td>-0.3817</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>0.9435</td>\n",
              "      <td>0.6296</td>\n",
              "      <td>0.3864</td>\n",
              "      <td>0.1420</td>\n",
              "      <td>0.9834</td>\n",
              "      <td>0.4189</td>\n",
              "      <td>0.7980</td>\n",
              "      <td>-0.2132</td>\n",
              "      <td>0.7651</td>\n",
              "      <td>-1.2410</td>\n",
              "      <td>0.0747</td>\n",
              "      <td>-1.5750</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.0840</td>\n",
              "      <td>0.6705</td>\n",
              "      <td>-0.7517</td>\n",
              "      <td>-0.2756</td>\n",
              "      <td>-1.0920</td>\n",
              "      <td>-0.8683</td>\n",
              "      <td>0.3021</td>\n",
              "      <td>-0.3164</td>\n",
              "      <td>-0.2074</td>\n",
              "      <td>0.4587</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2189</td>\n",
              "      <td>-0.5262</td>\n",
              "      <td>-0.2982</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>-1.0040</td>\n",
              "      <td>-0.6726</td>\n",
              "      <td>-0.0321</td>\n",
              "      <td>-0.5398</td>\n",
              "      <td>-0.7518</td>\n",
              "      <td>0.0370</td>\n",
              "      <td>0.7213</td>\n",
              "      <td>-0.3466</td>\n",
              "      <td>0.2354</td>\n",
              "      <td>-0.4432</td>\n",
              "      <td>-0.1020</td>\n",
              "      <td>-0.9391</td>\n",
              "      <td>-1.1970</td>\n",
              "      <td>0.1365</td>\n",
              "      <td>-0.9264</td>\n",
              "      <td>0.5828</td>\n",
              "      <td>-0.7379</td>\n",
              "      <td>-0.4354</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>-0.3771</td>\n",
              "      <td>-0.6525</td>\n",
              "      <td>-0.4169</td>\n",
              "      <td>-1.0640</td>\n",
              "      <td>-0.3331</td>\n",
              "      <td>-0.5761</td>\n",
              "      <td>-0.3085</td>\n",
              "      <td>-0.1866</td>\n",
              "      <td>0.7629</td>\n",
              "      <td>0.3288</td>\n",
              "      <td>-0.9915</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.4979</td>\n",
              "      <td>0.5281</td>\n",
              "      <td>-0.9245</td>\n",
              "      <td>-0.9367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>id_009d8340f</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.4471</td>\n",
              "      <td>-0.0839</td>\n",
              "      <td>-0.3864</td>\n",
              "      <td>0.3196</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>-0.3156</td>\n",
              "      <td>-0.1187</td>\n",
              "      <td>1.1610</td>\n",
              "      <td>0.5838</td>\n",
              "      <td>-0.2996</td>\n",
              "      <td>-0.3995</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>0.2969</td>\n",
              "      <td>-0.2785</td>\n",
              "      <td>0.9678</td>\n",
              "      <td>-0.1409</td>\n",
              "      <td>1.0850</td>\n",
              "      <td>-0.0656</td>\n",
              "      <td>-0.6502</td>\n",
              "      <td>0.3527</td>\n",
              "      <td>0.1998</td>\n",
              "      <td>0.0975</td>\n",
              "      <td>0.0563</td>\n",
              "      <td>-0.3578</td>\n",
              "      <td>-0.0657</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.6573</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>1.2380</td>\n",
              "      <td>-0.4994</td>\n",
              "      <td>-0.8140</td>\n",
              "      <td>0.2567</td>\n",
              "      <td>-0.8155</td>\n",
              "      <td>1.1180</td>\n",
              "      <td>-0.2501</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.5214</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>-0.5903</td>\n",
              "      <td>0.1332</td>\n",
              "      <td>-0.3517</td>\n",
              "      <td>-0.3276</td>\n",
              "      <td>-0.4955</td>\n",
              "      <td>0.1359</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>0.5725</td>\n",
              "      <td>-0.1126</td>\n",
              "      <td>-0.0874</td>\n",
              "      <td>1.2220</td>\n",
              "      <td>-0.0641</td>\n",
              "      <td>0.0246</td>\n",
              "      <td>-0.5659</td>\n",
              "      <td>-0.7402</td>\n",
              "      <td>1.1170</td>\n",
              "      <td>-0.0612</td>\n",
              "      <td>-1.3040</td>\n",
              "      <td>-0.4025</td>\n",
              "      <td>0.3760</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>0.8064</td>\n",
              "      <td>-0.0170</td>\n",
              "      <td>0.3092</td>\n",
              "      <td>0.2671</td>\n",
              "      <td>0.3311</td>\n",
              "      <td>-0.4572</td>\n",
              "      <td>0.4795</td>\n",
              "      <td>0.3939</td>\n",
              "      <td>0.7665</td>\n",
              "      <td>0.7932</td>\n",
              "      <td>-0.6804</td>\n",
              "      <td>-0.0435</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>0.2000</td>\n",
              "      <td>-0.4326</td>\n",
              "      <td>0.9364</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "25  id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38  id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40  id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "47  id_008a986b7  com_controle     48   D2  ... -0.4979  0.5281 -0.9245 -0.9367\n",
              "63  id_009d8340f  com_controle     24   D2  ...  0.0949  0.2000 -0.4326  0.9364\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A1amcIYPynwk"
      },
      "source": [
        "##Desafio 06: Renomear as colunas tirando o hífen."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pvx_1L6a1-fY"
      },
      "source": [
        "colunas = dados.columns"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SLDI7OXg0OwM",
        "outputId": "48f06d8b-6efd-4ede-c9e2-979fdd96eee6"
      },
      "source": [
        "colunas_com_hifen = dados.columns\n",
        "colunas_sem_hifen = []\n",
        "for coluna in colunas:\n",
        "  colunas_sem_hifen.append(coluna.replace('-', ''))\n",
        "colunas_sem_hifen[5:10]"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['g0', 'g1', 'g2', 'g3', 'g4']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pk4WaUyN1reV"
      },
      "source": [
        "dados.columns = colunas_sem_hifen"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "q361gS5211h_",
        "outputId": "eabe3d29-419e-476e-c04c-7e8dd9c190b0"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...     c96     c97     c98     c99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bV5qQB5Q2QXL",
        "outputId": "5cca028e-7d25-445f-eecc-a132ab2d80fc"
      },
      "source": [
        "dados['c10'].value_counts()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-10.0000    281\n",
              "-1.1350      12\n",
              " 1.1030      11\n",
              "-1.1000       9\n",
              " 1.0280       9\n",
              "           ... \n",
              " 0.9269       1\n",
              " 0.7760       1\n",
              " 0.0345       1\n",
              "-0.5250       1\n",
              " 0.8071       1\n",
              "Name: c10, Length: 14617, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kPECPV-63SLR"
      },
      "source": [
        "##Desafio 07: Deixar os gráficos bonitões. (Matplotlib.pyplot)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I-X-BF_h3T9M"
      },
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JxOeWnvz5m43",
        "outputId": "fafa5704-2574-472d-fe77-360aadbee37b"
      },
      "source": [
        "dados.shape[0]"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23814"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 0
        },
        "id": "2YSl9W_i3dS2",
        "outputId": "35cdb4cd-3cd5-487d-f07b-7a91045653a9"
      },
      "source": [
        "dados['tempo'].value_counts().plot.bar()\n",
        "plt.title('Quantidade de tratamentos')\n",
        "plt.xlabel('Tempo (h)')\n",
        "plt.ylabel('Quantidade')\n",
        "plt.show()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0kbV4J498wym"
      },
      "source": [
        "##Desafio 08: Resumo do que você aprendeu com os dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wx_2fSUU8yEn"
      },
      "source": [
        "###Resumo\n",
        "\n",
        "\n",
        "&nbsp;\n",
        "O dataframe que estamos utilizando é o registro de experimentos feitos em células. Foram realizados 23.814 experimentos e cada um possui um id, se o tratamento foi feito com droga ou controle, tempo do tratamento que pode ser de 24, 48 ou 72 horas, dose contendo dois tipos D1 ou D2 e o hash da droga utilizada, as outras 872 colunas são referentes ao genes e o valor de suas reações com o teste. \n",
        "\n",
        "\n",
        "&nbsp;\n",
        "No total foram utilizados 3289 drogas diferentes, sendo uma para controle, os testes precisam ter tratamentos com controle, que são responsáveis para sabermos como as células se comportam sem o uso da droga em diferentes condições, foi observado que temos variações entre os tratamentos com controle mas o hash da droga é sempre o mesmo, com isso possível ver se os tratamentos feitos com uma droga x apresentão uma reação válida. \n",
        "\n",
        "\n",
        "&nbsp;\n",
        "Foram realizados mais testes com o tempo do tratamento de 48 horas mas a diferença é pequena e o número de testes com doses D1 ou D2 são parecidos. Como cada tramento de controle pode ser usado para validar varios testes com drogas diferentes temos apenas 7,8% de tratamentos com controle e o restante é realizado com drogas.\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lGfR9Puc6Up9"
      },
      "source": [
        "#Aula2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-GbdfyHQCBBG"
      },
      "source": [
        "##Código"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9AhH6d1IB_Qi"
      },
      "source": [
        "import seaborn as sns\n",
        "sns.set()"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3w3e4bD5DTyE"
      },
      "source": [
        "mapa = {'droga':'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "iQRLya6jDzy8",
        "outputId": "87023a2d-0c87-4f0e-b4a0-a159446b1d05"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...     c96     c97     c98     c99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8IHlPD17ExF-"
      },
      "source": [
        "cod_compostos = dados['composto'].value_counts().index[0:5]"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IL4WAufLdRus",
        "outputId": "60bf42bc-ff2e-4a6a-ae6f-4c48a12804fc"
      },
      "source": [
        "cod_compostos"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "dxuNh-wDdGnn",
        "outputId": "34b1d058-e6ad-4923-9584-be4b752468eb"
      },
      "source": [
        "dados.query('composto in @cod_compostos')"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>id_002fb9c19</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>8.7380</td>\n",
              "      <td>0.1914</td>\n",
              "      <td>2.4380</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>3.2010</td>\n",
              "      <td>1.4910</td>\n",
              "      <td>5.3920</td>\n",
              "      <td>-1.0420</td>\n",
              "      <td>-8.4860</td>\n",
              "      <td>-2.5790</td>\n",
              "      <td>-6.7470</td>\n",
              "      <td>3.6150</td>\n",
              "      <td>-1.4510</td>\n",
              "      <td>0.6909</td>\n",
              "      <td>-0.7623</td>\n",
              "      <td>-2.9400</td>\n",
              "      <td>-9.2850</td>\n",
              "      <td>-6.7110</td>\n",
              "      <td>-0.4195</td>\n",
              "      <td>1.1600</td>\n",
              "      <td>-1.3180</td>\n",
              "      <td>1.3660</td>\n",
              "      <td>-1.4020</td>\n",
              "      <td>-2.6220</td>\n",
              "      <td>0.7204</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-4.0630</td>\n",
              "      <td>-0.8282</td>\n",
              "      <td>-3.5000</td>\n",
              "      <td>0.9206</td>\n",
              "      <td>-5.1450</td>\n",
              "      <td>9.8040</td>\n",
              "      <td>-2.6840</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>-0.1427</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-9.5910</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.8870</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-4.9020</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-5.5520</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.7960</td>\n",
              "      <td>-8.1770</td>\n",
              "      <td>-9.8990</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-6.7840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23793</th>\n",
              "      <td>id_ffd26f361</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.6008</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>-0.3319</td>\n",
              "      <td>-0.8782</td>\n",
              "      <td>0.9281</td>\n",
              "      <td>0.7535</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>1.6350</td>\n",
              "      <td>-0.3146</td>\n",
              "      <td>0.4984</td>\n",
              "      <td>-1.1890</td>\n",
              "      <td>0.3772</td>\n",
              "      <td>-0.8196</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-2.0350</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.7586</td>\n",
              "      <td>-0.4024</td>\n",
              "      <td>-0.0449</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.2358</td>\n",
              "      <td>0.7919</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>0.4232</td>\n",
              "      <td>1.8460</td>\n",
              "      <td>-2.0940</td>\n",
              "      <td>0.1438</td>\n",
              "      <td>-0.6604</td>\n",
              "      <td>0.7243</td>\n",
              "      <td>0.0338</td>\n",
              "      <td>-0.0182</td>\n",
              "      <td>-0.2022</td>\n",
              "      <td>0.8827</td>\n",
              "      <td>0.3147</td>\n",
              "      <td>-0.9263</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1934</td>\n",
              "      <td>1.2240</td>\n",
              "      <td>-0.1178</td>\n",
              "      <td>0.1459</td>\n",
              "      <td>-0.1242</td>\n",
              "      <td>0.3106</td>\n",
              "      <td>-0.7959</td>\n",
              "      <td>0.5681</td>\n",
              "      <td>0.3663</td>\n",
              "      <td>0.4874</td>\n",
              "      <td>-0.0548</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>1.3470</td>\n",
              "      <td>1.6210</td>\n",
              "      <td>-0.8260</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>0.3264</td>\n",
              "      <td>0.9241</td>\n",
              "      <td>0.3012</td>\n",
              "      <td>1.2980</td>\n",
              "      <td>-0.2789</td>\n",
              "      <td>0.7019</td>\n",
              "      <td>-0.3528</td>\n",
              "      <td>0.7383</td>\n",
              "      <td>1.0300</td>\n",
              "      <td>0.6527</td>\n",
              "      <td>1.6750</td>\n",
              "      <td>-0.5046</td>\n",
              "      <td>0.2942</td>\n",
              "      <td>0.2950</td>\n",
              "      <td>1.2470</td>\n",
              "      <td>0.9569</td>\n",
              "      <td>-0.2065</td>\n",
              "      <td>-0.4918</td>\n",
              "      <td>0.7863</td>\n",
              "      <td>0.0504</td>\n",
              "      <td>0.8813</td>\n",
              "      <td>0.7757</td>\n",
              "      <td>-0.5272</td>\n",
              "      <td>0.7082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23802</th>\n",
              "      <td>id_fff3976bd</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>3.2890</td>\n",
              "      <td>2.1270</td>\n",
              "      <td>0.9770</td>\n",
              "      <td>2.0490</td>\n",
              "      <td>2.3170</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>-0.6357</td>\n",
              "      <td>-6.9060</td>\n",
              "      <td>-4.4830</td>\n",
              "      <td>-2.8400</td>\n",
              "      <td>-5.3310</td>\n",
              "      <td>0.6547</td>\n",
              "      <td>-2.2080</td>\n",
              "      <td>3.6030</td>\n",
              "      <td>0.6380</td>\n",
              "      <td>-2.1280</td>\n",
              "      <td>-3.1680</td>\n",
              "      <td>-4.2180</td>\n",
              "      <td>-0.3170</td>\n",
              "      <td>0.2140</td>\n",
              "      <td>-1.7660</td>\n",
              "      <td>-1.9700</td>\n",
              "      <td>-1.4820</td>\n",
              "      <td>-1.3710</td>\n",
              "      <td>-0.2628</td>\n",
              "      <td>-0.5276</td>\n",
              "      <td>-2.4160</td>\n",
              "      <td>-0.4638</td>\n",
              "      <td>-3.8630</td>\n",
              "      <td>-0.8880</td>\n",
              "      <td>-1.9850</td>\n",
              "      <td>2.0530</td>\n",
              "      <td>-1.4700</td>\n",
              "      <td>-3.3220</td>\n",
              "      <td>1.8800</td>\n",
              "      <td>...</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.0200</td>\n",
              "      <td>-6.7560</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.1240</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-5.7500</td>\n",
              "      <td>-8.4760</td>\n",
              "      <td>-6.9470</td>\n",
              "      <td>-4.7650</td>\n",
              "      <td>-9.7690</td>\n",
              "      <td>-5.7900</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-5.7450</td>\n",
              "      <td>-2.3570</td>\n",
              "      <td>-9.1190</td>\n",
              "      <td>-4.5980</td>\n",
              "      <td>-8.7760</td>\n",
              "      <td>-7.7980</td>\n",
              "      <td>-4.1620</td>\n",
              "      <td>-6.1510</td>\n",
              "      <td>-5.7400</td>\n",
              "      <td>-6.8700</td>\n",
              "      <td>-9.1000</td>\n",
              "      <td>-3.3360</td>\n",
              "      <td>-6.6420</td>\n",
              "      <td>-2.2750</td>\n",
              "      <td>-3.4720</td>\n",
              "      <td>-6.2670</td>\n",
              "      <td>-6.3980</td>\n",
              "      <td>-8.6300</td>\n",
              "      <td>-8.1490</td>\n",
              "      <td>-6.2900</td>\n",
              "      <td>-8.0970</td>\n",
              "      <td>-8.7330</td>\n",
              "      <td>-2.3780</td>\n",
              "      <td>-8.4480</td>\n",
              "      <td>-4.4550</td>\n",
              "      <td>-5.7930</td>\n",
              "      <td>-3.7000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23805</th>\n",
              "      <td>id_fff6df1c5</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>5628cb3ee</td>\n",
              "      <td>1.7380</td>\n",
              "      <td>-1.2900</td>\n",
              "      <td>-0.4533</td>\n",
              "      <td>-1.1640</td>\n",
              "      <td>-0.4841</td>\n",
              "      <td>-0.2392</td>\n",
              "      <td>-0.1774</td>\n",
              "      <td>-1.3980</td>\n",
              "      <td>-0.4059</td>\n",
              "      <td>0.1553</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-0.8020</td>\n",
              "      <td>-0.5039</td>\n",
              "      <td>-0.7167</td>\n",
              "      <td>-0.5016</td>\n",
              "      <td>-0.9369</td>\n",
              "      <td>-0.5864</td>\n",
              "      <td>-0.1009</td>\n",
              "      <td>0.8987</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>-1.3460</td>\n",
              "      <td>-0.5087</td>\n",
              "      <td>-0.0892</td>\n",
              "      <td>-0.6559</td>\n",
              "      <td>0.0864</td>\n",
              "      <td>-0.6251</td>\n",
              "      <td>0.2471</td>\n",
              "      <td>-0.4523</td>\n",
              "      <td>-0.0389</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.0796</td>\n",
              "      <td>-0.2560</td>\n",
              "      <td>-0.7851</td>\n",
              "      <td>-0.1687</td>\n",
              "      <td>-1.2890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2866</td>\n",
              "      <td>0.3854</td>\n",
              "      <td>-0.4986</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.5843</td>\n",
              "      <td>0.0907</td>\n",
              "      <td>-0.9303</td>\n",
              "      <td>0.1981</td>\n",
              "      <td>0.6515</td>\n",
              "      <td>0.2877</td>\n",
              "      <td>0.4389</td>\n",
              "      <td>-0.3859</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>-1.1070</td>\n",
              "      <td>2.3870</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-0.6434</td>\n",
              "      <td>-0.9722</td>\n",
              "      <td>-0.4200</td>\n",
              "      <td>-0.5693</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>-0.5117</td>\n",
              "      <td>-1.2130</td>\n",
              "      <td>0.3769</td>\n",
              "      <td>0.5296</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>1.0150</td>\n",
              "      <td>-0.7669</td>\n",
              "      <td>0.2865</td>\n",
              "      <td>0.5974</td>\n",
              "      <td>-0.2727</td>\n",
              "      <td>0.1188</td>\n",
              "      <td>1.0770</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>0.1516</td>\n",
              "      <td>0.4503</td>\n",
              "      <td>-0.6312</td>\n",
              "      <td>-0.8302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3235 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...     c96     c97     c98     c99\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n",
              "25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n",
              "23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n",
              "23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "\n",
              "[3235 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "kCbolQMLD-Dr",
        "outputId": "4c966410-ee8c-4eb9-d815-4f82f9c77ab9"
      },
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "ax = sns.countplot(data=dados.query('composto in @cod_compostos'), x='composto', order=cod_compostos)\n",
        "ax.set_title('Top 5 Compostos')\n",
        "plt.show()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WhUBf3XmiIyD",
        "outputId": "5128f6d7-0f76-40ed-f178-76d6322608b6"
      },
      "source": [
        "len(dados['g0'].unique())"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14367"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YJJiNJdliktD",
        "outputId": "248f23b2-aefb-448f-aef8-f5473a9a2b85"
      },
      "source": [
        "dados['g0'].min()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-5.513"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n2ZNzruai3Jx",
        "outputId": "65eef519-d9a5-4cdc-c88d-64c5446c0538"
      },
      "source": [
        "dados['g0'].max()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "to99rq-li4rC",
        "outputId": "da882831-2a04-41b0-992b-b867760076c0"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.histplot(data=dados, x='g0', bins=100)\n",
        "plt.show()"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "y5Cwx-KsscCC",
        "outputId": "60a05f8f-b73b-4418-be8d-1066002b3601"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.histplot(data=dados, x='g19', bins=100)\n",
        "plt.show()"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i8IhZlEAsdUs",
        "outputId": "cae37000-57d8-42cb-8a0c-41a0951b1f29"
      },
      "source": [
        "dados['g0'].mean()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.24836629293692816"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "id": "zimFFoXUsgXG",
        "outputId": "9fa4ffbc-48dd-47ae-e5e7-d8313e32076c"
      },
      "source": [
        "dados.describe()"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tempo</th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>g35</th>\n",
              "      <th>g36</th>\n",
              "      <th>g37</th>\n",
              "      <th>g38</th>\n",
              "      <th>...</th>\n",
              "      <th>c60</th>\n",
              "      <th>c61</th>\n",
              "      <th>c62</th>\n",
              "      <th>c63</th>\n",
              "      <th>c64</th>\n",
              "      <th>c65</th>\n",
              "      <th>c66</th>\n",
              "      <th>c67</th>\n",
              "      <th>c68</th>\n",
              "      <th>c69</th>\n",
              "      <th>c70</th>\n",
              "      <th>c71</th>\n",
              "      <th>c72</th>\n",
              "      <th>c73</th>\n",
              "      <th>c74</th>\n",
              "      <th>c75</th>\n",
              "      <th>c76</th>\n",
              "      <th>c77</th>\n",
              "      <th>c78</th>\n",
              "      <th>c79</th>\n",
              "      <th>c80</th>\n",
              "      <th>c81</th>\n",
              "      <th>c82</th>\n",
              "      <th>c83</th>\n",
              "      <th>c84</th>\n",
              "      <th>c85</th>\n",
              "      <th>c86</th>\n",
              "      <th>c87</th>\n",
              "      <th>c88</th>\n",
              "      <th>c89</th>\n",
              "      <th>c90</th>\n",
              "      <th>c91</th>\n",
              "      <th>c92</th>\n",
              "      <th>c93</th>\n",
              "      <th>c94</th>\n",
              "      <th>c95</th>\n",
              "      <th>c96</th>\n",
              "      <th>c97</th>\n",
              "      <th>c98</th>\n",
              "      <th>c99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.020156</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.517397</td>\n",
              "      <td>-0.360770</td>\n",
              "      <td>-0.435752</td>\n",
              "      <td>-0.613591</td>\n",
              "      <td>-0.402083</td>\n",
              "      <td>-0.619682</td>\n",
              "      <td>-0.452265</td>\n",
              "      <td>-0.497164</td>\n",
              "      <td>-0.413836</td>\n",
              "      <td>-0.277029</td>\n",
              "      <td>-0.547845</td>\n",
              "      <td>-0.358611</td>\n",
              "      <td>-0.442906</td>\n",
              "      <td>-0.475194</td>\n",
              "      <td>-0.010404</td>\n",
              "      <td>-0.467001</td>\n",
              "      <td>-0.276963</td>\n",
              "      <td>-0.455848</td>\n",
              "      <td>-0.412918</td>\n",
              "      <td>-0.456404</td>\n",
              "      <td>-0.472514</td>\n",
              "      <td>-0.505481</td>\n",
              "      <td>-0.492735</td>\n",
              "      <td>-0.446836</td>\n",
              "      <td>-0.463029</td>\n",
              "      <td>-0.409310</td>\n",
              "      <td>-0.333124</td>\n",
              "      <td>-0.295009</td>\n",
              "      <td>-0.328342</td>\n",
              "      <td>-0.401615</td>\n",
              "      <td>-0.469244</td>\n",
              "      <td>-0.461411</td>\n",
              "      <td>-0.513256</td>\n",
              "      <td>-0.500142</td>\n",
              "      <td>-0.507093</td>\n",
              "      <td>-0.353726</td>\n",
              "      <td>-0.463485</td>\n",
              "      <td>-0.378241</td>\n",
              "      <td>-0.470252</td>\n",
              "      <td>-0.301505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>19.402807</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>...</td>\n",
              "      <td>2.122318</td>\n",
              "      <td>1.710725</td>\n",
              "      <td>1.898871</td>\n",
              "      <td>2.307820</td>\n",
              "      <td>1.785055</td>\n",
              "      <td>2.225596</td>\n",
              "      <td>1.991021</td>\n",
              "      <td>2.063896</td>\n",
              "      <td>1.887001</td>\n",
              "      <td>1.459639</td>\n",
              "      <td>2.187835</td>\n",
              "      <td>1.730634</td>\n",
              "      <td>1.924716</td>\n",
              "      <td>2.021927</td>\n",
              "      <td>1.029820</td>\n",
              "      <td>2.004317</td>\n",
              "      <td>1.429340</td>\n",
              "      <td>1.924263</td>\n",
              "      <td>1.888788</td>\n",
              "      <td>1.832863</td>\n",
              "      <td>2.011396</td>\n",
              "      <td>2.091353</td>\n",
              "      <td>2.055624</td>\n",
              "      <td>1.987476</td>\n",
              "      <td>2.014045</td>\n",
              "      <td>1.883974</td>\n",
              "      <td>1.647241</td>\n",
              "      <td>1.634073</td>\n",
              "      <td>1.663170</td>\n",
              "      <td>1.832794</td>\n",
              "      <td>2.000488</td>\n",
              "      <td>2.042475</td>\n",
              "      <td>2.001714</td>\n",
              "      <td>2.107105</td>\n",
              "      <td>2.159589</td>\n",
              "      <td>1.629291</td>\n",
              "      <td>2.059725</td>\n",
              "      <td>1.703615</td>\n",
              "      <td>1.834828</td>\n",
              "      <td>1.407918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.839000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.452000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.938000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.588075</td>\n",
              "      <td>-0.564025</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.583250</td>\n",
              "      <td>-0.566500</td>\n",
              "      <td>-0.603200</td>\n",
              "      <td>-0.541575</td>\n",
              "      <td>-0.560825</td>\n",
              "      <td>-0.555200</td>\n",
              "      <td>-0.534500</td>\n",
              "      <td>-0.569100</td>\n",
              "      <td>-0.558300</td>\n",
              "      <td>-0.573350</td>\n",
              "      <td>-0.594275</td>\n",
              "      <td>-0.389925</td>\n",
              "      <td>-0.551200</td>\n",
              "      <td>-0.544150</td>\n",
              "      <td>-0.575075</td>\n",
              "      <td>-0.568275</td>\n",
              "      <td>-0.582650</td>\n",
              "      <td>-0.558575</td>\n",
              "      <td>-0.562375</td>\n",
              "      <td>-0.572800</td>\n",
              "      <td>-0.561225</td>\n",
              "      <td>-0.560675</td>\n",
              "      <td>-0.560100</td>\n",
              "      <td>-0.533700</td>\n",
              "      <td>-0.504575</td>\n",
              "      <td>-0.544275</td>\n",
              "      <td>-0.569150</td>\n",
              "      <td>-0.566175</td>\n",
              "      <td>-0.565975</td>\n",
              "      <td>-0.589975</td>\n",
              "      <td>-0.568700</td>\n",
              "      <td>-0.563775</td>\n",
              "      <td>-0.567975</td>\n",
              "      <td>-0.552575</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.592600</td>\n",
              "      <td>-0.562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017650</td>\n",
              "      <td>-0.041550</td>\n",
              "      <td>-0.002950</td>\n",
              "      <td>-0.012650</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.004950</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.023800</td>\n",
              "      <td>-0.011450</td>\n",
              "      <td>-0.007100</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.009300</td>\n",
              "      <td>0.081550</td>\n",
              "      <td>-0.006900</td>\n",
              "      <td>0.018400</td>\n",
              "      <td>-0.014650</td>\n",
              "      <td>-0.014350</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>-0.005300</td>\n",
              "      <td>-0.004050</td>\n",
              "      <td>0.003300</td>\n",
              "      <td>-0.007900</td>\n",
              "      <td>-0.004600</td>\n",
              "      <td>-0.002400</td>\n",
              "      <td>0.007850</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>-0.020600</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>-0.009900</td>\n",
              "      <td>0.003250</td>\n",
              "      <td>-0.009100</td>\n",
              "      <td>-0.013750</td>\n",
              "      <td>-0.003300</td>\n",
              "      <td>-0.010250</td>\n",
              "      <td>-0.001250</td>\n",
              "      <td>-0.006800</td>\n",
              "      <td>0.014000</td>\n",
              "      <td>-0.019500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>...</td>\n",
              "      <td>0.452675</td>\n",
              "      <td>0.427675</td>\n",
              "      <td>0.462175</td>\n",
              "      <td>0.447975</td>\n",
              "      <td>0.447150</td>\n",
              "      <td>0.441250</td>\n",
              "      <td>0.470600</td>\n",
              "      <td>0.458550</td>\n",
              "      <td>0.441000</td>\n",
              "      <td>0.460075</td>\n",
              "      <td>0.460950</td>\n",
              "      <td>0.449975</td>\n",
              "      <td>0.445200</td>\n",
              "      <td>0.473200</td>\n",
              "      <td>0.563575</td>\n",
              "      <td>0.456350</td>\n",
              "      <td>0.493400</td>\n",
              "      <td>0.448375</td>\n",
              "      <td>0.451975</td>\n",
              "      <td>0.463075</td>\n",
              "      <td>0.447675</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.468900</td>\n",
              "      <td>0.452375</td>\n",
              "      <td>0.460475</td>\n",
              "      <td>0.461675</td>\n",
              "      <td>0.465950</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.450075</td>\n",
              "      <td>0.430875</td>\n",
              "      <td>0.457750</td>\n",
              "      <td>0.461500</td>\n",
              "      <td>0.445675</td>\n",
              "      <td>0.452900</td>\n",
              "      <td>0.470900</td>\n",
              "      <td>0.444750</td>\n",
              "      <td>0.465225</td>\n",
              "      <td>0.446400</td>\n",
              "      <td>0.461275</td>\n",
              "      <td>0.438650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>3.888000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>4.857000</td>\n",
              "      <td>3.549000</td>\n",
              "      <td>3.382000</td>\n",
              "      <td>3.328000</td>\n",
              "      <td>4.157000</td>\n",
              "      <td>3.736000</td>\n",
              "      <td>3.582000</td>\n",
              "      <td>3.119000</td>\n",
              "      <td>3.323000</td>\n",
              "      <td>5.014000</td>\n",
              "      <td>2.898000</td>\n",
              "      <td>4.185000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>3.276000</td>\n",
              "      <td>4.992000</td>\n",
              "      <td>3.770000</td>\n",
              "      <td>2.851000</td>\n",
              "      <td>3.211000</td>\n",
              "      <td>4.534000</td>\n",
              "      <td>3.890000</td>\n",
              "      <td>3.994000</td>\n",
              "      <td>4.321000</td>\n",
              "      <td>4.020000</td>\n",
              "      <td>3.738000</td>\n",
              "      <td>3.252000</td>\n",
              "      <td>5.406000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>3.320000</td>\n",
              "      <td>4.069000</td>\n",
              "      <td>3.960000</td>\n",
              "      <td>3.927000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>3.747000</td>\n",
              "      <td>2.814000</td>\n",
              "      <td>3.505000</td>\n",
              "      <td>2.924000</td>\n",
              "      <td>3.111000</td>\n",
              "      <td>3.805000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 873 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              tempo            g0  ...           c98           c99\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean      48.020156      0.248366  ...     -0.470252     -0.301505\n",
              "std       19.402807      1.393399  ...      1.834828      1.407918\n",
              "min       24.000000     -5.513000  ...    -10.000000    -10.000000\n",
              "25%       24.000000     -0.473075  ...     -0.592600     -0.562900\n",
              "50%       48.000000     -0.008850  ...      0.014000     -0.019500\n",
              "75%       72.000000      0.525700  ...      0.461275      0.438650\n",
              "max       72.000000     10.000000  ...      3.111000      3.805000\n",
              "\n",
              "[8 rows x 873 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        },
        "id": "VypAOKZks0EM",
        "outputId": "91ce6c08-4335-4a81-9e60-881de2231db2"
      },
      "source": [
        "dados[['g0','g1']].head()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       g0      g1\n",
              "0  1.0620  0.5577\n",
              "1  0.0743  0.4087\n",
              "2  0.6280  0.5817\n",
              "3 -0.5138 -0.2491\n",
              "4 -0.3254 -0.4009"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "id": "C2oxMII8tFZW",
        "outputId": "45ada0be-737e-4031-f9c4-b3f37c36f2ed"
      },
      "source": [
        "dados.loc[:,'g0':'g771'].describe()"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g0</th>\n",
              "      <th>g1</th>\n",
              "      <th>g2</th>\n",
              "      <th>g3</th>\n",
              "      <th>g4</th>\n",
              "      <th>g5</th>\n",
              "      <th>g6</th>\n",
              "      <th>g7</th>\n",
              "      <th>g8</th>\n",
              "      <th>g9</th>\n",
              "      <th>g10</th>\n",
              "      <th>g11</th>\n",
              "      <th>g12</th>\n",
              "      <th>g13</th>\n",
              "      <th>g14</th>\n",
              "      <th>g15</th>\n",
              "      <th>g16</th>\n",
              "      <th>g17</th>\n",
              "      <th>g18</th>\n",
              "      <th>g19</th>\n",
              "      <th>g20</th>\n",
              "      <th>g21</th>\n",
              "      <th>g22</th>\n",
              "      <th>g23</th>\n",
              "      <th>g24</th>\n",
              "      <th>g25</th>\n",
              "      <th>g26</th>\n",
              "      <th>g27</th>\n",
              "      <th>g28</th>\n",
              "      <th>g29</th>\n",
              "      <th>g30</th>\n",
              "      <th>g31</th>\n",
              "      <th>g32</th>\n",
              "      <th>g33</th>\n",
              "      <th>g34</th>\n",
              "      <th>g35</th>\n",
              "      <th>g36</th>\n",
              "      <th>g37</th>\n",
              "      <th>g38</th>\n",
              "      <th>g39</th>\n",
              "      <th>...</th>\n",
              "      <th>g732</th>\n",
              "      <th>g733</th>\n",
              "      <th>g734</th>\n",
              "      <th>g735</th>\n",
              "      <th>g736</th>\n",
              "      <th>g737</th>\n",
              "      <th>g738</th>\n",
              "      <th>g739</th>\n",
              "      <th>g740</th>\n",
              "      <th>g741</th>\n",
              "      <th>g742</th>\n",
              "      <th>g743</th>\n",
              "      <th>g744</th>\n",
              "      <th>g745</th>\n",
              "      <th>g746</th>\n",
              "      <th>g747</th>\n",
              "      <th>g748</th>\n",
              "      <th>g749</th>\n",
              "      <th>g750</th>\n",
              "      <th>g751</th>\n",
              "      <th>g752</th>\n",
              "      <th>g753</th>\n",
              "      <th>g754</th>\n",
              "      <th>g755</th>\n",
              "      <th>g756</th>\n",
              "      <th>g757</th>\n",
              "      <th>g758</th>\n",
              "      <th>g759</th>\n",
              "      <th>g760</th>\n",
              "      <th>g761</th>\n",
              "      <th>g762</th>\n",
              "      <th>g763</th>\n",
              "      <th>g764</th>\n",
              "      <th>g765</th>\n",
              "      <th>g766</th>\n",
              "      <th>g767</th>\n",
              "      <th>g768</th>\n",
              "      <th>g769</th>\n",
              "      <th>g770</th>\n",
              "      <th>g771</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>0.132026</td>\n",
              "      <td>...</td>\n",
              "      <td>0.263569</td>\n",
              "      <td>-0.242638</td>\n",
              "      <td>0.110180</td>\n",
              "      <td>-0.039868</td>\n",
              "      <td>-0.064056</td>\n",
              "      <td>0.193629</td>\n",
              "      <td>0.004470</td>\n",
              "      <td>-0.187085</td>\n",
              "      <td>0.067186</td>\n",
              "      <td>0.006159</td>\n",
              "      <td>-0.201189</td>\n",
              "      <td>-0.243317</td>\n",
              "      <td>0.548903</td>\n",
              "      <td>0.247065</td>\n",
              "      <td>0.085950</td>\n",
              "      <td>0.090544</td>\n",
              "      <td>0.215525</td>\n",
              "      <td>-0.007705</td>\n",
              "      <td>0.236954</td>\n",
              "      <td>0.022785</td>\n",
              "      <td>0.103224</td>\n",
              "      <td>0.048402</td>\n",
              "      <td>0.109367</td>\n",
              "      <td>-0.103262</td>\n",
              "      <td>0.004129</td>\n",
              "      <td>0.066211</td>\n",
              "      <td>0.072773</td>\n",
              "      <td>-0.033051</td>\n",
              "      <td>-0.400643</td>\n",
              "      <td>-0.338978</td>\n",
              "      <td>0.207299</td>\n",
              "      <td>0.009161</td>\n",
              "      <td>0.171027</td>\n",
              "      <td>0.002316</td>\n",
              "      <td>-0.209799</td>\n",
              "      <td>-0.076251</td>\n",
              "      <td>0.134162</td>\n",
              "      <td>-0.128018</td>\n",
              "      <td>-0.219210</td>\n",
              "      <td>0.101524</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>0.990477</td>\n",
              "      <td>...</td>\n",
              "      <td>1.075809</td>\n",
              "      <td>1.309482</td>\n",
              "      <td>0.881283</td>\n",
              "      <td>0.917119</td>\n",
              "      <td>1.186966</td>\n",
              "      <td>1.212621</td>\n",
              "      <td>1.175611</td>\n",
              "      <td>1.182180</td>\n",
              "      <td>1.057292</td>\n",
              "      <td>0.996940</td>\n",
              "      <td>1.029370</td>\n",
              "      <td>1.378815</td>\n",
              "      <td>2.023791</td>\n",
              "      <td>1.639307</td>\n",
              "      <td>1.238753</td>\n",
              "      <td>0.961212</td>\n",
              "      <td>1.293783</td>\n",
              "      <td>0.966213</td>\n",
              "      <td>1.284074</td>\n",
              "      <td>1.015557</td>\n",
              "      <td>1.035968</td>\n",
              "      <td>1.048645</td>\n",
              "      <td>0.856080</td>\n",
              "      <td>1.175372</td>\n",
              "      <td>0.701031</td>\n",
              "      <td>0.996914</td>\n",
              "      <td>1.077310</td>\n",
              "      <td>1.579948</td>\n",
              "      <td>1.913468</td>\n",
              "      <td>1.701554</td>\n",
              "      <td>1.096488</td>\n",
              "      <td>1.200395</td>\n",
              "      <td>1.357701</td>\n",
              "      <td>1.052771</td>\n",
              "      <td>1.201918</td>\n",
              "      <td>1.115477</td>\n",
              "      <td>0.951264</td>\n",
              "      <td>1.230636</td>\n",
              "      <td>1.326193</td>\n",
              "      <td>1.417674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.223000</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.504000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-3.790000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.920000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.462000</td>\n",
              "      <td>-6.634000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.912000</td>\n",
              "      <td>-9.833000</td>\n",
              "      <td>-7.227000</td>\n",
              "      <td>-5.561000</td>\n",
              "      <td>-8.393000</td>\n",
              "      <td>-5.790000</td>\n",
              "      <td>-4.915000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.918000</td>\n",
              "      <td>-5.255000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.264000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.505000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.193000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.795000</td>\n",
              "      <td>-8.180000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.269000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>-0.401700</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.390700</td>\n",
              "      <td>-0.565075</td>\n",
              "      <td>-0.433275</td>\n",
              "      <td>-0.498650</td>\n",
              "      <td>-0.526300</td>\n",
              "      <td>-0.430750</td>\n",
              "      <td>-0.488775</td>\n",
              "      <td>-0.593125</td>\n",
              "      <td>-0.498275</td>\n",
              "      <td>-0.489800</td>\n",
              "      <td>-0.564100</td>\n",
              "      <td>-0.538000</td>\n",
              "      <td>-0.464000</td>\n",
              "      <td>-0.521975</td>\n",
              "      <td>-0.488600</td>\n",
              "      <td>-0.442925</td>\n",
              "      <td>-0.457200</td>\n",
              "      <td>-0.477900</td>\n",
              "      <td>-0.458175</td>\n",
              "      <td>-0.479075</td>\n",
              "      <td>-0.478825</td>\n",
              "      <td>-0.489300</td>\n",
              "      <td>-0.327500</td>\n",
              "      <td>-0.576775</td>\n",
              "      <td>-0.278275</td>\n",
              "      <td>-0.492700</td>\n",
              "      <td>-0.501575</td>\n",
              "      <td>-0.526450</td>\n",
              "      <td>-0.507375</td>\n",
              "      <td>-0.559175</td>\n",
              "      <td>-0.433875</td>\n",
              "      <td>-0.502250</td>\n",
              "      <td>-0.537075</td>\n",
              "      <td>-0.508775</td>\n",
              "      <td>-0.606175</td>\n",
              "      <td>-0.506200</td>\n",
              "      <td>-0.353100</td>\n",
              "      <td>-0.544600</td>\n",
              "      <td>-0.554400</td>\n",
              "      <td>-0.523800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>0.007400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.065650</td>\n",
              "      <td>-0.014100</td>\n",
              "      <td>0.030850</td>\n",
              "      <td>-0.001800</td>\n",
              "      <td>-0.008400</td>\n",
              "      <td>0.101400</td>\n",
              "      <td>0.033400</td>\n",
              "      <td>-0.001600</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>0.014800</td>\n",
              "      <td>-0.044000</td>\n",
              "      <td>0.017400</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>-0.015550</td>\n",
              "      <td>0.025350</td>\n",
              "      <td>0.017750</td>\n",
              "      <td>0.053450</td>\n",
              "      <td>0.027700</td>\n",
              "      <td>-0.002100</td>\n",
              "      <td>0.009500</td>\n",
              "      <td>-0.004450</td>\n",
              "      <td>-0.000050</td>\n",
              "      <td>0.002400</td>\n",
              "      <td>0.024250</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>0.013600</td>\n",
              "      <td>0.001350</td>\n",
              "      <td>0.007350</td>\n",
              "      <td>0.038700</td>\n",
              "      <td>0.059600</td>\n",
              "      <td>-0.005900</td>\n",
              "      <td>-0.013600</td>\n",
              "      <td>-0.027700</td>\n",
              "      <td>-0.011850</td>\n",
              "      <td>0.009900</td>\n",
              "      <td>0.005400</td>\n",
              "      <td>0.000600</td>\n",
              "      <td>0.028700</td>\n",
              "      <td>-0.006500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>0.439400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.646900</td>\n",
              "      <td>0.467900</td>\n",
              "      <td>0.543400</td>\n",
              "      <td>0.477200</td>\n",
              "      <td>0.497400</td>\n",
              "      <td>0.846400</td>\n",
              "      <td>0.573875</td>\n",
              "      <td>0.501675</td>\n",
              "      <td>0.519825</td>\n",
              "      <td>0.515000</td>\n",
              "      <td>0.412375</td>\n",
              "      <td>0.479400</td>\n",
              "      <td>0.646325</td>\n",
              "      <td>0.565200</td>\n",
              "      <td>0.610075</td>\n",
              "      <td>0.506975</td>\n",
              "      <td>0.671725</td>\n",
              "      <td>0.514175</td>\n",
              "      <td>0.524175</td>\n",
              "      <td>0.501325</td>\n",
              "      <td>0.516975</td>\n",
              "      <td>0.517475</td>\n",
              "      <td>0.375275</td>\n",
              "      <td>0.572250</td>\n",
              "      <td>0.251600</td>\n",
              "      <td>0.540950</td>\n",
              "      <td>0.530900</td>\n",
              "      <td>0.527900</td>\n",
              "      <td>0.475275</td>\n",
              "      <td>0.522075</td>\n",
              "      <td>0.648500</td>\n",
              "      <td>0.492150</td>\n",
              "      <td>0.522500</td>\n",
              "      <td>0.457000</td>\n",
              "      <td>0.483000</td>\n",
              "      <td>0.511175</td>\n",
              "      <td>0.409075</td>\n",
              "      <td>0.498500</td>\n",
              "      <td>0.496400</td>\n",
              "      <td>0.536950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.889000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.635000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.664000</td>\n",
              "      <td>9.566000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.497000</td>\n",
              "      <td>6.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.323000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.533000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.008000</td>\n",
              "      <td>5.900000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.552000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.346000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>6.317000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 g0            g1  ...          g770          g771\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean       0.248366     -0.095684  ...     -0.219210      0.101524\n",
              "std        1.393399      0.812363  ...      1.326193      1.417674\n",
              "min       -5.513000     -5.737000  ...    -10.000000    -10.000000\n",
              "25%       -0.473075     -0.562200  ...     -0.554400     -0.523800\n",
              "50%       -0.008850     -0.046600  ...      0.028700     -0.006500\n",
              "75%        0.525700      0.403075  ...      0.496400      0.536950\n",
              "max       10.000000      5.039000  ...     10.000000     10.000000\n",
              "\n",
              "[8 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "id": "dlAw51qhtzDA",
        "outputId": "340a8ff7-6972-4381-e669-dca5373687da"
      },
      "source": [
        "dados.loc[:,'g0':'g771'].describe().T['mean'].hist(bins=50)\n",
        "plt.show()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "id": "192Av7xvuM7Q",
        "outputId": "e51b3b98-e8c0-4b10-91c7-50a3c6dec55e"
      },
      "source": [
        "dados.loc[:,'g0':'g771'].describe().T['min'].hist(bins=50)\n",
        "plt.show()"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXsAAAD7CAYAAACL+TRnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAX/0lEQVR4nO3db1BU593/8c8eKjQGdANisqBTWqN2G6a1uh0zncG2mNyQDEramYyU6oOoTWcyOjYWWkZvwaIOBUnS2urPtDHNNKUhtr+JFDSgGWzTph0nxNJK6SQZR9NJWP8t0oCK3u7u/cA7O7W6e3Zh2QWu9+uRnOucPd/9Bj7nyrV/jiMYDAYFAJjUrGQXAAAYe4Q9ABiAsAcAAxD2AGAAwh4ADEDYA4ABCHsAMMDHkl1AJBcvXlIgEPvHALKy0uXzDY1BRZMHPbJHj+zRI3uJ7JFlOXTXXXfedmxch30gEBxR2H90LCKjR/bokT16ZG889IhlHAAwAGEPAAYg7AHAADGF/U9+8hPNnz9f77zzjiSpu7tby5cvV1FRkVavXi2fzxfaN9IYACCxog77v//97+ru7lZubq4kKRAIqLKyUtXV1ero6JDH41FjY6PtGAAg8aIK+2vXrqm2tlZbt24Nbevp6VFaWpo8Ho8kqaysTO3t7bZjAIDEi+qtlz/60Y+0fPlyzZo1K7TN6/UqJycn9HNmZqYCgYAGBgYijjmdzqiLy8pKj3rf/5SdnTHiY01Bj+zRI3v0yN546JFt2P/lL39RT0+PKioqElHPTXy+oRG9P3W6c6pSp6Tcsn346nUNfnglHqVNeNnZGTp/fjDZZYxr9MgePbKXyB5ZliPsJNk27N98802dPHlSS5culSSdOXNGa9as0apVq9TX1xfar7+/X5Zlyel0yuVyhR1LhNQpKVr2nZZbtrc+VSp+LQGYyHbN/vHHH9cf//hHdXZ2qrOzU/fcc4/27duntWvXanh4WF1dXZKk5uZmFRcXS5Ly8/PDjgEAEm/EX5dgWZYaGhpUU1Ojq1evKjc3Vzt37rQdAwAkXsxh39nZGfr3woUL1draetv9Io0BABKLT9ACgAEIewAwAGEPAAYg7AHAAIQ9ABiAsAcAAxD2AGAAwh4ADEDYA4ABCHsAMABhDwAGIOwBwACEPQAYgLAHAAMQ9gBgAMIeAAxA2AOAAaK6U9UTTzyh999/X5ZlaerUqdqyZYvcbrcKCwuVmpqqtLQ0SVJFRYUKCgokSd3d3aqurr7ptoRZWVlj90wAAGFFFfb19fXKyMiQJL322mvatGmTXnnlFUnSrl27NG/evJv2DwQCqqysVF1dnTwej/bs2aPGxkbV1dXFuXwAQDSiWsb5KOglaWhoSA6HI+L+PT09SktLk8fjkSSVlZWpvb19FGUCAEYj6huOb968WW+88YaCwaCee+650PaKigoFg0EtWrRIGzdu1LRp0+T1epWTkxPaJzMzU4FAQAMDA3I6nVEXl5WVHvW+0crOzrDfyRD0wh49skeP7I2HHkUd9jt27JAkHThwQA0NDfrZz36mpqYmuVwuXbt2TTt27FBtba0aGxvjVpzPN6RAIBjzcZEae/784GhKmjSyszPohQ16ZI8e2UtkjyzLEXaSHPO7cR555BEdO3ZMFy9elMvlkiSlpqaqvLxcx48flyS5XC719fWFjunv75dlWTHN6gEA8WMb9pcuXZLX6w393NnZqenTpystLU2DgzeuVsFgUIcOHZLb7ZYk5efna3h4WF1dXZKk5uZmFRcXj0X9AIAo2C7jXLlyRRs2bNCVK1dkWZamT5+uvXv3yufzaf369fL7/QoEApozZ45qamokSZZlqaGhQTU1NTe99RIAkBy2YT9jxgzt37//tmMHDhwIe9zChQvV2to68soAAHHDJ2gBwACEPQAYgLAHAAMQ9gBgAMIeAAxA2AOAAQh7ADAAYQ8ABiDsAcAAhD0AGICwBwADEPYAYADCHgAMQNgDgAEIewAwAGEPAAYg7AHAALZ3qpKkJ554Qu+//74sy9LUqVO1ZcsWud1unTp1SlVVVRoYGJDT6VR9fb3y8vIkKeIYACCxoprZ19fX67e//a0OHDig1atXa9OmTZKkmpoalZeXq6OjQ+Xl5aqurg4dE2kMAJBYUYV9RkZG6N9DQ0NyOBzy+Xzq7e1VSUmJJKmkpES9vb3q7++POAYASLyolnEkafPmzXrjjTcUDAb13HPPyev16u6771ZKSookKSUlRTNnzpTX61UwGAw7lpmZGXVxWVnpMT4de9nZGfY7GYJe2KNH9uiRvfHQo6jDfseOHZKkAwcOqKGhQRs2bBizoj7i8w0pEAjGfFykxp4/PziakiaN7OwMemGDHtmjR/YS2SPLcoSdJMf8bpxHHnlEx44d0z333KOzZ8/K7/dLkvx+v86dOyeXyyWXyxV2DACQeLZhf+nSJXm93tDPnZ2dmj59urKysuR2u9XW1iZJamtrk9vtVmZmZsQxAEDi2S7jXLlyRRs2bNCVK1dkWZamT5+uvXv3yuFwaOvWraqqqtKePXs0bdo01dfXh46LNAYASCzbsJ8xY4b2799/27E5c+bo17/+dcxjAIDE4hO0AGAAwh4ADEDYA4ABCHsAMABhDwAGIOwBwACEPQAYgLAHAAMQ9gBgAMIeAAxA2AOAAQh7ADAAYQ8ABiDsAcAAhD0AGICwBwADEPYAYADbO1VdvHhR3/3ud/XPf/5Tqamp+sQnPqHa2lplZmZq/vz5mjdvnizrxjWjoaFB8+fPl3TjXrUNDQ3y+/267777VFdXpzvuuGNsnw0A4LZsZ/YOh0Nr165VR0eHWltbNXv2bDU2NobGm5ub1dLSopaWllDQX7p0SVu2bNHevXt15MgR3Xnnndq3b9/YPQsAQES2Ye90OrV48eLQzwsWLFBfX1/EY15//XXl5+crLy9PklRWVqZXX311dJUCAEbMdhnn3wUCAb300ksqLCwMbVu1apX8fr+WLFmi9evXKzU1VV6vVzk5OaF9cnJy5PV6Yy4uKys95mPsZGdnxP0xJyp6YY8e2aNH9sZDj2IK+23btmnq1KlauXKlJOl3v/udXC6XhoaGVFlZqd27d+vJJ5+MW3E+35ACgWDMx0Vq7Pnzg6MpadLIzs6gFzbokT16ZC+RPbIsR9hJctTvxqmvr9d7772nH/7wh6EXZF0ulyQpPT1djz76qI4fPx7a/u9LPX19faF9AQCJF1XYP/300+rp6dHu3buVmpoqSfrXv/6l4eFhSdL169fV0dEht9stSSooKNCJEyd0+vRpSTdexH3ooYfGoHwAQDRsl3HeffddPfvss8rLy1NZWZkkadasWVq7dq2qq6vlcDh0/fp1ff7zn9eGDRsk3Zjp19bW6lvf+pYCgYDcbrc2b948ts8EABCWbdjPnTtXb7/99m3HWltbwx73wAMP6IEHHhh5ZQCAuOETtABgAMIeAAxA2AOAAQh7ADAAYQ8ABiDsAcAAhD0AGICwBwADEPYAYADCHgAMQNgDgAEIewAwAGEPAAYg7AHAAIQ9ABiAsAcAAxD2AGAA27C/ePGivvnNb6qoqEjLli3TunXr1N/fL0nq7u7W8uXLVVRUpNWrV8vn84WOizQGAEgs27B3OBxau3atOjo61NraqtmzZ6uxsVGBQECVlZWqrq5WR0eHPB6PGhsbJSniGAAg8WzD3ul0avHixaGfFyxYoL6+PvX09CgtLU0ej0eSVFZWpvb2dkmKOAYASDzbG47/u0AgoJdeekmFhYXyer3KyckJjWVmZioQCGhgYCDimNPpjPp8WVnpsZQXlezsjLg/5kRFL+zRI3v0yN546FFMYb9t2zZNnTpVK1eu1JEjR8aqphCfb0iBQDDm4yI19vz5wdGUNGlkZ2fQCxv0yB49spfIHlmWI+wkOeqwr6+v13vvvae9e/fKsiy5XC719fWFxvv7+2VZlpxOZ8QxAEDiRfXWy6efflo9PT3avXu3UlNTJUn5+fkaHh5WV1eXJKm5uVnFxcW2YwCAxLOd2b/77rt69tlnlZeXp7KyMknSrFmztHv3bjU0NKimpkZXr15Vbm6udu7cKUmyLCvsGAAg8WzDfu7cuXr77bdvO7Zw4UK1trbGPAYASCw+QQsABiDsAcAAhD0AGICwBwADEPYAYADCHgAMQNgDgAEIewAwAGEPAAYg7AHAAIQ9ABiAsAcAAxD2AGAAwh4ADEDYA4ABCHsAMABhDwAGiOqG4/X19ero6NAHH3yg1tZWzZs3T5JUWFio1NRUpaWlSZIqKipUUFAgSeru7lZ1dfVNtyXMysoao6cBAIgkqpn90qVL1dTUpNzc3FvGdu3apZaWFrW0tISCPhAIqLKyUtXV1ero6JDH41FjY2N8KwcARC2qsPd4PHK5XFE/aE9Pj9LS0uTxeCRJZWVlam9vH1mFAIBRi2oZJ5KKigoFg0EtWrRIGzdu1LRp0+T1epWTkxPaJzMzU4FAQAMDA3I6nVE/dlZW+mjLu0V2dkbcH3Oiohf26JE9emRvPPRoVGHf1NQkl8ula9euaceOHaqtrY3rco3PN6RAIBjzcZEae/784GhKmjSyszPohQ16ZI8e2UtkjyzLEXaSPKp343y0tJOamqry8nIdP348tL2vry+0X39/vyzLimlWDwCInxGH/eXLlzU4eONqFQwGdejQIbndbklSfn6+hoeH1dXVJUlqbm5WcXFxHMoFAIxEVMs427dv1+HDh3XhwgU99thjcjqd2rt3r9avXy+/369AIKA5c+aopqZGkmRZlhoaGlRTU3PTWy8BAMnhCAaDsS+KJ8ho1uyXfafllu2tT5Wyvvh/WGu1R4/s0SN7k2LNHgAwMRD2AGAAwh4ADEDYA4ABCHsAMABhDwAGIOwBwACEPQAYgLAHAAMQ9gBgAMIeAAxA2AOAAQh7ADAAYQ8ABiDsAcAAhD0AGICwBwAD2IZ9fX29CgsLNX/+fL3zzjuh7adOndKKFStUVFSkFStW6PTp01GNAQASzzbsly5dqqamJuXm5t60vaamRuXl5ero6FB5ebmqq6ujGgMAJJ5t2Hs8Hrlcrpu2+Xw+9fb2qqSkRJJUUlKi3t5e9ff3RxwDACTHx0ZykNfr1d13362UlBRJUkpKimbOnCmv16tgMBh2LDMzM6bzhLtx7mhkZ2fE/TEnKnphjx7Zo0f2xkOPRhT2ieLzDSkQCMZ8XKTGJuou7+NdIu94P1HRI3v0yF4ie2RZjrCT5BGFvcvl0tmzZ+X3+5WSkiK/369z587J5XIpGAyGHQMAJMeI3nqZlZUlt9uttrY2SVJbW5vcbrcyMzMjjgEAksN2Zr99+3YdPnxYFy5c0GOPPSan06mDBw9q69atqqqq0p49ezRt2jTV19eHjok0BgBIPEcwGIx9UTxBRrNmv+w7Lbdsb32qlPXF/8Naqz16ZI8e2Rsva/Z8ghYADEDYA4ABCHsAMABhDwAGIOwBwACEPQAYgLAHAAMQ9gBgAMIeAAxA2AOAAQh7ADAAYQ8ABiDsAcAAhD0AGICwBwADEPYAYADCHgAMMKIbjv+7wsJCpaamKi0tTZJUUVGhgoICdXd3q7q6WlevXlVubq527typrKysURcMAIjdqMNeknbt2qV58+aFfg4EAqqsrFRdXZ08Ho/27NmjxsZG1dXVxeN0AIAYjckyTk9Pj9LS0uTxeCRJZWVlam9vH4tTAQCiEJeZfUVFhYLBoBYtWqSNGzfK6/UqJycnNJ6ZmalAIKCBgQE5nc6oHzfcjXNHIzs7I+6POVHRC3v0yB49sjceejTqsG9qapLL5dK1a9e0Y8cO1dbW6sEHH4xHbfL5hhQIBGM+LlJjE3WX9/EukXe8n6jokT16ZC+RPbIsR9hJ8qiXcVwulyQpNTVV5eXlOn78uFwul/r6+kL79Pf3y7KsmGb1AID4GVXYX758WYODN65YwWBQhw4dktvtVn5+voaHh9XV1SVJam5uVnFx8eirBQCMyKiWcXw+n9avXy+/369AIKA5c+aopqZGlmWpoaFBNTU1N731EgCQHKMK+9mzZ+vAgQO3HVu4cKFaW1tH8/AAgDjhE7QAYADCHgAMQNgDgAEIewAwAGEPAAYg7AHAAIQ9ABiAsAcAAxD2AGCAuHzFMSaea//jv+23gw5fva7BD68koSIAY4mwN1TqlBQt+07LLdtbnyoVX1gLTD4s4wCAAQh7ADAAyziYsDKm3aGPp936Kxyv1x3Cva5x9ZpfaakpUZ93rOsEokHYxxF/1CMXrndS+P59PO1jt33d4f//oCQuLz5Hel0jlvNKimn/cBcTid8ljBxhH0exho808WeJ8aonXO+k2F80DhfSIwnXWES6OMS6f7x6AXyEsI8gXJDFGg7h/qil+M0S4xUCsS5dhKsnXrPreIo1XMOFdDLFa2kpnPE2mUD8jGnYnzp1SlVVVRoYGJDT6VR9fb3y8vLG8pQRxSvIEhEOsc4Sw4m0PBLreeMxa410EYO9eC0txbo0FutkIpkXDS5YtzemYV9TU6Py8nKVlpaqpaVF1dXV+sUvfjGWp4xoMszswgl3IZPCX7CSYSQXsUjPDZHF66Ib7r/Btf/x33b/sX49JZJ4XbAmmzELe5/Pp97eXv385z+XJJWUlGjbtm3q7+9XZmZmVI9hWY4Rn3/mXXdMiO3xeqzUKSlas/3wLdv3/fd/jbvnHOv2yfzcJsrvS7j9/9/3loa9aMR63ku3+XtPT/+40kawlHq7c4f9P/ur1zU0NBz2seJhNFkWr/M4gsFgcCxO2tPTo+9973s6ePBgaNvDDz+snTt36r777huLUwIAwuBDVQBggDELe5fLpbNnz8rvv7Gm5/f7de7cOblcrrE6JQAgjDEL+6ysLLndbrW1tUmS2tra5Ha7o16vBwDEz5it2UvSyZMnVVVVpQ8//FDTpk1TfX29PvWpT43V6QAAYYxp2AMAxgdeoAUAAxD2AGAAwh4ADEDYA4ABJk3Yt7S0aNmyZfrMZz6jX/7ylzeNXblyRd/+9rf14IMPqri4WEePHk1SlePLqVOntGrVKpWWluqhhx7Sj3/842SXNC69+OKLKi4u1rJly1RaOnG+LynRjh07JrfbfcvfH6Tvf//7Ki4u1vLly1VWVqYTJ04kvIZJ8xXHbrdbzzzzjH7605/eMrZv3z6lp6fryJEjOn36tL7xjW/o8OHDuvPOO5NQ6fixc+dOFRUVaeXKlbp06ZJKSkr0pS99SZ/97GeTXdq4cfjwYbW3t+s3v/mN0tPTdeHChWSXNC4NDQ2psbFRS5YsSXYp49KSJUu0adMmTZkyRUePHtWTTz6p1157LaE1TJqZ/bx583TvvffKsm59Sq+++qpWrFghScrLy1N+fr5ef/31RJc47jgcDg0O3vgewOHhYTkcDj709h+ef/55rVu3Tunp6ZKkGTNmJLmi8ekHP/iB1qxZo7vuuivZpYxLX/nKVzRlyhRJ0oIFC3TmzBkFAoGE1jBpwj6Svr4+5ebmhn52uVw6c+ZMEisaHzZt2qRDhw6poKBAhYWFWrNmjWbNmpXsssaVkydP6q9//avKysr0ta99Tfv37092SePO73//ew0ODqq4uDjZpUwITU1N+vKXv3zbielYmjDLOF/96lfV19d327E//elPSkkZ/W3lJhu7nr388ssqLS3V2rVrde7cOa1atUr5+fn63Oc+l+BKk8euR36/X16vV7/61a908eJFff3rX9cnP/lJfeELX0hwpckTqUft7e166qmnQl9lbqpo8+ngwYNqbW1VU1NTIsuTNIHC/pVXXhnxsTk5Ofrggw9CSxRer1eLFy+OV2njll3PXnzxxdC64cyZM3X//ffrzTffNCrs7XqUk5OjkpISWZalrKwsffGLX9Tf/vY3o8I+Uo+6urp0/vx5Pfroo5Kkixcv6ujRoxoYGNC6desSVWLSRZNPR44c0TPPPKMXXnghKcuBRizjFBcX6+WXX5YknT59WidOnFBBQUGSq0q+WbNm6Q9/+IOkGy+wvfXWW5o7d26SqxpfSkpKQj26fPmy3nrrLX36059OclXjh8fj0Z///Gd1dnaqs7NTRUVFWr9+vVFBH42jR4+qrq5O+/btS9pS6aT5bpy2tjY1NDToww8/1JQpU3THHXfo+eef17333qvLly+rqqpK//jHP2RZliorK/XAAw8ku+Sk6+np0fbt23X58mVdv35dDz/8MH+k/2F4eFhbtmxRb2+vJKm0tFSPP/54kqsav6qqqpSfn6+VK1cmu5Rx5f7779eUKVNuegPECy+8kNAXtCdN2AMAwjNiGQcATEfYA4ABCHsAMABhDwAGIOwBwACEPQAYgLAHAAMQ9gBggP8F8Ay7MC4Tf8cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "a6JlqxBbuRu-",
        "outputId": "a27c365b-8a52-49f6-d30c-21eded142f23"
      },
      "source": [
        "dados.loc[:,'g0':'g771'].describe().T['max'].hist(bins=50)\n",
        "plt.show()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "id": "iFif5M8dwLxB",
        "outputId": "af84a3c7-d4b2-4112-8baa-d4f1f2f91e09"
      },
      "source": [
        "dados.loc[:,'c0':'c99'].describe().T['mean'].hist(bins=50)\n",
        "plt.show()"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "kAqp5o1Zxhtf",
        "outputId": "8faf5769-4f74-4657-8454-eba1f592fdc0"
      },
      "source": [
        "plt.figure(figsize=(20,7))\n",
        "sns.boxplot(data=dados, x='g0' )\n",
        "plt.show()"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1440x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "vA2ggm4gzaw0",
        "outputId": "2056998c-8be5-4f67-f7dd-d8cb30819abc"
      },
      "source": [
        "plt.figure(figsize=(20,7))\n",
        "sns.boxplot(data=dados, x='g0', y='tratamento' )\n",
        "plt.show()"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1440x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DZc9vrbzgS-S"
      },
      "source": [
        "##Desafio 01 - Ordernar o gráfico countplot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "ZhWGgFaWgWOA",
        "outputId": "9ab36d0d-d2bb-49db-e2d4-3759f1489543"
      },
      "source": [
        "#Ao calcular o value_counts.index no cod_compostos ele já ordena os valores no array, então basta passa-lo no param oder\n",
        "plt.figure(figsize=(10, 5))\n",
        "sns.countplot(data=dados.query('composto in @cod_compostos'), x='composto', order=cod_compostos)"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f35ab3558d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SxAmRJuOhbtT"
      },
      "source": [
        "##Desafio 02 - Melhorar a visualização alterando tamanho da fonte..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9KeJcrZzh9qF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "74d9866d-9993-444e-f6ab-6e1b1496dddc"
      },
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "sns.histplot(data=dados, x='g19', bins=100, hue='tratamento', hue_order=['com_controle', 'com_droga'])\n",
        "plt.title('Expressão do g19', fontsize=25)\n",
        "plt.xlabel('g19',fontsize=15)\n",
        "plt.ylabel('Contagem', fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "pKckcEms9OX4",
        "outputId": "5976e468-031f-4675-d311-28a7e58993a2"
      },
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "sns.histplot(data=dados, x='g0', bins=100, hue='tratamento', hue_order=['com_controle', 'com_droga'])\n",
        "plt.title('Expressão do g0', fontsize=25)\n",
        "plt.xlabel('g0',fontsize=15)\n",
        "plt.ylabel('Contagem', fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TqIk3E6mv4kS"
      },
      "source": [
        "##Desafio 03 - Plotar os histogramas com seaborn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GmV8sWlNv6KK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "f5e98829-990a-443a-c604-87717eb00976"
      },
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "sns.histplot(data=dados, x='c0', bins=100, hue='tratamento', hue_order=['com_controle', 'com_droga'])\n",
        "plt.title('Expressão do c0', fontsize=25)\n",
        "plt.xlabel('c0',fontsize=15)\n",
        "plt.ylabel('Contagem', fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAGUCAYAAAChu4FLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdd3gVZf7+8fcpSUghCQkBQigqGKoNAlhYZUEBpai7+AVZZOmCoLg2kBJAsISiIkVsiAgouiJKkcAPbFhYEBAjKqsgIIQAqaRwcsr8/shy5JDCSUg5kPt1XVwXM8+Uz3MGkvvMPDNjMgzDQEREROR/zFVdgIiIiPgWhQMRERHxoHAgIiIiHhQORERExIPCgYiIiHhQOBAREREPCgciUqnS0tIYPnw41157LV26dOGll17i5MmTvPPOOzRr1oxffvmlqkss0h9//EGzZs1o1qwZf/zxR1WXI1KhrFVdgEhlmDdvHvPnz/d6eV/9BXUpeO211/jiiy8ICQnhyJEjLFiwgAULFgBw5ZVX0qRJkyqu8NKzceNGVq5cyd69e8nOziYqKoqOHTsydOhQGjduXNXliQ9SOJBqp3bt2lVdQrV2xRVX8K9//YuRI0dy4sQJtm7dyoEDB4iIiODuu+/GatWPpfJiGAYTJkxg1apVAJjNZoKCgjhy5AgrV67k448/Zu7cudxyyy1VXKn4Gv0vlGrnq6++quoSqrV77rnH/feoqCjuvvvuKqzm0vb666+7g8GYMWMYMmQIwcHB7N+/nwkTJrBr1y4efvhhPv74Yxo2bFjF1Yov0ZgDEZFLUGZmJi+//DIAffv25cEHHyQ4OBgoOHvzyiuvEBUVRW5uLi+99FJVlio+SGcORM5jypQpvPvuu9SsWZPVq1fToEGDQsusWLGCadOmYbFYeOutt2jXrh1QMIitS5cuAGzevBmHw8GiRYv4+uuvSUtLo3bt2tx8882MHj2aunXrFtrutm3bGDhwIFAwDmLv3r288cYbbN++ndTUVNq0acPbb7/tXj4/P5/333+fDRs2sG/fPnJycggLC+Pqq6+mX79+xZ4+Pn36NMuXL2fjxo3s37+f3NxcatasSUREBFdddRWdO3emW7duHus4HA4++OAD1q5dy759+8jOziYkJITw8HBatGjBTTfd5HGWACArK4vExES2bt3K/v37SUlJIS8vj8jISNq0acOAAQNo06ZNicfj0KFDvPHGG3zzzTccO3YMq9VK48aN6dKlC4MGDSIkJKTE9UuSkpLCggUL+Pzzz0lNTSUiIoKbbrqJkSNHYrFYzrv+iRMnWLx4MV988QVHjhwBICYmhltuuYUhQ4Zc8CWtrVu38sEHH7B7925SU1OpUaMGdevWpX379vTs2ZPrrrvOveymTZvIyckB4P777y+0rbCwMPr168e8efPYuHEj06ZNIygo6ILqk0uHSS9ekurg7AGJpR1sePr0afr06cN///tfrrvuOpYtW+ZxXXzfvn306dMHm83G6NGjeeihh9xtZ4eDF154gUmTJpGTk0NQUBAul4vTp08DEB4ezuLFi2nVqpXHvs8OBy+99BKPPvoodrudkJAQ7HY711xzjTscHDlyhPvvv5///ve/AJhMJkJCQjh16pR7e/369WPatGke+8jOzuYf//gHP//8s3u9mjVrkpubi8PhAAp+wW3ZssW9jtPpZPjw4R6XaGrWrInNZiM/P98979zPeuHChcydOxcAi8VCSEgIeXl57nVMJhPjx49n0KBBRR6L9evXM27cOPfywcHB2O1293R0dDRvvPFGmQY1/vjjjwwePJjMzEwAatSogdlsJjc3l5CQEKZPn86//vUvoCDonRsS//Of/zB69GiysrIA3L9oc3NzgYJfxgsXLiQuLq7UteXl5TF+/Hg2bNjgnhccHIzZbHYf3+bNm/PRRx+52x955BHWrVtH06ZNWbduXZHb3bNnjzvAvf766/zlL38pdW1yiTJEqoGXXnrJiI2NNWJjY8u0/i+//GJcffXVRmxsrPH888+75+fl5Rk9evQwYmNjjX79+hkOh8NjvcOHD7v327ZtW6NXr17G999/bxiGYbhcLuPLL780OnXqZMTGxhqdOnUyTp065bH+t99+617/2muvNYYPH278+uuv7vYDBw4YhmEYOTk5Rvfu3Y3Y2FhjwIABxrZt2wybzWYYhmFkZWUZb775pnHttdcasbGxxpIlSzz2sWDBAiM2NtZo3769kZiY6F7P6XQax44dMz788ENj0qRJHuusXr3aiI2NNa666irjvffeM7Kzs919OnnypLFx40bjwQcfLPQ5vvfee8bcuXONH374wb0fl8tlHDp0yJgxY4bRrFkzo3nz5sYPP/xQaN2kpCSjVatW7s/6559/dte5efNm46abbjJiY2ONW2+91V2Pt06dOuVxHLZu3Wq4XC7DMAxj586dRo8ePYy4uDj3sTh8+LDH+kePHnW333HHHcaOHTvcbdu3bze6devm/oyPHTtWqtoMwzDGjh1rxMbGGs2bNzdmzZplJCcnu9tSU1ONjz/+2IiPj/dYp2fPnkZsbKwxduzYYrebm5vr7tPixYtLXZdcuhQOpFo4OxzceOONJf6ZPn16kdtYsWKF+wf0N998YxiGYUyePNmIjY014uLijCNHjhRa5+xw0L59e+PkyZOFlvn111/dv/Ree+01j7azw0GfPn0KhY8z5s+f7w4G+fn5RS6zceNGIzY21ujQoYNht9vd84cNG2bExsYaixYtKvrDK8KUKVOM2NhYY/LkyV6v441p06YZsbGxxpNPPlmobejQoUZsbKxx2223Gbm5uYXaf/zxR6Nly5ZGbGys8frrr5dqv6+++qoRGxtrtGrVyiN8nXH8+HGjXbt2xYaD+Ph4IzY21mjXrp1x/PjxQusnJycbbdq0MWJjY41p06aVqravv/7avd/ly5d7vV779u2N2NhY45lnnilxuTOh5rnnnitVXXJp04BEqXZOnjxZ4p/s7Owi17v33nvp2rUrLpeLxx9/nJUrV7Jy5UoApk+fTv369Uvcb79+/YiMjCw0v0mTJu7r+evXry92/aFDhxZ73fuDDz4AYNCgQfj5+RW5zK233kpISAjp6en8+OOP7vmhoaFAwfVyb5VlHW+cGRPx3XffeczPyspi69atQMHnEBgYWGjdli1bcttttwEUexq9OGc+9+7duxd5SSIqKop+/foVua5hGO7T/f369SMqKqrQMvXq1XOvX9ra/v3vfwMQGxtL//79vV7vzHiDGjVqlLjcmfYzy4uABiRKNXQhDziaMWMGSUlJHD16lPj4eKDg1rzu3bufd93rr7++xLa1a9fyyy+/YLfbi/wFX9xAvZSUFPfgt4kTJ7rrKsqZ699HjhzhmmuuAaBTp06sXbuWZcuWkZaWxh133EGbNm2IiIgodjs333wzr776Klu2bGHYsGHcddddtGvXrshBlec6fPgwK1asYNu2bRw6dIicnBxcLpfHMsePH/eY/vHHHzH+NzzqxhtvLHbbN910E5988kmJn+O58vPz2bdvH3D+Y/TKK68Umv/HH3+QkZEBwA033FBiba+//joZGRkcPnzY61sHd+3aBRQcJ5HKonAgUgphYWHEx8czcuRIABo2bMjEiRO9WrekX5xn2hwOB5mZmUWOai/qrAMUhIMz0tPTvarlzEBIgF69erFnzx6WLVvGunXr3N9sGzduzE033cTf//53Wrdu7bF+XFwcjz32GC+++CJffvklX375JVDwDfnGG2/kzjvvLPIX7aZNm3jkkUc8Bi2GhIQQEBCAyWTCbreTmZnpDjFnpKWluf9+oZ/juTIzM90DL73Z9rlSU1NLVRsU9MfbcHDy5EmA856ZOldwcDAZGRkex7ooZ9rP3OYoAgoHIqX23nvvuf+ekpLCwYMHad68eYXvt7hLCmd/616/fn2ZRupPnDiRAQMGsGHDBnbs2MHu3bs5ePAgBw8eZMWKFQwcOLBQCBo2bBi9evXik08+Yfv27ezatYtjx46xatUqVq1aRbdu3ZgzZ47723t6ejrjx48nPz+f66+/ntGjR3P11Vd7nPb+5ptvir1ToboymUxlWq9OnTpkZGR4hMdz5eXlue+uqFOnTpn2I5cmjTkQKYVly5axZcsWLBYLTZs2JT8/n0ceeYS8vLzzrlvSD+kzbVarlbCwsFLVdPa346NHj5Zq3bM1btyY+++/n9dee41t27axcuVKbr31VgCWLl3K5s2bC61Tt25dBg0axIIFC/j666/5+OOP3bfGJSYm8s4777iX/fzzz8nOziYsLIxFixbRvn37QtfDixvDcPYljmPHjhXbh7J8jmFhYe7gVdIxOvdSxxlnn9Hx5hgDJV6yOdeZ41vaY3vllVcCuG9tLcrZbU2bNi3V9uXSpnAg4qVffvmFmTNnAvDAAw/w6quvEhoaym+//cazzz573vW3bdt23rZmzZp5dZ38bA0aNHCfsv70009LtW5xzGYz1157LS+99JL7dPbXX3993vWaNWvGjBkz3OMjzl7nzC/1yy+/vMgBhVBw5qAorVq1wmw2l7jM2fsrzefo7+9Ps2bNgJKP0bffflvk/AYNGhAeHu51beHh4aV6VPGZBxuV9tieGZvx22+/FRssvvjiC6BgUGLbtm1LtX25tCkciHjh9OnTPPLII9hsNtq2bcuoUaOIiYnhqaeeAmDlypUkJiaWuI13333X49r5Gfv373eve/vtt5epvv/7v/8DCka27927t8RlzwyeO+Ps6//nslgs7l+yZ5/eLmkd+HME/Nnr1KxZE4Dff/8dm81WaJ2ffvqJNWvWFLm90NBQOnbsCMAbb7xR5Jman3/+mY0bNwLQs2fPEus715nPfcOGDezfv79Qe2pqKu+++26R65pMJvf6K1euLPLsR0pKivvOltLW1qdPH6DgW/6KFSu8Xu+2224jODgYwzB49dVXC7VnZWW5+9S1a1c9HVE8KByIeOGZZ57h119/JTQ0lNmzZ7tPQ99+++3uH96TJ08mOTm52G04HA6GDBnCnj17gIJb4L7++muGDRtGfn4+0dHR3HvvvWWqb/DgwcTGxmKz2Rg4cCDLli3zGJyYlZXF559/zhNPPME//vEPj3XvueceZsyYwbZt2zwGAqakpDB9+nQOHjwI4PHo5QceeIAnn3ySzz//3H3NGgqCx8KFC93foM8eYX/TTTdhNpvJyMjgsccec59mz8/PZ/369e6XAhXn4Ycfxs/Pj4MHDzJ06FD3XScul4vPP/+c4cOH43A4aNSoEX379i3V59e/f3/q1atHfn4+w4YN45tvvnHfHfH9998zaNCgQndUnG3kyJGEhoaSkZHB4MGD2blzp7vtu+++Y/DgwWRlZREeHs6IESNKVdv1119Pjx49gIJbZufMmeNxaSUtLY3333+fCRMmeKwXFhbGqFGjgIJgOn/+fPfxPXDggPutmEFBQR5P9RQBPT5ZqomzH5/szQj2efPmuU+Nb9y4kQcffBCAuXPnFrptMS8vj7/97W/s37+fuLg4li5d6g4PJT0+2TAM9zfg0NBQFi9ezFVXXeWx7XPfrVCSlJQUHnroIXbv3g38+Rhkl8vl8eyGxo0bu79hA3Tu3Nl9K+SZdRwOh0dQGDRoEE8++aR7+r777uM///mPe/rM+wzO3k+3bt148cUX3ZcDAGbPns1rr73mnq5ZsyanT5/GbrfToEEDHn74YR577LFi+7t+/XqeeOIJ7Ha7e792u919JuJCHp/8ww8/MGTIEHfYCQwMxGQykZubS3BwMDNmzDjv45MfeOAB9+OMz318cmhoKC+//HKZH5/8xBNPeBy3kJAQTCZTsY9PhsKvbLZYLAQFBbnXCQwM1CubpUiWqVOnTq3qIkQq2n/+8x/3L7Pc3Nzz/rnzzjtp0KABycnJjBgxApvNRp8+fYp8gY2fnx9t27Zl1apVHD58GLPZTPv27YGCb+xLly4F4IknnqBPnz5kZ2dz/PhxcnJyiIqKokePHrzwwgtF/kI7cuQIH374IYA7oBQnJCSEv/3tbzRp0gS73U5OTg6nTp3CMAzq1atHXFwc/fv3Z9y4cR7f0K+55hqio6PdgSY7OxuHw0F0dDR/+ctfmDhxYqEzGq1atSImJgY/Pz9MJhM5OTnk5+dTu3ZtOnTowCOPPMKYMWMKjbS/8cYbadiwIcePHyczMxPDMGjQoAF9+/Zl5syZ5ObmltjfK6+8kh49epCfn8+pU6fIzMzEarXStGlT7r33XmbOnEm9evVK/JyKU7duXXr16kVOTg6pqank5OQQHh5O165dmT17NtHR0e5j+c9//tP9IKgzYmJiuOuuuzCZTGRlZblDRuPGjbn77ruZPXu2e5Bgafn5+XHHHXdw1VVXYbPZyM7OJjs7m4CAABo3bswdd9zBqFGjCt1KaTKZuPXWW4mNjXXXlJeXR7169bj99tuZNWuW+3kXImfTmQORCnTuWxmLeqOjiIiv0ZgDERER8aBwICIiIh4UDkRERMSDwoGIiIh40IBEERER8aAzByIiIuJBb2UE0tNzcLnK5wRKZGQIqanZ51/wElLd+lzd+gvqc3VR3fpc3foLBX32hsIB4HIZ5RYOzmyvuqlufa5u/QX1ubqobn2ubv31li4riIiIiAeFAxEREfGgcCAiIiIeNOagCE6ng/T0EzgcJb+zvijHj5tLfLXrpcgX+2y1+lOrVhQWi/6Ji4iUln5yFiE9/QQ1agQRHFyv0FvlzsdqNeNw+NYvyorma302DIOcnCzS009Qu3Z0VZcjInLR0WWFIjgc+QQHh5Y6GIhvMJlMBAeHlunMj4iIKBwUS8Hg4qbjJyJSdgoHIiIi4kHhoAr06dOL7du3lXn9p5+eyquvLizHisqPL9cmIiLeUTjwMQ6Ho6pLEBGRak53K1Sy6dMnk5JyjHHjHsFiMTNo0DBefnke48dPYvHi14iOrs+CBa8xadI49uzZjc12mqZNY3n00fFccUUTPvpoFRs3foLJZOL999/huuvimDnzBd5+ewlr1nxIeno6devWZfjwB7jllr8CsH79Gtas+ZAWLVqxfv0aatYMIz7+KQ4fPsTrry8iPz+f0aPHcvvtPQHIz8/n1VcXsmXLJux2Ozff3ImHHnqEgIAa7Ny5g+nT4/m//+vP8uVvYbGYGTVqDN279yq2tt9/P8Ds2c/y66/7qF27DiNHjqZjx1uq8jCIiEgJFA4q2eTJ0/n++92MGzeJdu06kJx8lJdfnseuXTtZvvzfmM0FA+muv/5GJkyIx2r14+WX5/HUU5NZsmQFd975N5KS9hAVVYcRIx5wbzcmpgELF75OREQkn376/5g+fTKtWq2mdu3aAOzd+yM9e97FunWbeeONV5gyZQI33XQz7777Ibt372TixCe45ZbOBAUFsWjRPI4c+YMlS1ZgtVqZOnUSb775OiNHjgEgLS2VnJxsVq/+hO3bv2XSpPHceOMtRdbmcDgYN+5f9OjRmxdeWMCePbsZP/5R3nhjKY0aXVa5H76IiHhFlxV8xJAhIwgMDCQgoAYAPXveSVBQMP7+/gwZMoJff91Hdnbxbw/r3PlWateOwmw206VLVxo0aMRPPyW526Oj69OjR28sFgtdunTl+PEUBg8ehr+/P+3bX4+fnx9HjhzGMAw+/vhDHnroUUJDwwgKCmbgwMFs3rzRvS2LxcqgQcOwWq3ccENHgoICOXToYJF1/fjjD+Tl5TFgwCD8/Pxo27YdN97YkU2bEsvpkxOR8mS1mt1/pPrSmQMfUbduPfffnU4nr766kE8//X9kZGS4zyZkZmYQElL06zY/+WQtK1eu4NixowDk5eWRmZnhbq9VK8L994CAAAAiIiI95uXm5pGRkc7p06cZOnSAu80wDI8nIIaFhWG1Ws9atwZ5eblF1nXy5Anq1KmL2fznD5p69aI5efJECZ+GiFQ2q9VM9s/byE89CYBfSBjWRtf51APOpPIoHFSB892Dv2nTBrZu/ZwXX1xIdHR9srOzuf32v2IYRpHrHzuWzMyZT/Piiy/TuvVVWCwWBg3qj1GGN5GGhYUTEBDA22+/R1RUnVKvf25ttWtHcfx4Ci6Xyx0QUlKO0bBho9IXJyIVypmbiT0r1T3tX4W1SNXSeaMqUKtWBEePHim2PTc3Fz8/f8LCwjh9+jSvvLKgxPXz8vIwmUzUqhUOwLp1H3PgwG9lqs1sNtOr19289NLzpKenAXDixHG2bfvGq/XPra1ly9YEBNRg+fKlOBwOdu7cwVdffcmtt3YrU30iIlLxFA6qwH33DeKtt96ge/dOfPrp5kLt3bv3oF69etx11x0MGHAPrVq19mjv2fNOfv/9AN27d+LJJx/l8suvoG/ff3D//UPo3bsr+/f/ylVXXVPm+kaNepAGDRoyYsRguna9hYcffqDYMQXnOrc2Pz8/EhKeZ9u2r+nRowvPP5/ApEnTaNz4sjLXJyIiFctkGGU5+XxpSU3NxuX682M4duwg9eo1LtO2fO0lRJXBV/t8IcexJFFRNTlx4lS5b9eXqc+XPqvVjPnAV5xKOQaAX2gk/i07+eT/7fJS3Y4xFPTZGzpzICIiIh4UDkRERMSDwoGIiIh4qNRwkJCQQOfOnWnWrBn79u1zz7fZbEyZMoWuXbvSq1cvJk+e7G47cOAAffv2pVu3bvTt25fff//dqzYREREpm0oNB126dGH58uXExMR4zJ81axYBAQEkJiayZs0axo4d626bMmUK/fv3JzExkf79+xMfH+9Vm4iIXACTCYvFrCcmVlOVerTj4uKIjo72mJeTk8Pq1asZO3as+wE6Z94HkJqayt69e+nZs+CFQD179mTv3r2kpaWV2CYiIhfGGhyK8+BO8vd+Rv7ezzAO7VJAqEaq/AmJhw8fJjw8nPnz57Nt2zaCg4MZO3YscXFxJCcnU7duXSwWCwAWi4U6deqQnJyMYRjFtkVERJS0SxER8YIjO0NPTKymqjwcOJ1ODh8+TMuWLRk3bhzff/89I0eOZNOmTZVWQ2Sk5/sKjh+/sFNo1TFd+2KfzWaz1/f0llZFbdeXqc+XvswDEBRc8O4V/wArTqcflv9NWwL9CKsVXJXlVYjqdoy9VeXhIDo6GqvV6r48cM0111CrVi0OHDhA/fr1SUlJwel0YrFYcDqdHD9+nOjoaAzDKLattM59CJLL5Sr04I+w8CD8/SwX1tki5NudZGYU/dKii4WvPgTJ5XJVyANOquuDU9TnS5vVasYM5ObYADBsDlw2O7b/TftZ7LjSc3zy/3pZVbdjDN6HoSoPBxEREXTo0IGvvvqKjh07cuDAAVJTU2ncuDGhoaG0aNGCtWvXcuedd7J27VpatGjhvmxQUlt58/ez8Nqq78+7nNls8gga5zP8b2V/zPHF5I03XmHgwCH4+fmVad28vDzGjHm4AioTqb7OPuNnsZip9o/LFbdKDQczZsxg48aNnDx5ksGDBxMeHs66deuYNm0aEyZMICEhAavVysyZMwkNDQVg6tSpjB8/noULFxIaGkpCQoJ7eyW1iW95883XuPfe+4oMBw6Hw+MV0CJS8axWM8ahXdizMwGoERVznjWkOqnUn8iTJk1i0qRJheY3bNiQt99+u8h1mjRpwvvvv1/qtktNUtIeFiyYS25uwSWI0aPHUrNmTV58cTanT+dRo0YgDz/8GC1atCI5+SjDht1Hr153s23b19hsNuLjZ/DRRx+wd28S/v4BPPfcHCIjaxe7v99/P8DcubNJS0vFMAzuvfc+br+9J3/8cZhZs54hIyMdi8XCiBGj6dixIwAdO8YxYsQDfPHFZ2RmZjJ69EN06tSFOXMKQtuoUUMwmczMm/cKL700B4vFwqFDB8nNzWXJkhUsW7aExMT1ALRo0YqHH36coKCgQrUtW7aEzz/fgtPppHbtOowbN7HEvohI0ezZf76i2RoSVvWnksVn+N4oMikkKyuTCRMe54EHHuKtt95h8eJlNG16JRMnPsHw4aN46613GTZsJBMnPoHdbgcgMzOTq6++ljffXEHPnnfy8MOj+Nvf7uGtt96lWbMWfPDBe8Xuz+FwMH78o/TqdTdvvfUuS5eu5MYbCwLAtGmTuO22brz11rtMnjyd6dMnk56e7l43ODiY119fyuTJ03jxxdkAPProOABefnkxS5asoGbNgmte//3vPubMmceSJSv45puvSExcz6JFi1m6dCVOp5MlS14vVFti4nqOHDnCK68sYfHi5dxww03Mn/9i+XzQIiIC+MCYAzm/pKQfuOyyy92vYbZYLKSnp+Pn50dcXHsA2rXrgJ+fH4cOHSQoKIjAwCD3L/TY2OZERdXhyiubAdC8eXO2b99W7P4OHTqI0+mkc+db3fPCwsLJzc3h11/3cccdvQG4/PIraNq0GUlJe7jhhr8A0KVLNwBatbqKkydPYLPZCAgIKHI/nTp1ITAwEIAdO/5Dly5dCQ4uuHOkd++/MXfu7ELrbN36BT///BNDhgwAwOl0EBISUmg5EREpO4WDS5S//5/X9s1mM/7+AWdNF9zdUTH7LbgT+szzJ0raT1BQYKm3bxgG//znEHr2vLNsBYqIyHnpssJFoHXrq/j99wMkJe0BCn7h1qpVC7vdzs6dOwD47rvtOBwOGjVqfMH7a9SoMRaLhS1b/p97XmZmBkFBwTRtGssnn6wFCsYl/PbbPlq3vvq82wwKCiYnJ7vY9ri49mzZsonc3BwMw2Dt2tW0a9eh0HIdO97Mhx/+m6ysLADy8/P573/3FVpORETKTmcOvJRvd1bIbYf59vN/gw8NDePpp2cyb94LnD6dh8lkZvTosTz99EyPAYkzZiSU6VbBc1mtVp57bg4vvDCTJUtew2Qyc++9A+jevQdTpsxg1qxneO+9FVgsFiZNeopatWqd997nfv3+wUMPjSQgoAbz5r1SqP2GG27it9/+y/33DwagefOW/POfQwst1717DzIzM3jwwRFAwbMM7r77Hq68MvaC+y0iIgVMhmFU+1tbz30I0rFjB6lXr2zfwH31gUAVyVf7fCHHsSTV9cEp6vOlxWo1k7/3M/fdCoH1r8DqzOVUyjH3tCs3E1tGQbtfaCT+LY8LYfYAACAASURBVDv55P/1srrUj3FRvH0Iki4riIiIiAddVqjG1qxZXeQtjRMnTnHf2SAiItWPwkE11qvXXfTqdVdVlyEiIj5GlxVERETEg8KBiIiIeNBlBREROT+TCYul8PfJS+nuBfmTwoGXIsJrYCmHZwicy2m3k5Zxuty3KyJSnqzBoTgP7iQ/K8M9zy8kDGuj6xQQLkEKB16y+PnxxydLz7uc2WzyeGbC+TS4fSDg++GgT59ezJz5Aldc0bSqSxGRKuLIznA/F+EM/yqqRSqWxhzIBXE4HFVdgoiIlDOdObhIJCXtYcGCueTm5gIwevRYatas6fH45IcffowWLVqRnHyUYcPuo1evu9m27WtsNhvx8TP46KMP2Ls3CX//AJ57bg6RkbWL3d/33+9izpznALj22jac/SDNPn160aVLV3bu3M4VVzTl0UefYPbsBH766Ueg4BHH//jHPwE4cGA/zzwzjdOn87jyymb88cdh/vnPodx00194551lbN68EafTgb9/AI89Nl7PVxAR8QEKBxeBrKxMJkx4nKefnslVV12D0+kkMzODYcMGMmHCFOLi2rN9+zYmTnyClStXA5CZmcnVV1/LyJFjWLFiKQ8/PIp5815h3LhJzJ79HB988B4jRjxQ5P7y8/OZMmUC8fHTadMmjs2bN7Fq1fsey+Tk5PDaawWXWRYtmofL5WLp0pXk5uZw//1DuOKKptxww01Mnx5P37796dbtDn7+eS8jRgxyb6N79x7ce2/Bq5e3b9/GrFnP8uqrS8r/AxQRkVLRZYWLQFLSD1x22eVcdVXBi58sFgvp6en4+fkRF9cegHbtOuDn58ehQwcBCAwM4sYbOwIQG9ucqKg67m/lzZs358iRw8Xu79Chg9SoUYM2beIA6NLlNkJCQjyW6d69h/vv27dvo1evuzGZTAQHh3DrrV3ZseM/5ORkc+DAb9x2W/f/7bclTZr8OWbhl19+YvTo4dx33/8xf/4L/Pqr3q4oIuILdObgEuXv/+edFWazGX//gLOmLTid538bpCeTx1RQUKD3a5pMhebZ7XYmTx7H/Pmv0axZc06ePMFdd91eyppERKQi6MzBRaB166v4/fcDJCXtAcDpdFKrVi3sdjs7d+4A4LvvtuNwOGjU6MLfQtioUWNsNhvff78LgE8//X9kZxf/5rJ27Tqwbt1HGIZBbm4OmzdvpF27DgQHh3D55VewaVMiAL/88jP79/8GQH6+DafTSZ06dQEKXbYQEZGqozMHXnLa7f+77bD8t3s+oaFhPP30TObNe4HTp/MwmcyMHj2Wp5+e6TEgccaMBPzK4VkM/v7+TJ36NHPmPIfJZOKaa66jbt16xS4/ZMhwZs16joED+wLQrdsdXH/9jQBMmjSNZ599imXL3uSKK5pyxRVNCAkJITg4hKFD72f48IGEhobx1792ueC6RUSkfJiMs4ehV1OpqdkezyY4duwg9eqV7Ru41Wqudg8EKanPubm5BAYGYjKZOHBgPw8+eD8rVnxAaGhohdd1IcexJNX1HfDq86XFajWTv/cz93MLAutfgdWZy6mUY+5pV24mtozUIqcB/EIj8W/Z6aL9mXepH+OiREXV9Go5nTmQCnXmFkwoCF/jxk2slGAgIoVZrX9eSS7qUcgiZygcVGNr1qzmgw/eKzR/4sQp5fa8gfbtr6d9++vLZVsiUnZWqxnj0C7s2ZkA1IiKwax8IMVQOKjGevW6i1697qrqMkSkktizM92XEawhYVVcjfgy5cZiaCjGxU3HT0Sk7BQOimC1+pOTk6VfMBcpwzDIycnCatUrYUREykKXFYpQq1YU6eknyM7OOP/C5zCbzbhcF+fI3bLyxT5brf7UqhVV1WWIiFyUKj0cJCQkkJiYyJEjR1izZg2xsbEe7fPnz2fevHkebbt37yY+Ph6bzUZMTAyzZs0iMjLyvG1lZbFYqV07ukzrVtdbY6pbn0VELmWVflmhS5cuLF++nJiYmEJtP/74I7t37/Zoc7lcPP7448THx5OYmEhcXByzZ88+b5uIiIiUTaWHg7i4OKKjC38rz8/P56mnnmLq1Kke85OSkggICCAuruAlQP369WPDhg3nbRMREZGy8ZkBiXPnzqV37940aNDAY35ycjL169d3T0dEROByucjIyCixTURERMrGJwYk7tq1i6SkJB577LEq2X9kZMj5FyoFbx9PeSmpbn2ubv0F9flSkBnoh5+z4A2t/gFWnE4/LMFnTedCUHAJ7WdNA1gC/QirFVzJvShfl9oxLi8+EQ62b9/Ob7/9RpcuBS/fOXbsGEOHDuXZZ58lOjqao0ePupdNS0vDbDYTHh5eYltpnPtuhQtRHQfnVbc+V7f+gvp8KbBazeTn2bHn2AAwbA5cNju2s6atQG4J7WdPA/hZ7LjSc/RuhYvIRfVuhREjRjBixAj3dOfOnVm0aBGxsbG4XC5Onz7Njh07iIuL491336V79+4AtG7dutg2ERERKZtKDwczZsxg48aNnDx5ksGDBxMeHs66deuKXd5sNjNz5kymTJnicbvi+dpERESkbPTKZnRZ4UJVtz5Xt/6C+nwpKOoVzee+klmvbL70eXtZwWfuVhARERHfoHAgIiIiHhQORERExINP3K0gIiLlz2r98/ufxaLvguI9hQMRkUuQ1WrGOLQLe3YmADWiYjArH4iXFA5ERC5R9uxM990J1pCwKq5GLibKkSIiIuJB4UBEREQ8KByIiIiIB4UDERER8aBwICIiIh4UDkRERMSDwoGIiIh40HMORESkbEymQk9evFjf0CieFA5ERKRMrMGhOA/uJD8rAwC/kDCsja5TQLgEKByIiEiZObIz3E9hBPCvwlqk/GjMgYiIiHhQOBAREREPCgciIiLiQeFAREREPCgciIiIiAeFAxEREfGgcCAiIiIeFA5ERETEg8KBiIiIeFA4EBEREQ8KByIiIuJB4UBEREQ8KByIiIiIh0oPBwkJCXTu3JlmzZqxb98+ANLT0xk+fDjdunWjV69ejBkzhrS0NPc6u3fvpnfv3nTr1o0hQ4aQmprqVZuIiIiUXqWHgy5durB8+XJiYmLc80wmE8OGDSMxMZE1a9bQsGFDZs+eDYDL5eLxxx8nPj6exMRE4uLivGoTERGRsqn0cBAXF0d0dLTHvPDwcDp06OCevvbaazl69CgASUlJBAQEEBcXB0C/fv3YsGHDedtERKobq9Xs/mOx6KqxlJ21qgs4l8vl4p133qFz584AJCcnU79+fXd7REQELpeLjIyMEtvCw8MrvXYRkapitZoxDu3Cnp0JQI2oGMzKB1JGPhcOpk+fTlBQEAMGDKi0fUZGhpTr9qKiapbr9i4G1a3P1a2/oD5fDDIP5IIzGwCL6zT+AX5YggMA8A+w4nSeZzoXgrxcvqh5lkA/wmoFV05ny8nFdowri0+Fg4SEBA4ePMiiRYsw/y/yRkdHuy8xAKSlpWE2mwkPDy+xrTRSU7NxuYxy6UNUVE1OnDhVLtu6WFS3Ple3/oL6fDGwWs3k59mx59gAMGwOXDY7tlJMW4FcL5cvap6fxY4rPQeHw1Upfb5QF9sxLg/ehiGfOen0/PPPk5SUxIIFC/D393fPb926NadPn2bHjh0AvPvuu3Tv3v28bSIiIlI2lX7mYMaMGWzcuJGTJ08yePBgwsPDefHFF3nllVe47LLL6NevHwANGjRgwYIFmM1mZs6cyZQpU7DZbMTExDBr1iyAEttERKSSmUyFBkJeLGcRxFOlh4NJkyYxadKkQvN/+eWXYtdp06YNa9asKXWbiIhUHmtwKM6DO8nPygDALyQMa6PrFBAuQj415kBERC5ujuwM7Fl/PozOv4RlxXf5zJgDERER8Q0KByIiIuJB4UBEREQ8KByIiIiIB4UDERER8aBwICIiIh4UDkRERMSDwoGIiIh4UDgQERERDwoHIiIi4kHhQERERDwoHIiIiIgHhQMRERHxoHAgIiIiHhQORERExIPCgYiIiHhQOBAREREPCgciIiLiwVqahffs2cOmTZtISUnBZrN5tJlMJl588cVyLU5EREQqn9fhYMmSJTz33HPUrl2bBg0a4OfnV5F1iYiISBXxOhwsXryYgQMH8uSTT2IymSqyJhEREalCXo85yM/Pp1OnTgoGIiIilzivw8Hdd9/Nxo0bK7IWERER8QFeX1Z4/PHHeeqppxg0aBDXX389NWvW9Gg3mUz079+/3AsUERGRyuV1OPj2229Zs2YNOTk5fPvtt4XaFQ5EREQuDV6Hg2nTpnHNNdcwceJEGjVqpLsVRERELlFejzk4fvw4w4YNo0mTJgoGIiIilzCvw8ENN9zAzz//fEE7S0hIoHPnzjRr1ox9+/a55x84cIC+ffvSrVs3+vbty++//37BbSIiIlI2XoeD++67j5UrV7Jw4UJ27tzJr7/+WujP+XTp0oXly5cTExPjMX/KlCn079+fxMRE+vfvT3x8/AW3iYiISNl4PeZg8ODBALz00kvMmzfPo80wDEwmEz/99FOJ24iLiys0LzU1lb179/Lmm28C0LNnT6ZPn05aWhqGYZSpLSIiwttuiYiIyDm8DgdLly6tkAKSk5OpW7cuFosFAIvFQp06dUhOTsYwjDK1KRyIiIiUndfhoH379hVZR5WKjAwp1+1FRdU8/0KXmOrW5+rWX1CfLwaZgX74OQMA8A+w4nT6YQkuxXQuBHm5vDfLWAL9CKsVXAk9L7uL7RhXllK9lRHg888/JykpiWPHjjFq1Cjq16/P9u3badSoEXXr1i11AdHR0aSkpOB0OrFYLDidTo4fP050dDSGYZSprbRSU7NxuYxSr1eUqKianDhxqly2dbGobn2ubv0F9fliYLWayc+zY88peGOuYXPgstmxlWLaCuR6ubw3y/hZ7LjSc3A4XBX/AZTBxXaMy4O3YcjrAYknT57knnvuYdSoUaxevZp///vfpKenA7Bq1SoWLlxYpkIjIyNp0aIFa9euBWDt2rW0aNGCiIiIMreJiFQHVqvZ/cdi8frHuch5eX3mYPr06eTm5vLJJ58QExND69at3W033HADCxYsOO82ZsyYwcaNGzl58iSDBw8mPDycdevWMXXqVMaPH8/ChQsJDQ0lISHBvU5Z20RELmVWqxnj0C7s2ZkA1IiKwax8IOXE63Dw5ZdfkpCQQOPGjXE6nR5t9erVIyUl5bzbmDRpEpMmTSo0v0mTJrz//vtFrlPWNhGRS509OxN7VioA1pCwKq5GLiWlGnNw5s6Ac6WnpxMQEFBkm4iIVFMmU6HLHb46/kA8eX0SKi4ujrffftvjrIHJZALggw8+4Prrry//6kRE5KJlDQ7FeXAn+Xs/I3/vZxiHdmG16trHxcDrMwePPfYY/fv3p2fPntx2222YTCbee+89fv31V/bt28fKlSsrsk4REbkIObIz3Jc+APyrsBbxntcRLjY2llWrVtG6dWtWrVqFxWJh06ZN1K1bl/fee4/LL7+8IusUERGRSlKqMQeNGjVi1qxZFVWLiIiI+ABd/BEREREPXp85GDhwYLFtZrOZkJAQmjdvzt///vcyPaVQREREfIPXZw7Cw8M5dOgQO3fuxGazERQUhM1mY+fOnfz+++/k5eXx9ttv06NHD/bs2VORNYuIiEgF8joc/PWvfyUiIoLNmzezcuVKFi1axMqVK9m8eTO1atWie/fubN68maZNm/L8889XZM0iIiJSgbwOBwsWLOCBBx4o9HKlunXrMnr0aF5++WVCQkIYNGgQ33//fbkXKiIiIpXD63Bw4sQJ8vPzi2yz2WykphbcxxoZGVk+lYmIiEiV8DoctGvXjjlz5vDjjz96zP/hhx+YM2cO7du3B+DgwYPUr1+/fKsUERGRSlOqtzKOHDmSPn36ULt2bSIiIkhLS+PkyZM0a9aMp556CgCXy8WwYcMqrGARERGpWF6Hg+joaD766CM+++wzkpKSOHHiBFFRUVx11VXccsst7uX69etXIYWKiIhI5SjVExIBOnXqRKdOnSqgFBEREfEFpQ4HDoeD5ORkbDZbobamTZuWS1EiIiJSdbwOB3a7nRkzZrB69epi71r46aefyq0wERERqRqles7BZ599xtNPP41hGEyePJlnn32WG264gZiYGBYtWlSRdYqIiEgl8TocfPLJJ4wZM4bbb78dgKuvvpq77rqLxYsX07ZtWzZv3lxhRYqIiEjl8TocHDt2jMsvvxyLxUJAQABZWVnutl69epGYmFghBYqIiEjl8jocREVFuQNBgwYN2L59u7vt0KFD5V+ZiIiIVAmvByS2b9+eHTt20LlzZ+655x5mzZrFoUOH8Pf3Z/369fTo0aMi6xQREZFK4nU4+Ne//kV6ejoAgwYNAmDDhg3YbDYGDBjA6NGjK6RAERERqVxeh4OoqCiioqLc04MGDXKHBBEREbl0eD3moEuXLvz8889Ftu3bt48uXbqUW1EiIiJSdbw+c3DkyJFiH350+vRpUlJSyq0oEREpzGr98/ucxeL1dzuRUisxHGRnZ3vcsnjixAmOHj3qsYzNZmPdunXUqVOnYioUERGsVjPGoV3YszMBqBEVg1n5QCpIieFgyZIlzJ8/H5PJhMlkYsyYMUUuZxgG48ePr5ACRUSkgD07E3tWKgDWkLAqrkYuZSWGg549e9K6dWsMw2DUqFGMGzeOyy+/3GMZPz8/Lr/8curXr3/BxXz66afMnTsXwzAwDIMxY8bQtWtXDhw4wPjx48nIyCA8PJyEhAQuu+wygBLbREREpPRKDAeXXXaZ+xft0qVLadmyJSEhIRVSiGEYPPHEEyxfvpzY2Fh+/vln7r33Xm699VamTJlC//79ufPOO/noo4+Ij49n6dKlACW2iYiISOl5fcWqffv27mDgdDrJy8sr9OeCizGbOXXqFACnTp2iTp06pKens3fvXnr27AkUnM3Yu3cvaWlppKamFtsmIiIiZeP13QrZ2dk8//zzbNy4kbS0NAzDKLTMhbyy2WQy8eKLL/LAAw8QFBRETk4Or776KsnJydStWxeLxQKAxWKhTp06JCcnYxhGsW0RERFlrkVERKQ68zocxMfH8+mnn3LPPffQtGlT/Pz8yrUQh8PBK6+8wsKFC2nbti3fffcdDz/8MDNnzizX/RQlMrJ8L5VERdUs1+1dDKpbn6tbf0F99gWZgX74OQMA8A+w4nT6YQkux+lcCPJy+bLswxLoR1it4Ir7gMrA146xr/A6HGzdupUJEyZwzz33VEghP/30E8ePH6dt27YAtG3blsDAQAICAkhJScHpdGKxWHA6nRw/fpzo6GgMwyi2rTRSU7NxuQqfCSmLqKianDhxqly2dbGobn2ubv0F9dkXWK1m8vPs2HNsABg2By6bHVs5TluBXC+XL8s+/Cx2XOk5OByuCvucSsPXjnFl8DYMeT3mIDAwkLp165a5oPOpV68ex44dY//+/QD89ttvpKam0rhxY1q0aMHatWsBWLt2LS1atCAiIoLIyMhi20RERKRsvD5zMHjwYFasWEHHjh0xV8CTN6Kiopg6dSpjx47FZDIB8MwzzxAeHs7UqVMZP348CxcuJDQ0lISEBPd6JbWJiIhI6XkdDlJSUvjll1/o3r07HTp0oGZNz1MTJpOJxx9//IKK6d27N7179y40v0mTJrz//vtFrlNSm4iIiJSe1+EgMTERk8mEw+Hgq6++KtReHuFAREREqp7X4WDLli0VWYeIiIj4CL22Q0RERDx4feYA4PDhw7z++uvs3LnT/S6Dtm3bMnToUBo2bFhRNYqIiEgl8jocJCUlMXDgQAICAujUqRO1a9fm5MmTbNy4kTVr1rB06VJatWpVkbWKiIhIJfA6HCQkJNCyZUtee+01AgMD3fPz8vIYMWIECQkJeuGRiIjIJcDrMQc//PADw4YN8wgGUPBwpCFDhrBnz55yL05EREQqn9dnDgICAsjIyCiyLTMzk4CAgCLbREREADCZsFg8v5P6yqOUxZPX4aBTp07Mnj2bBg0aEBcX556/Y8cO5syZw1//+tcKKVBERC4N1uBQnAd3kp9V8EXTLyQMa6PrFBB8kNfhYPz48TzwwAPcd999REZGEhERQVpaGidPnuS6665j3LhxFVmniIhcAhzZGdizUt3T/lVYixTP63BQq1Yt3nnnHb744gt++OEHTpw4QVRUFNdccw0dO3asyBpFRESkEpU4IPH48eM8+OCDfPnll+55N998M6NHj2bq1KmMHj0awzB48MEHSU1NLWFLIiIicrEoMRwsXryYw4cPl3hmoGPHjvzxxx8sXry43IsTERGRyldiOPj000/p16+f+xXKRTGZTPTt25fNmzeXe3EiIiJS+UoMB0ePHqVp06bn3UiTJk04cuRIuRUlIiIiVafEcFCjRg2ys7PPu5Hc3Fxq1KhRbkWJiIhI1SkxHLRs2dKrVzVv3ryZli1blltRIiIiUnVKDAf9+/fn3//+Nx9++GGxy6xevZpVq1YxYMCAci9OREREKl+Jzzno1q0bAwcO5Mknn2TZsmX85S9/oX79+phMJo4ePcrWrVtJSkpi0KBB3HbbbZVVs4iIiFSg8z4Eafz48bRv35633nqLxYsXk5+fD4C/vz9t2rRh4cKFenSyiIjIJcSrJyR27tyZzp0743A43C9fCg8Px2r1+gGLIiIicpEo1W93q9VK7dq1K6oWERER8QH66i8i4qOs1j/HjJ/7qmORiqRwICLig6xWM8ahXdizMwGoERWDWflAKonCgYiIj7JnZ7pfb2wNCaviaqQ6UQ4VERERDwoHIiIi4kHhQERERDwoHIiIiIgHnwoHNpuNKVOm0LVrV3r16sXkyZMBOHDgAH379qVbt2707duX33//3b1OSW0iIiJSej4VDmbNmkVAQACJiYmsWbOGsWPHAjBlyhT69+9PYmIi/fv3Jz4+3r1OSW0iIiJSej4TDnJycli9ejVjx47FZDIBULt2bVJTU9m7dy89e/YEoGfPnuzdu5e0tLQS20RERKRsfOY5B4cPHyY8PJz58+ezbds2goODGTt2LDVq1KBu3bpYLBYALBYLderUITk5GcMwim2LiIjwet+RkSHl2peoqJrlur2LQXXrc3XrL6jPVSEz0A8/ZwAA/gFWnE4/LMEVOJ0LQV4uXx77tAT6EVYruCI+Oq9V9TH2VT4TDpxOJ4cPH6Zly5aMGzeO77//npEjRzJ37twK33dqajYul1Eu24qKqsmJE6fKZVsXi+rW5+rWX1Cfq4LVaiY/z449xwaAYXPgstmxVeC0Fcj1cvny2KefxY4rPQeHw1UBn+D5VfUxrgrehiGfCQfR0dFYrVb3JYJrrrmGWrVqUaNGDVJSUnA6nVgsFpxOJ8ePHyc6OhrDMIptExERkbLxmTEHERERdOjQga+++goouAshNTWVyy67jBYtWrB27VoA1q5dS4sWLYiIiCAyMrLYNhERESkbnzlzADBt2jQmTJhAQkICVquVmTNnEhoaytSpUxk/fjwLFy4kNDSUhIQE9zoltYmIiEjp+VQ4aNiwIW+//Xah+U2aNOH9998vcp2S2kRERKT0fOaygoiIiPgGhQMRERHxoHAgIiIiHhQORERExIPCgYiIiHhQOBAREREPCgciIiLiQeFAREREPCgciIiIiAefekKiiEh1ZrX++X3NYtF3N6k6CgciIj7AajVjHNqFPTsTgBpRMZiVD6SKKByIiPgIe3Ym9qxUAKwhYVVcjVRnyqUiIiLiQWcORESkaphMhcZWOByuKipGzqZwICIiVcIaHIrz4E7yszIA8AsJw9roOgUEH6BwICIiVcaRneEeZwHgX4W1yJ805kBEREQ8KByIiIiIB4UDERER8aBwICIiIh4UDkRERMSDwoGIiIh4UDgQERERDwoHIiIi4kHhQERERDwoHIiIiIgHhQMRERHxoHAgIiIiHnwyHMyfP59mzZqxb98+AHbv3k3v3r3p1q0bQ4YMITX1z5d0lNQmIiIipedz4eDHH39k9+7dxMTEAOByuXj88ceJj48nMTGRuLg4Zs+efd42ERFfZ7Wa3X8sFp/7cSzVmE/9a8zPz+epp55i6tSp7nlJSUkEBAQQFxcHQL9+/diwYcN520REfJnVasY4tIv8vZ+Rv/czjGO/YPapn8hSnfnUP8W5c+fSu3dvGjRo4J6XnJxM/fr13dMRERG4XC4yMjJKbBMR8XX27EzsWanYs1Jx5GVXdTkibtaqLuCMXbt2kZSUxGOPPVbp+46MDCnX7UVF1SzX7V0Mqlufq1t/QX2uCJmBfvg5AwDwD7DidPphCa7C6VwI8nL5iqjBEuhHWK3gcvyEz686/rv2hs+Eg+3bt/Pbb7/RpUsXAI4dO8bQoUO57777OHr0qHu5tLQ0zGYz4eHhREdHF9tWGqmp2bhcRrn0IyqqJidOnCqXbV0sqlufq1t/QX2uCFarmfw8O/YcGwCGzYHLZsdWhdNWINfL5SuiBj+LHVd6Dg6Hq/w+6BJU13/X3vCZywojRoxg69atbNmyhS1btlCvXj3eeOMNhg0bxunTp9mxYwcA7777Lt27dwegdevWxbaJiIhI2fjMmYPimM1mZs6cyZQpU7DZbMTExDBr1qzztomIiEjZ+Gw42LJli/vvbdq0Yc2aNUUuV1KbiIiIlJ7PXFYQERER36BwICIiIh4UDkRERMSDwoGIiIh48NkBiSIiUs2YTIXeMVFZzzwQTwoHIiLiE6zBoTgP7iQ/q+AR+H4hYVgbXaeAUAUUDkRExGc4sjOwZ6W6p/2rsJbqTOGgAlitf54WU+IVEZGLjcJBObJazWT/vI381JOATomJiMjFSeGgnDlzM3VKTERELmoKByIileTsS47njsoX8SUKByIilcBqNWMc2oU9OxOAGlExmJUPxEcpHIiIVBJ79p+XHa0hYVVcjUjxlFtFRETEg8KBiIiI5Loe3AAAESdJREFUeFA4EBEREQ8KByIiIuJB4UBEREQ8KByIiIiIB4UDERER8aBwICIiIh4UDkRERMSDwoGIiIh4UDgQERERD3q3goiI+CaTqdDbKx0OVxUVU70oHIiIVBC9ovnCWINDcR7cSX5WBgB+IWFYG12ngFAJFA5ERCqAXtFcPhzZGe43WQL4V2Et1YnCgYhIBdErmuVi5TM5Nj09neHDh9OtWzd69erFmDFjSEtLA2D37t307t2bbt26MWTIEFJT/0yRJbWJiIhI6flMODCZTAwbNozExETWrFlDw4YNmT17Ni6Xi8cff5z4+HgSExOJi4tj9uzZACW2iYiISNn4TDgIDw+nQ4cO7ulrr72Wo0ePkpSUREBAAHFxcQD069ePDRs2AJTYJiIiImXjM+HgbC6Xi3feeYfOnTuTnJxM/fr13W0RERG4XC4yMjJKbBMREZGy8ckBidOnTycoKIgBAwawadOmCt9fZGRIuW0r8wAEBQcAYAn0I6xWcLlt25dFRdWs6hIqVXXrL6jPZZEZ6Iefs+Dngf//b+9eY9qq/z+Av3vaAuVSGIVNLv7EuYtV/m5zLiyLI4IacIGRmSzgIg+UOZ9golEznLqpM2EMZFmUBB+wLbvpzKIiTDcxI85lZgKyjYp/XRjsp3J1wLiUi1B+D3AdLaUX1tPT075fz07POeXTQ885n/P9fvr9BqowOamGMsSLl423r1+OtpciRjGuqf74vXaG1yUHRUVFuH79OsrLyyEIAmJiYtDe3m5e39vbC0EQEBERYXedK27cGILJNHXHsatUAgQAxuExAIBa+Q9MfcM+/5vc6Ogw9PQMSh2Gx/jb5wX4medDpRIwPvIP/vn3ejA1NgHT2D8Y8+JlFW5fvxxtL0WM7r6m+uv32hle1a1QWloKg8GAsrIyBARM/5o1MTERo6OjqK+vBwB8+umnSE9Pd7iOiIiI5sdrWg6uXr2Kjz/+GAkJCcjJyQEAxMfHo6ysDHv37sWuXbswNjaGuLg4FBcXAwAEQZhzHREREc2P1yQHS5cuxW+//WZz3cMPP4yqqiqX1xEReRKHSyZf4TXJARGRnHG4ZPIlTA6IiNzEp4dLViigCgmHaUYtoFITCtPIgHQxkWiYHBARzZOsuxGsbvZKTSgwPDLn5sqgEFxqN+FGt9H8ms6kxIpwLcb6/hY7WvIwJgdERPMg924E65u9zqTEI9FhADqmN7BOHgI16LvZhZ7uvtvvEawFfKyBhKYxOSAimie5dyP09Q+ab/bKYC0QfXuddfKQEKyEoOKEyf6CyQEREUGhUEAICoZaqwMwu6VAFzN3l4PHKBSzum98fZA5qTA5ICIihGuD0dAuoPsvNQDnWgoUCgWUmtDbCYUmDIKgsKhjcGfBoipEi8nrP2N8YHr+HHVoOFT/WcUEQQRMDoiICADQf3PIpZaCcG0wGruAv9tvJRQhGBoW8Hf78PR7iFCwODHUb+7KAQB2dIiDyQERkT+wUWAIxZ0/1fffHLZIKG4ODFvWMcivFIPA5ICIyC+wwJBcweSAiMhPzPx1glcUGJLXYnJAROQkWQ96JIHZBYscUVEumBwQEc3BOhmYaG2Qz6BHItUYuMK6YJEjKsoHkwMiIisqlYCh/7+I8Ru3b2JB0XGYNMpn0CNvqTGYWbDIAkX5YHJARGTDzEQA8P5kwBbWGNB8MTkgIvIFXtCN4AhrEOSDyQERkQ/wlm4Ee1iDIB9MDoiIMLv4cErCWJziYNZEb+1GcGsNAudaEA2TAyLye7amX/Y6VslAQHgUGtqMuNHlvS0FYuNcC+JhckBEhNnTL3vbxdFWt8HNoTGvbykQG+daEIe3ff+JiGgOvvbrAxYoei8mB0Tkk2bWENjCpmfpsUDRezE5EBOLZYgkYauGwDQ2fLtvOiwCgQkPY3Jy+nzkUMjSYYGid2JyICIWyxA5z/pJ/07PE+saApPV6IYzz02vHwqZnMJrrvswORAZi2XIV7l6M7e3vfWTvjMXdXvdBs60BMw8N71y9EMZDGrkbu6oQeA11z2YHHgSm7xIxuxNQmTdTA84uPnbaNYfmfGkD4UCGjs3eFuTIM3sNpBFS4D1zd/qRiiHQY3cjTUI3oPJgQexyYvkzLoP33oSIovvtoObv6NmfetzxdbN3/rvW3cbeDvrm3/UlAqrFsXCNDk9/JJcBjVyN07U5B2YHHgYm7xICo66ABxV9gOz+/CtWTfTO+rTd9Ssb71ebjd/Z1j+NDEGjV1K81OzP7QUOMKfOkrHJ5KD1tZWFBQUoL+/HxERESgqKkJCQoLUYTnmhm4GdxdxkXdy9Wd5rnQBWK8HZj+pG+PucbmZ3uv79D3NiRqCmU/N/tJSYI91N8Os1hVHyYKNayw5xyeSg127dmHLli3IyspCZWUldu7cicOHD0sdlkOzuhkc9NsCrvf72noPl+NkAjLrGLjjSdxZjvrXHd3sHXUBWK+/tc3MJ3WTTue2z+M3ONyxW1gmTJatK7OThTAIgsJ8zAOjYjH530aM35ze3/rcGdJFIzD2/+xec/2V7JODGzduoLm5GQcPHgQAZGRkYPfu3ejt7UVkZKTE0Tlmryn2Ti/6tt7DVbMSkHlUkd9JFbut9a5y5mR3VPk+8xgY4+4BBm+69H+y7i93ddlR/7q9m70zTfY0D/MoKORwx3fOXrKQEByCoWEBf7cPT683KbEi3DTnuQOd7o4e0ObiCwmG7JODjo4OLFq0CEqlEgCgVCqxcOFCdHR0OJ0cCILCLbEIggIBC+9BSNACAECANhKm8Eiowhc6vzwxBigDzMuK4S4oxkYBTLc0KMIjoVAHTi8Hh0EIuHfO/ed6j6mJcUy6sDzzbyqDQqAMUEGlspyzLihIfftYDnTA9O/+QmAQArQxMJlsz3HnaHvr9a7G7+jvO/s3LI6BJhQqCC79n0wBAebt57M86/9s53vj1PZ2lm29pl4Qjakg7bzfU47LAibM57KtbYKiYtDaa8JQwBAAIBRa3PMfLVTa6RtPYEQUgm4OISRcO70cFIi7YqIQ+O9VNyoqApoQjVctB4cGQy1MObW9t8Q8PDJmcYwnpmBe1oRoEBAVAqgCbf4P1QuiMTVinPNcdvV6ZGsfdxgfn3DbezlLMTU15fUzk9pjMBiwfft2nDp1yvzahg0bUFxcjAcffFDCyIiIiORJ9pUaMTEx6OrqwuTkJABgcnIS3d3diImJkTgyIiIieZJ9cqDT6aDX61FdXQ0AqK6uhl6vl0W9ARERkTeSfbcCALS0tKCgoAADAwPQarUoKirC4sWLpQ6LiIhIlnwiOSAiIiL3kX23AhEREbkXkwMiIiKywOSAiIiILDA5ICIiIgtMDoiIiMgCkwM3qKysRGZmJh544AEcPXrUYt3IyAhefvllPPnkk0hPT0dtba1EUYqrtbUVubm5yMrKwlNPPYUPP/xQ6pBEd+TIEaSnpyMzMxNZWVlSh+MxFy9ehF6vn/Vd90Xvvvsu0tPTsXHjRuTk5KCpqUnqkETR2tqK7OxspKWlITs7G21tbVKHJKq+vj688MILSEtLQ2ZmJvLz89Hb2yt1WB7x0UcfYfny5fj999/tbsfkwA30ej327duHjIyMWesqKioQGhqKmpoalJeX46233sLw8LAEUYqruLgYaWlpqKysxMmTJ/H555/jypUrUoclmm+//RanT5/GyZMnUVVVhYqKCqlD8oihoSGUlJQgOTlZ6lA8Ijk5GVVVVfjqq6/w4osv4pVXXpE6JFHcmtn2zJkz2LJlC3bu3Cl1SKJSKBTYunUrzpw5g6qqKtx9990oKSmROizR/fLLL7h06RLi4uIcbsvkwA2WLVuGJUuWQLAx4f0333yD7OxsAEBCQgISExNx7tw5T4coOoVCgcHBQQDA6OgoFAqFT49SeeDAAeTn5yM0NBQAEBUVJXFEnrFnzx7k5eVhwYIFjjf2ASkpKVCrpycVW7lyJTo7O2EyyX/GvZluzWx76+EmIyMDzc3NPv0kHRERgaSkJPPyypUr0d7eLmFE4hsfH8d7772Hd955x6ntmRyIrL293SJLi4mJQWdnp4QRiWPHjh34+uuvsX79eqSmpiIvLw/x8fFShyWalpYWXL58GTk5OXj66afx2WefSR2S6L7//nsMDg4iPT1d6lAkcezYMTz22GM2HwLkzN7Mtv7AZDLhk08+QWpqqtShiGr//v3YuHGj09dl2U/Z7AmbNm2aM6u8cOGC+aTyZY6OwYkTJ5CVlYWtW7eiu7sbubm5SExMxIoVKzwcqXs4+ryTk5Po6OjA8ePH0dfXh2eeeQb33nsv1qxZ4+FI3cfeZz59+jQ++OADHDx40MNRicvZc/vUqVOoqqrCsWPHPBkeecDu3bsRHByMZ599VupQRNPY2AiDwYDXXnvN6X2YHDjhiy++mPe+sbGx+Ouvv8xN7B0dHRbNWXLh6BgcOXIE3333HQBg4cKFWLt2Lerq6mSbHDj6vLGxscjIyIAgCNDpdFi3bh2uXLki6+TA3meur69HT08PNm/eDGC6oKu2thb9/f3Iz8/3VIhu58y5XVNTg3379uHQoUM+2X00c2ZbpVLpVzPbFhUV4fr16ygvL/e5FqGZ6urq0NLSgscffxwA0NnZiby8PBQWFuLRRx+1uY/vHg0vkZ6ejhMnTgAA2tra0NTUhPXr10sclfvFx8fjhx9+ADBdtNbQ0IClS5dKHJV4MjIyzJ/XaDSioaEB999/v8RRieeRRx7Bjz/+iLNnz+Ls2bNIS0vDSy+9JOvEwBm1tbUoLCxERUWFz3aT+evMtqWlpTAYDCgrK0NAQIDU4Yhq27ZtOH/+vPn8veuuu1BRUTFnYgBw4iW3qK6uxt69ezEwMAC1Wg2NRoMDBw5gyZIlMBqNKCgowK+//gpBEPD666/jiSeekDpktzMYDHj//fdhNBoxMTGBDRs2+PSNY3R0FG+//Taam5sBAFlZWdi2bZvEUXlOQUEBEhMTfbopFgDWrl0LtVptcaM8dOiQzxVk+tvMtlevXkVGRgYSEhIQFBQEYPoBp6ysTOLIPCM1NRXl5eVYtmzZnNswOSAiIiIL7FYgIiIiC0wOiIiIyAKTAyIiIrLA5ICIiIgsMDkgIiIiC0wOiEgyg4ODeOONN7BmzRqsXr0ar776Kvr6+qQOi8jv8aeMRCSZvLw8tLa2Yvv27RAEASUlJdDpdDh+/LjUoRH5NQ6fTESSaGxsxPnz53H06FHzsNOLFi3C5s2bceHCBaxbt07iCIn8F7sViEhUdXV1yM3NxapVq7B69Wrk5uaiubkZ586dQ1RUlMV8FA899BDi4+N9clpzIjlhywERiebixYt4/vnnkZSUhD179kCj0eDnn39GV1cXrl27ZnOI3vvuuw/Xrl2TIFoiuoXJARGJprS0FMuXL0dFRQUUCgUAIDk5GQBw+PBhhIWFzdpHq9Xizz//9GicRGSJ3QpEJAqj0YjLly9j06ZN5sSAiOSByQERiWJgYABTU1OIjo62uV6r1WJwcNDmflqtVuzwiMgOJgdEJAqtVgtBENDT02Nz/eLFi9Ha2jrr9blqEYjIc5gcEJEogoODsWLFCnz55ZewNZxKcnIyenp6UF9fb36tqakJf/zxh7kugYikwUGQiEg0dXV1eO6555CUlITs7GxoNBpcunQJiYmJSElJQV5eHtra2syDIBUXF3MQJCIvwOSAiET1008/Yf/+/TAYDFCr1dDr9dixYwf0ej0GBgZQWFiImpoamEwmpKSk4M0330RkZKTUYRP5NSYHREREZIE1B0RERGSByQERERFZYHJAREREFpgcEBERkQUmB0RERGSByQERERFZYHJAREREFpgcEBERkQUmB0RERGThf2QTaE4xDbrYAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9fGYnfnnv7Ex"
      },
      "source": [
        "##Desafio 04 - Estudar sobre estatísticas retornadas no .describe"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lI_4ln8-_ltX"
      },
      "source": [
        "https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.describe.html\n",
        "\n",
        "Retorna valores estatísticos como média, desvio padrão, quartis, mínimo e máximo\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HhoU5czCwBad"
      },
      "source": [
        "##Desafio 05 - Refletir sobre a manipulação do tamanho das visualizações."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VeEH1RuR7DC3"
      },
      "source": [
        "\n",
        "##Desafio 06: Fazer outras análises com o boxplot e até com o histograma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 528
        },
        "id": "vT6xwVou3cSP",
        "outputId": "e740f724-0cce-4ca2-cc93-786c82cd470e"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.scatterplot(data=dados.query('composto in @cod_compostos'), y='g0', x='c0', hue='composto', hue_order=cod_compostos)\n",
        "plt.title('Relação de Expressões de g0 com c0', fontsize=25)\n",
        "plt.xlabel('g0', fontsize=15)\n",
        "plt.ylabel('c0', fontsize=15)\n",
        "plt.legend(title='Composto',loc='upper right', bbox_to_anchor=(1.22, 1))\n",
        "plt.show()"
      ],
      "execution_count": 148,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G0Ii2pNG7ENi"
      },
      "source": [
        "###Sobre\n",
        "cacb2b860 é o composto de controle tem um concentração na direita, junto da maioria dos compostos.\n",
        "\n",
        "87d7143666 tem um diferença de comportamento e apresenta um conjunto de expressões na parte superior esquerda e na parte central "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "4PsAXM0TA8-q",
        "outputId": "041a7d0e-d34f-41be-d7d3-9f3bb17ee715"
      },
      "source": [
        "plt.figure(figsize=(12, 10))\n",
        "sns.boxplot(data=dados.query('composto in @cod_compostos'), y='g0', x='composto', hue='composto')\n",
        "plt.title('Boxplot expressão do g0', fontsize=25)\n",
        "plt.ylabel('g0', fontsize=15)\n",
        "plt.legend(title='Composto',loc='upper right', bbox_to_anchor=(1.20, 1))\n",
        "plt.show()"
      ],
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "gpVn-BcoFJsf",
        "outputId": "58a91a87-cac9-481f-8188-c414f28b356f"
      },
      "source": [
        "plt.figure(figsize=(12, 10))\n",
        "sns.boxplot(data=dados.query('composto in @cod_compostos'), y='g600', x='composto', hue='composto')\n",
        "plt.title('Boxplot expressão do g600', fontsize=25)\n",
        "plt.ylabel('g600', fontsize=15)\n",
        "plt.legend(title='Composto',loc='upper right', bbox_to_anchor=(1.20, 1))\n",
        "plt.show()"
      ],
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "d2sovwtHFTtp",
        "outputId": "7fdef265-cd85-4c21-8140-f265434ac789"
      },
      "source": [
        "plt.figure(figsize=(12, 10))\n",
        "sns.boxplot(data=dados.query('composto in @cod_compostos'), y='c0', x='composto', hue='composto')\n",
        "plt.title('Boxplot expressão do c0', fontsize=25)\n",
        "plt.ylabel('c0', fontsize=15)\n",
        "plt.legend(title='Composto',loc='upper right', bbox_to_anchor=(1.20, 1))\n",
        "plt.show()"
      ],
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DAdCEA207GEo"
      },
      "source": [
        "##Desafio 07: Resumo do que você aprendeu com os dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yQQLpbMRB0Mc"
      },
      "source": [
        "###Resumo\n",
        "Os itens na coluna droga na verdade são compostos, isso porque drogas são compostos já conhecidos e validados, a maioria dos compostos possivelmente ainda estão sendo testados e ainda não foram validados.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "0-n8ydyCDuZU",
        "outputId": "8e456253-fa9a-41f2-f7ed-fb2fe0d11af1"
      },
      "source": [
        "plt.figure(figsize=(10, 5))\n",
        "sns.countplot(data=dados.query('composto in @cod_compostos'), x='composto', order=cod_compostos)\n",
        "plt.title('Top 5 Compostos', fontsize=20)\n",
        "plt.show"
      ],
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 152
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s-SVlN8ID3f-"
      },
      "source": [
        "O primeiro composto mais utilizado é de controle e o segundo apresentou maior expressão em relação aos demais, isso pode ser uma informação relevante já que ele está alterando consideravelmente o comportamento de celulas e genes. O Terceiro composto teve menor expressão e se mantem proximo do controle, então seu uso não afeta tanto o comportamento testado."
      ]
    }
  ]
}