Aula_02.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Cópia de Aula_02.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "UIsjjtsF74vf",
        "KbXSuyvbqdTE"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UIsjjtsF74vf"
      },
      "source": [
        "#Aula 01"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jw4JmFUsNPwq",
        "outputId": "68ad36fb-ace9-4b1a-ceef-b1eb911ae0ce"
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <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",
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              "      <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",
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              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
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              "      <th>c-65</th>\n",
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              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
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              "      <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",
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              "      <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/"
        },
        "id": "qBvT4sBNNPws",
        "outputId": "191eee90-5117-4bf7-ee7e-bee93fa155cd"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": null,
      "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": "fYdow_XdNPws",
        "outputId": "004721b0-18ac-4be6-8f57-3c4e17392923"
      },
      "source": [
        "dados.shape"
      ],
      "execution_count": null,
      "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": "zOmQRiUTNPwt",
        "outputId": "4959ecec-ccb6-4ee9-e834-1a73a30e0c57"
      },
      "source": [
        "dados['tratamento']"
      ],
      "execution_count": null,
      "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": "BrCJ2TzSNPwt",
        "outputId": "278b29f7-8c29-46e3-8632-576baf422c94"
      },
      "source": [
        "dados['tratamento'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['com_droga', 'com_controle'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d-eF7mPaNPwt",
        "outputId": "a120898e-64a1-4c88-e90f-a4671cf1681e"
      },
      "source": [
        "dados['tempo'].unique()"
      ],
      "execution_count": null,
      "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": "Zgm1XiOeNPwu",
        "outputId": "4f3be6a6-0211-462c-8fcb-582b415f3a79"
      },
      "source": [
        "dados['dose'].unique()"
      ],
      "execution_count": null,
      "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": "dByGDqcGNPwu",
        "outputId": "dac0bcdd-6287-484b-e48a-e94c5cc1a0ba"
      },
      "source": [
        "dados['droga'].unique()"
      ],
      "execution_count": null,
      "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": "hvdM3kYSNPwv",
        "outputId": "84125b39-7374-4c16-c824-d46ac9163d70"
      },
      "source": [
        "dados['g-0'].unique()"
      ],
      "execution_count": null,
      "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": "ZwjZj1F6NPwv",
        "outputId": "34f18381-4c4e-4161-c408-7fcc3d73ca41"
      },
      "source": [
        "dados['tratamento'].value_counts()"
      ],
      "execution_count": null,
      "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": "8buFt2cKNPwv",
        "outputId": "6c3d9db4-fdd6-4ef1-fd9d-2b3583c29086"
      },
      "source": [
        "dados['dose'].value_counts()"
      ],
      "execution_count": null,
      "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": "jmkevYGTNPww",
        "outputId": "ea96902b-1a0c-4c81-dcee-d506ce145c4a"
      },
      "source": [
        "dados['tratamento'].value_counts(normalize = True)"
      ],
      "execution_count": null,
      "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/"
        },
        "id": "owgn4RkDNPww",
        "outputId": "55dbd197-f603-4da2-8819-f3af7e66d064"
      },
      "source": [
        "dados['dose'].value_counts(normalize = True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "D1    0.510078\n",
              "D2    0.489922\n",
              "Name: dose, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OzMt7-vdNPwx",
        "outputId": "6aea3730-d3e4-497e-da36-ae8307660df9"
      },
      "source": [
        "dados['tratamento'].value_counts().plot.pie()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f942211f510>"
            ]
          },
          "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/"
        },
        "id": "wTkLLtMnNPwx",
        "outputId": "04fc20d8-a641-4aa0-ba47-3c7e682d97d8"
      },
      "source": [
        "dados['tempo'].value_counts().plot.pie()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9422067290>"
            ]
          },
          "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": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ArVvC7PRNPwx",
        "outputId": "b42f2543-a3b4-45e4-cba2-1903d7f75209"
      },
      "source": [
        "dados['tempo'].value_counts().plot.bar()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9421d2f210>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "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/"
        },
        "id": "ngAH-Ir6NPwy",
        "outputId": "cbf06da8-a8c6-4dfe-f0e2-1247e298521d"
      },
      "source": [
        "dados_filtrados = dados[dados['g-0'] > 0]\n",
        "dados_filtrados.head()"
      ],
      "execution_count": null,
      "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": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "87yE0HvTNY6u"
      },
      "source": [
        "#Aula 02"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xFXfW7vFvfK-"
      },
      "source": [
        "Olá!\n",
        "\n",
        "Seja bem vindo e bem vinda a aula 02!\n",
        "\n",
        "Na aula 01, nós começamos a explorar um conjunto de dados relacionados à industria farmacêutica. Para isso nós utilizamos uma biblioteca muito conhecida no mundo de DataScience: o Pandas.\n",
        "\n",
        "Nós utilizamos o Pandas para abrir o dataset, que estava no formato CSV, e para gerar um dataframe, uma tabela, para então começarmos a analisar e entender o que significava cada coluna. Com a ajuda da Vanessa, especialista na área, identificamos que temos colunas que nos remetem a dados que estão sob tratamento(droga) e com controle. Além disso, temos também diversas colunas que remetem aos genes.\n",
        "\n",
        "Começamos nossa análise olhando para cada coluna de forma separada e também geramos gráficos, para auxiliar nossa análise.\n",
        "\n",
        "E você? Como se saiu na resolução dos desafios?\n",
        "\n",
        "Agora, vamos mergulhar juntos na aula 02!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "hB3O-zZW9ZYw",
        "outputId": "0118b4b1-3a10-4b49-b2a8-78b92d7649bf"
      },
      "source": [
        "dados"
      ],
      "execution_count": null,
      "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": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGB4Kq8JvmZ5"
      },
      "source": [
        "A base de dados que usamos até o momento tem uma variável chamada ```composto```mas entendemos, com a ajuda da Vanessa, que essa não é a melhor nomenclatura para representa-la. \n",
        "Por isso, vamos usar a função ```map``` da biblioteca Pandas para renomear essa coluna.\n",
        "É importante destacar que passamos o parâmetro ```inplace = True```, esse parâmetro faz com que os dados sejam modificados no local e o dataframe será atualizado. \n",
        "Caso esse parâmetro não seja declarado, o default é ```inplace = False``` e o retorno será uma cópia do objeto e caso você queira, precisa salva-lo com um outro nome."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CFse2h0Vcrp4"
      },
      "source": [
        "mapa = {'droga': 'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lq5EDpC4w_rS"
      },
      "source": [
        "Aqui, estamos usando a função ```head``` para apresentar as 5 primeiras linhas da base de dados e assim, podemos conferir se a renomeação aconteceu da maneira que estavámos esperando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "id": "VX73K_tLcoQg",
        "outputId": "d73efd90-e4e3-4bf9-c6ad-716c322ff5af"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": null,
      "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",
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              "    }\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>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": "i7mgnrykiMNb"
      },
      "source": [
        "Queremos melhorar a visualização do nosso histograma de compostos e, como existem mais de 3.000 variações na nossa base de dados, decidimos elencar os 5 compostos que mais aparecem.\n",
        "Para isso, vamos usar a função ```value_counts``` (função presente na biblioteca Pandas e que conta a ocorrência dos diferentes valores) e, como queremos saber somente os 5 elementos mais frequentes, também declaramos o ```index[0:5]```. Essa parte final, faz com que o ```value_counts```se atenha à contagem dos maiores valores e apresente como resultado apenas o index do  intervalo [0, 5[, ou seja, o nome dos 5 maiores valores. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D5hK5mcVej_G"
      },
      "source": [
        "cod_compostos = dados['composto'].value_counts().index[0:5]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hrOGPnbP4cE_"
      },
      "source": [
        "Na célula acima, declaramos a variável ```cod_compostos``` e definimos a função que está atrelada à ela. \n",
        "E agora, executamos a nossa nova variável para verificar o resultado."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LgrRw3eSfLYu",
        "outputId": "56d9e5c2-9450-47c0-9ae4-5ff06d526296"
      },
      "source": [
        "cod_compostos"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1JANbNGx4wQO"
      },
      "source": [
        "Exitem algumas maneiras de filtrar uma base de dados e optamos em usar a função ```query``` do Pandas e, somente a título de curiosidade, essa função é bastante análoga ao SQL (linguagem de programação para bancos de dados).\n",
        "A estrutura dela é bastante simplificada, precisamos apenas definir o dataframe, chamar a função e passar como parâmetro a condição que deve ser \n",
        "filtrada no nosso conjunto de dados.\n",
        "\n",
        "Nesta parte do projeto, queremos realizar um filtro em nossos dados, selecionando apenas as linhas nas quais o composto esteja dentro da nossa lista ```cod_composto``` (lista que representa os 5 compostos mais testados no experimento) e vamos utilizar o método ```query``` para resolver este problema. \n",
        "\n",
        "Como parâmetro da função, passamos uma string contendo a lógica para realização da seleção dos dados. O que queremos é o seguinte: o ```query```precisa retornar para nós todas as linhas contendo os 5 compostos mais utilizados. Logo, a string necessária para isso é: ```composto in @cod_compostos```. \n",
        "\n",
        "Usamos ```composto``` porque essa é a coluna a ser verificada no dataframe e ```cod_compostos``` por ser a lista com os top 5 compostos, o detalhe aqui é que o ```@``` é necessário para informar o ```query``` que ```cod_composto``` é uma variável que já foi definida fora da função."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "_GlSwTMGfpFs",
        "outputId": "9a5e7628-dcd3-4357-8732-14424bb4bc58"
      },
      "source": [
        "dados.query('composto in @cod_compostos')"
      ],
      "execution_count": null,
      "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>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>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  ...    c-96    c-97    c-98    c-99\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": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p9FQo1EuFF8M"
      },
      "source": [
        "Agora que vimos que a nossa filtragem funcionou e que temos como retorno uma base de dados com 3.235 linhas, podemos usar a função ```query```como parâmetro para o ```countplot```, o nosso gráfico de barras.\n",
        "O ```countplot``` é um gráfico pré-programado da biblioteca ```Seaborn```e, por isso, precisaremos fazer a importação padrão da mesma (```import seaborn as sns```). Adicionalmente, aqui no Google Colaboratory, para que possamos enxergar o gráfico com os padrões de configuração da biblioteca, precisamos rodar ```sns.set()```.\n",
        "Além disso, para refinar a apresentação do gráfico, podemos utilizar algumas funcionalidades da biblioteca ```Matplotlib``` (fazendo, primeiramente, sua importação - ```import matplotlib.pyplt as plt```).\n",
        "Também estamos definindo o tamanho do gráfico através da função ```figure``` e seu parâmetro ```figsize=(x, y))``` e o título através do ```set_title('Título')```.\n",
        "Como comentado na aula, usualmente, armazenamos o nosso gráfico em uma variável ```ax``` e então, definimos as demais configurações (por exemplo, ```ax.set_title('Título')```.\n",
        "E, finalmente, para visualizar o gráfico de barras, usamos o ```plt.show()```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "IePUr98kdgED",
        "outputId": "bacf1d3c-7fc4-41f8-a9e6-56c69d8ed90a"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "sns.set()\n",
        "plt.figure(figsize=(8, 6))\n",
        "ax = sns.countplot(x = 'composto', data=dados.query('composto in @cod_compostos'))\n",
        "ax.set_title('Top 5 compostos')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "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": "bA_RUClHM6I8"
      },
      "source": [
        "Até o momento analisamos os dados de tempo, dose, compostos e afins. Entretanto, não analisamos os dados de expressões gênicas (G's) e viabilidade celular (C's). Será que podemos criar um gráfico de barras para esses dados?\n",
        "Vamos pensar que a nossa base de dados apresenta mais de 3.000 compostos. Mas quantos desses compostos aparecem na coluna ```g-0```? \n",
        "Para responder essa questão, vamos usar a função ```unique()``` do Pandas que conta os valores únicos presentes na coluna em questão. Como resposta padrão, o retorno será uma lista com arrays (os nomes dos compostos) mas, nosso objetivo é saber o tamanho dessa lista e, por isso, usamos o ```len```, pois assim, ele contará o tamanho desta lista de arrays."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DkQ2wH9Gj-w7",
        "outputId": "8dfdda55-305a-4244-fe66-1fdb2ac4b69d"
      },
      "source": [
        "len(dados['g-0'].unique())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14367"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wM4yn28tRflX"
      },
      "source": [
        "Como temos diversos compostos únicos dentro da coluna ```g-0```, não é viável que façamos o mesmo gráfico utilizado anteriormente. \n",
        "Por isso, precisamos traçar uma nova estratégia para visualizar os nossos dadose aqui, usaremos um histograma.\n",
        "O primeiro passo, é identificar qual o valor mínimo (```min()```) e o valor máximo (```max()```) para entender qual o intervalo númerico com o qual estamos trabalhando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mCC5DpK1kmiX",
        "outputId": "8197d06f-94a4-43cb-bb12-54e068fc6d1c"
      },
      "source": [
        "dados['g-0'].min()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-5.513"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qzH4Jl0OksuL",
        "outputId": "38bd8214-e411-447e-ab70-0278cc836b9d"
      },
      "source": [
        "dados['g-0'].max()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-Tp7M_wWUCU8"
      },
      "source": [
        "Depois que reconhecemos que o nosso intervalo vai de ~5,5 a 10,0, podemos partir para o histograma e a função que usaremos para plotar é do Pandas (```dataframe['variável'].hist()```).\n",
        "Assim que rodamos essa função, percebemos que a visualização destes dados ainda não está boa pois, a divisão padrão das barras do histograma, representam intervalos muito grandes que atrapalham o entendimento dos dados.\n",
        "Por isso, acresentamos um parâmetro dentro da função ```(bins = número de quebras)``` para melhor dividir e, consequentemente visualizar os dados.\n",
        "Quando definimos os bins em 100, podemos perceber que a forma se aproxima bastante de uma curva bastante conhecida: a curva normal."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "RnjRPpubk1z0",
        "outputId": "c8fff4e8-99c0-448d-d8b2-419a00483e6f"
      },
      "source": [
        "dados['g-0'].hist(bins = 100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9412a70b50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ILTZmvd2fczV"
      },
      "source": [
        "Aqui, estamos testando o mesmo histograma para outro gene, o ```g-19```. E queremos fazer uma comparação entre os gráficos e podemos fazer algumas considerações sobre ambos os gráficos.\n",
        "Percebemos, por exemplo, que a imagem seguem a mesma tendência de curva mas há um deslocamento para a direita."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "1_aedkvToYlB",
        "outputId": "f0bdbaf1-6951-41b7-cc71-1eac250c18d9"
      },
      "source": [
        "dados['g-19'].hist(bins = 100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f941292c1d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i8HZHcicEJ0F"
      },
      "source": [
        "Como concluimos que plotar os gráficos de todos os genes é inviável, vamos analisar resumidamente algumas estatísticas sobre eles. \n",
        "Para isso, vamos usar a função ```describe``` do Pandas que já calcula e descreve algumas estatísticas importantes para o entendimento dos dados (contagem, média, desvio padrão, mínimo, alguns quartis e máximo).\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "id": "Kv-2zPLBprgD",
        "outputId": "80e24760-8388-4c18-c61a-8f9192e0112f"
      },
      "source": [
        "dados.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\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>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>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</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>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           g-0  ...          c-98          c-99\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": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G4mCKUkUFYhb"
      },
      "source": [
        "Neste ponto, vamos separar as variáveis que queremos analisar da base de dados (exemplo: ```g-0``` e ```g-1```) através de uma lista de arrays.\n",
        "Entretanto, apesar desta ser uma ótima estratégia para a separação, temos 771 genes e escrevê-los um a um seria muito trabalhoso e podemos fazer de uma outra forma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "id": "OAkjbZdkqPlR",
        "outputId": "dff41bcc-91be-4747-a16e-4d178687f293"
      },
      "source": [
        "dados[['g-0', 'g-1']]"
      ],
      "execution_count": null,
      "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>g-0</th>\n",
              "      <th>g-1</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",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g-0     g-1\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\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.0636\n",
              "23810 -1.3260  0.3478\n",
              "23811  0.3942  0.3756\n",
              "23812  0.6660  0.2324\n",
              "23813 -0.8598  1.0240\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0LHi_9AUGFmS"
      },
      "source": [
        "Uma estratégia mais direta em que não precisaremos escrever a lista gene a gene, é o uso da função ```loc[]``` do Pandas.\n",
        "Como argumentos, passamos primeiramente o ```:```, os dois pontos faz com que o ```loc[]```retorne todos os elementos de uma determinada coluna, isso é importante quando não sabemos qual a quantidade de linhas de um dataframe. E, o segundo elemento, passamos as colunas que são de nosso interesse. No caso, queremos que a função nos retorne todos os elementos das colunas ```g-0```até ```g-771```.\n",
        "E, por fim, podemos declarar a nossa função de interesse a partir deste filtro realizado nos dados, o ```describe()```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "id": "dQX0KOhUqm66",
        "outputId": "365e30d4-93b9-40f3-ad98-9f086089d62f"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>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>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>g-39</th>\n",
              "      <th>...</th>\n",
              "      <th>g-732</th>\n",
              "      <th>g-733</th>\n",
              "      <th>g-734</th>\n",
              "      <th>g-735</th>\n",
              "      <th>g-736</th>\n",
              "      <th>g-737</th>\n",
              "      <th>g-738</th>\n",
              "      <th>g-739</th>\n",
              "      <th>g-740</th>\n",
              "      <th>g-741</th>\n",
              "      <th>g-742</th>\n",
              "      <th>g-743</th>\n",
              "      <th>g-744</th>\n",
              "      <th>g-745</th>\n",
              "      <th>g-746</th>\n",
              "      <th>g-747</th>\n",
              "      <th>g-748</th>\n",
              "      <th>g-749</th>\n",
              "      <th>g-750</th>\n",
              "      <th>g-751</th>\n",
              "      <th>g-752</th>\n",
              "      <th>g-753</th>\n",
              "      <th>g-754</th>\n",
              "      <th>g-755</th>\n",
              "      <th>g-756</th>\n",
              "      <th>g-757</th>\n",
              "      <th>g-758</th>\n",
              "      <th>g-759</th>\n",
              "      <th>g-760</th>\n",
              "      <th>g-761</th>\n",
              "      <th>g-762</th>\n",
              "      <th>g-763</th>\n",
              "      <th>g-764</th>\n",
              "      <th>g-765</th>\n",
              "      <th>g-766</th>\n",
              "      <th>g-767</th>\n",
              "      <th>g-768</th>\n",
              "      <th>g-769</th>\n",
              "      <th>g-770</th>\n",
              "      <th>g-771</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": [
              "                g-0           g-1  ...         g-770         g-771\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": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8mp610qzHQGY"
      },
      "source": [
        "Apesar do describe reunir as nossas estatísticas de interesse, é bastante complexo analisar o dataframe resposta. Para facilitar o nosso entendimento, vamos plotar histogramas que nos ajudaram na visualização das estatísticas de todas as colunas selecionadas.\n",
        "Olhando o dataframe original, anteriormente, fizemos o histograma de apenas uma coluna. Mas agora, nosso conjunto de dados de interesse é o ```describe()``` que fizemos a partir do ```loc[]``` e, deste ponto de vista, não queremos mais fazer o histograma coluna a coluna (genes), queremos que ele seja a partir das linhas (estatísticas). Por isso, vamos transpor as linhas e colunas (transformar as linhas em colunas e vice-versa).\n",
        "Para isso, vamos usar o ```.T[]``` no código anterior que produzimos para organizar o ```describe()```.\n",
        "Ou seja, vamos manter todo o código até o ```describe()``` e, ao final, acrescentaremos o ```.T[]```. Mas, ao rodarmos essa linha, percebemos que temos como devolutiva o mesmo dataframe mas transposto. E, como aqui, nosso interesse é produzir histogramas, acrescentamos como argumento do ```.T[]``` a estatística alvo (```.T['estatística']```) e, por último, acrescentamos o ```.hist(bins = número de quebras)``` para que o histograma seja observado.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "ij9QVxGArZsd",
        "outputId": "1120bf2f-9a57-4201-fe7d-b9e08d3cbf4b"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['mean'].hist(bins=30)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f94123eb510>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qbINMiTKKNqK"
      },
      "source": [
        "A seguir, reproduzimos o código acima apenas alterando o parâmetro estatístico a ser analisado (mínimo e máximo, por exemplo). \n",
        "E assim, podemos perceber as nuances de cada métrica."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "u31uRxYWr2PG",
        "outputId": "055feb16-4bf8-44ed-a202-f807fb248954"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['min'].hist(bins=30)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f94129582d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "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": 285
        },
        "id": "bYnsG81Sr8mc",
        "outputId": "1a64b44f-dbf9-4a7b-ef78-604c873403da"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['max'].hist(bins=30)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f941278ee10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g8FvuJapKhco"
      },
      "source": [
        "É muito interessante que a gente replique a análise desenvolvida para os ```genes (g)```, nos ```tipos celulares (c)```. \n",
        "Por isso, vamos copiar a linha de código que produz os histogramas mas aqui, vamos modificar o argumento ```loc[:,'g-0':'g-771'] -> loc[:,'c-0':'c-99']``` e a quantidade de bins ```hist(bins=100) -> hist(bins=50)```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "hu2jZ2snuJ09",
        "outputId": "6e359868-0f34-4af0-c385-5c007f9d9c26"
      },
      "source": [
        "dados.loc[:,'c-0':'c-99'].describe().T['mean'].hist(bins=50)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9412483890>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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cFFU4NLs9HDx4ULNnz1ZNTY1mzpypP/7xj+rr60txtdHZ7ePdd9/VnDlzVFVVpZkzZ+qll15KcaWx2e3j6NGjmjdvnsrKyjLqerKzoWE4HNaKFStUWVmpW265RVu2bLE3uWWYP//5z9Yf/vAHy7Isq7W11brpppusnp6eAcedOnXKqqiosD799FPLsizr7NmzVldXV0prjcVuHx9++KE1e/bsVJdnm90+zlu9erX1+9//PqN6stvDmTNnrN7eXsuyLCscDlsLFy60XnnllZTWGovdPvbt22cdOXLEsizLOnnypFVZWWnt3bs3pbXGYrePkydPWnv37rV27tyZUdfTvHnzrK1bt1qWZVlbt2615s2bN+CY119/3frtb39rhcNhKxQKWTfffLPV1tY25NzG3aG/+eabqq2tlSSNGzdOP/vZz7R79+4BxzU1NamsrEyTJ0+WJGVnZ2vkyJEprTUWu31kunj6+Pjjj3X48GHV1NSkssQh2e0hLy9POTk5kqRz587phx9+kNebOT9idvuYNGmSSktLJUk+n09XX321vvvuu5TWGovdPnw+n6ZMmaJhw6JvgpZq5zc0rKqqkvTfDQ0PHDigrq6unxz3xhtvaO7cufJ6vSoqKlJlZaXeeuutIefPnKvNJe3t7Ro9enT/14FAQEeOHBlw3D//+U9lZ2drwYIFqqmp0ZIlS/T999+nstSY7PYhSYcPH9bs2bM1d+5cvf7666kq0Ra7fZw+fVqrVq3SihUrUlmeLfGci6NHj6qmpkbl5eUaPny47rjjjlSVOaR4+jivpaVF+/bt0y9+8Ytkl2dbIn1kio6ODpWWliorK0uSlJWVpZKSEnV0dAw47rLLLuv/2m6PjrbPTYfZs2ervb190O+9//77tueJRCL68MMP9eqrr2rUqFFavXq1/vSnP2n16tVulRqTW31cf/312rVrl3w+n9ra2lRfX6/S0lLddNNNbpUak1t9PPXUU6qrq1NpaWnK/5MUt3qQpNLSUm3btk2nT5/WY489pnfeeUczZ850o8whudmHJHV2dur+++/XsmXL+u/YU8HtPi4mF1ygD3UHetlll+m7777r30+mo6ND5eXlA44LBAIqLy9XSUmJJKm6ulpLlixxv+Ao3OpjxIgR/f8eO3asKisr9fe//z1lge5WH5988ol2796tdevWqbe3V99//72qq6vV2NiYlLp/zK0efiw/P18zZsxQY2NjygLdzT5CoZDq6+s1f/583Xbbba7XGksyzkem+PGGhllZWVE3NAwEAmpvb9eNN94oaeAdezTGPXKZPn26/va3v0n676OIzz//XDfffPOA42677TZ99tln6unpkSTt3r1bEyZMSGmtsdjto7OzU9b/7d7w73//W3v27NG1116b0lpjsdtHY2OjduzYoR07dmjNmjUaP358SsLcDrs9tLW19X+qpa+vT++9957Gjx+f0lpjsdvHiRMnVF9fr7vvvjvjPjUl2e8jE9nd0HD69OnasmWLIpGIurq69O6772ratGlDzm/cXi6nT5/W4sWLdfDgQXm9Xj322GOqrKyUJK1du1YlJSW66667JElbt27Viy++KI/HozFjxqihoUGjRo1KZ/n97Pbx17/+VZs3b1Z2drbC4bB+/etfa/78+Wmu/v/Fcz7O++ijjxQMBvXaa6+lo+QB7Pawbdu2/uspEono5z//uRYtWqS8vLw0d/BfdvsIBoPatGmTrrzyyv7X/uY3v9Htt9+ertJ/wm4f4XBYv/rVr9TX16eenh4VFRVp7ty5euCBB9Jaf7QNDRcsWKAHH3xQN9xwg8LhsFauXKk9e/ZIkhYsWND/i+BYjAt0ALhYGffIBQAuVgQ6ABiCQAcAQxDoAGAIAh0ADEGgA4AhCHQAMASBDgCG+A+dnAYA/AActgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kUCr17j6xpu5"
      },
      "source": [
        "Um outro tipo de gráfico super interessante e útil é o boxplot. \n",
        "Para visualizá-lo, vamos usar a função ```boxplot```do Seaborn e, como argumentos dessa função vamos passar um ```x```, onde ```x = coluna que será plotada neste eixo``` e a base de dados ```data = conjunto de dados```.\n",
        "O boxplot apresenta uma caixa no meio onde podemos identificar a mediana (linha no meio da caixa que é o ponto onde metade dos dados estão na direita e a outra metade para a esquerda), os outliers (pontos acima ou abaixo do eixo principal do gráfico que representam valores discrepantes para mais ou para menos), a maior concentração dos dados (caixa principal que representa onde está a mior parte dos dados - primeiro quartil (25%) e terceiro quartil (75%)) e os máximos e mínimos desconsiderando os outliers (linhas laterais à caixa principal).\n",
        "O boxplot é uma importante ferramenta na visualização de dados porque em apenas um gráfico, podemos identificar várias métricas estatísticas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "R9LHaY0yv29K",
        "outputId": "2ae6eb41-f9b7-4708-c0b6-84dd3870e442"
      },
      "source": [
        "sns.boxplot(x='g-0' , data=dados)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9412354590>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4kvTdIE3d0W"
      },
      "source": [
        "Podemos também, além de definir apenas os dados que irão no eixo x, definimos os dados para o outro eixo, atribuindo um valor para o parâmetro ```y``` (```y = variável que vai ser plotada neste eixo```).\n",
        "Como podemos perceber, no boxplot que representa o ```tratamento = com_droga``` apresenta muitos outliers e isso gera uma discussão bastante interessante pois, do ponto de vista biológico a investigação desses pontos é importante mas, dependendo da área que estamos trabalhando, esse ponto pode apresentar outras soluções. \n",
        "Dito isso, é importante para um cientista de dados não só entender e manipular a base de dados mas também saber acerca do negócio que estamos tratando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "h87JI4a_yNa1",
        "outputId": "77976c76-65aa-4695-b7b2-1a5e843bead1"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.boxplot(y='g-0', x='tratamento' , data=dados)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f94121ae4d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        },
        {
          "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": "KbXSuyvbqdTE"
      },
      "source": [
        "#Desafios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X_Lg2XTu20ND"
      },
      "source": [
        "###Desafio 01: Investigar por que a classe tratamento é tão desbalanceada?\n",
        "\n",
        "###DEsafio 02: Plotar as 5 últimas linhas da tabela\n",
        "\n",
        "###Desafio 03: Proporção das classes tratamento.\n",
        "\n",
        "###Desafio 04: Quantas tipos de drogas foram investigados.\n",
        "\n",
        "###Desafio 05: Procurar na documentação o método query(pandas). \n",
        "\n",
        "###Desafio 06: Renomear as colunas tirando o hífen. \n",
        "\n",
        "###Desafio 07: Deixar os gráficos bonitões. (Matplotlib.pyplot)\n",
        "\n",
        "###Desafio 08: Resumo do que você aprendeu com os dados\n",
        "\n",
        "\n",
        "##Aula2\n",
        "\n",
        "###Desafio 01: Ordenar o gráfico countplot\n",
        "\n",
        "###Desafio 02: Melhorar a visualização alterando tamanho da fonte...\n",
        "\n",
        "###Desafio 03: Plotar os histogramas com seaborn\n",
        "\n",
        "###Desafio 04: Estudar sobre as estatíticas retornadas no .describe()\n",
        "\n",
        "###Desafio 05: Refletir sobre a manipulação do tamanho das visualizações. \n",
        "\n",
        "###Desafio 06: Fazer outras análises com o boxplot e até com o histograma. \n",
        "\n",
        "###Desafio 07: Resumo do que você aprendeu com os dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L2qI7Oe-5sf1"
      },
      "source": [
        "#Execução Aula2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pjxsTrg55w3V"
      },
      "source": [
        "###Desafio 01: Ordenar o gráfico countplot"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "ednixKa46NyV",
        "outputId": "0b192e22-a645-4170-eb40-5c9351f66d0e"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(10, 8))\n",
        "ax = sns.countplot(x = 'composto', data=dados.query('composto in @cod_compostos'), order = cod_compostos, palette = \"cubehelix\")\n",
        "ax.set_title('TOP 5 COMPOSTOS', fontsize = 18)\n",
        "ax.set_xlabel('Nome dos Compostos', fontsize = 16) \n",
        "ax.set_ylabel('Contagem dos Elementos', fontsize = 16) \n",
        "plt.show() "
      ],
      "execution_count": null,
      "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": "MiJ2NCFp51JQ"
      },
      "source": [
        "###Desafio 02: Melhorar a visualização alterando tamanho da fonte..."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uXriM1Ts52KD"
      },
      "source": [
        "###Desafio 03: Plotar os histogramas com seaborn"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "EQqJkL4QDVjM",
        "outputId": "5edf750a-32b5-4bdb-f2d4-bb6618779dc6"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# setando o tamanho do gráfico\n",
        "fig = plt.figure(figsize=(20,8)) \n",
        "\n",
        "#Definindo os parametros do primerio gráfico \n",
        "ax1 = fig.add_subplot(1, 2, 1)  # Adiciona a 1 linha, coluna 1\n",
        "ax1.set_title(\"Histograma - Expressão gênica do gene g-0\")\n",
        "ax1.set_xlabel(\" g-0\")\n",
        "ax1.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=dados['g-0'], bins=30, ax = ax1,  color = \"#FF4500\", kde=True)\n",
        "\n",
        "#Definindo os parametros do segundo gráfico \n",
        "ax2 = fig.add_subplot(1, 2, 2)  # Adiciona a 1 linha, coluna 2\n",
        "ax2.set_title(\"Histograma - Expressão gênica do gene g-19\")\n",
        "ax2.set_xlabel(\"g-19\")\n",
        "ax2.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=dados['g-19'], bins=30, ax = ax2, color = \"#FFA500\", kde=True)\n",
        "\n",
        "# Comando que retira informações extras/desnecessárias do gráfico \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "sjF5fzgJQdJM",
        "outputId": "ff287ac0-950e-48c6-b09e-e45629d62f8e"
      },
      "source": [
        "# Extraindo os dados através de consultas ao dataSet\n",
        "mean_g771 = dados.loc[:,'g-0':'g-771'].describe().T['mean']\n",
        "min_g771 = dados.loc[:,'g-0':'g-771'].describe().T['min']\n",
        "\n",
        "# setando o tamanho do gráfico\n",
        "fig = plt.figure(figsize=(20,8)) \n",
        "\n",
        "#Definindo os parametros do primerio gráfico \n",
        "ax1 = fig.add_subplot(1, 2, 1)  # Adiciona a 1 linha, coluna 1\n",
        "ax1.set_title(\"Histograma - Expressão gênica média dos genes g-0 à g-771\")\n",
        "ax1.set_xlabel(\" g-0\")\n",
        "ax1.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=mean_g771, bins=30, ax = ax1,  color = \"#8B008B\", kde=True)\n",
        "\n",
        "#Definindo os parametros do segundo gráfico \n",
        "ax2 = fig.add_subplot(1, 2, 2)  # Adiciona a 1 linha, coluna 2\n",
        "ax2.set_title(\"Histograma - Expressão gênica mínima dos genes g-0 à g-771\")\n",
        "ax2.set_xlabel(\"g-0 à g-771\")\n",
        "ax2.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=min_g771, bins=30, ax = ax2, color = \"#A020F0\", kde=True)\n",
        "\n",
        "\n",
        "# Comando que retira informações extras/desnecessárias do gráfico \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "JEk7JXtp6idM",
        "outputId": "364bfbd2-8719-43a7-fa78-3d3fc5a45d3c"
      },
      "source": [
        "#Extraindo os dados \n",
        "max_g771 = dados.loc[:,'g-0':'g-771'].describe().T['max']\n",
        "mean_c99 = dados.loc[:,'c-0':'c-99'].describe().T['mean']\n",
        "\n",
        "# setando o tamanho do gráfico\n",
        "fig = plt.figure(figsize=(20,8)) \n",
        "\n",
        "#Definindo os parametros do terceiro gráfico \n",
        "ax1 = fig.add_subplot(1, 2, 1)  # Adiciona a 1 linha, coluna 1\n",
        "ax1.set_title(\"Histograma - Expressão gênica máxima dos genes g-0 à g-771\")\n",
        "ax1.set_xlabel(\" g-0 à g-771\")\n",
        "ax1.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=max_g771, bins=30, ax = ax1,  color = \"#228B22\", kde=True)\n",
        "\n",
        "#Definindo os parametros do quarto gráfico \n",
        "ax2 = fig.add_subplot(1, 2, 2)  # Adiciona a 1 linha, coluna 2\n",
        "ax2.set_title(\"Histograma - Expressão gênica média dos genes c-0 à c-99\")\n",
        "ax2.set_xlabel(\"c-0 à c-99\")\n",
        "ax2.set_ylabel(\"Frequência\")\n",
        "sns.histplot(data=mean_c99, bins=50, ax = ax2, color = \"#00FF00\", kde=True)\n",
        "\n",
        "# Comando que retira informações extras/desnecessárias do gráfico \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s3J8zqQ_53Bo"
      },
      "source": [
        "###Desafio 04: Estudar sobre as estatíticas retornadas no .describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W5uw-8THe0Wi"
      },
      "source": [
        "#### A função .describe retorna os dados estatísticos de um dataframe, tais como: \n",
        "\n",
        "\n",
        "\n",
        "1. count:Número de registros/linhas do dataframe.\n",
        "2. unique: \n",
        "3. mean: A Média Aritmética de um conjunto de dados\n",
        "4. std: O desvio-padrão de um conjunto de dados.\n",
        "5. min: O valor mínimo. \n",
        "6. 25%: O primeiro quartil do conjunto de dados. \n",
        "7. 50%: O segundo quartil do conjunto de dados. \n",
        "8. 75%: O terceiro quartil do conjunto de dados. \n",
        "9. max:O valor máximo da série/coluna.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fl3Wyb4s53NZ"
      },
      "source": [
        "###Desafio 05: Refletir sobre a manipulação do tamanho das visualizações."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IZU4PcqH6QKq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "outputId": "5d378d13-2774-45d0-d447-68d5dac889c2"
      },
      "source": [
        "fig = plt.figure(figsize=(10,8)) \n",
        "sns.boxplot( x=dados[\"tempo\"], y=dados[\"c-99\"] )\n",
        "plt.show()"
      ],
      "execution_count": 83,
      "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": "170FMDpt53Wo"
      },
      "source": [
        "###Desafio 06: Fazer outras análises com o boxplot e até com o histograma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 502
        },
        "id": "lcBcv1Iq6Qts",
        "outputId": "a9e79276-ab8c-42b5-c20c-1d5d18422b25"
      },
      "source": [
        "fig = plt.figure(figsize=(10,8)) \n",
        "sns.boxplot( x=dados[\"g-99\"], y=dados[\"tratamento\"] )\n",
        "plt.show()"
      ],
      "execution_count": 77,
      "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": "r--ZtrqP53gL"
      },
      "source": [
        "###Desafio 07: Resumo do que você aprendeu com os dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "Nml9BnW26Ran",
        "outputId": "34772125-521e-4754-f812-79a5df53a57c"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(10,8))\n",
        "\n",
        "hist = sns.histplot(data=dados,bins=100, x='g-0', hue='dose', multiple=\"stack\")\n",
        "hist.set_title('Análise célular por tipo de dose', fontsize=18, color='b')\n",
        "hist.set_ylabel('Tipo de Dose', fontsize='14', color='b')\n",
        "hist.set_xlabel('Célula g0', fontsize='14', color='b')\n",
        "plt.show()"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9XTUn4P/vun117kk7V1zeyDOqPuR54ESBym12V62k1Obx15iZzdX55tKtV1U59Namwx493lNncktqne/29sVtXJsUfbEXk64Z2E1HzxTVCpNvbTosh1O1zrtrqoCLe/FKypp2mH73oRwdOV3o+tnpdOrtj9z7DwvxU2J8hLbvPasTWefdxr71YfXYEUkN9z+kX5Ssvj5677Njbn+neYVl2rLrtNtYs9mk64d216GThfr0P5l1rq+xQ5ThIf7q3zNc2/Zm6UzuN4Gu0u5Q6pava42/NqmbHE7prQ8PudV37s/W0TNFumZQN9eHgrZ6vwENYc8cUI9dh3KUV1immy7ev60uI6+M0esbDmrj9pO1roZsTKC/r67qG6WPvzwtP18f9Y0LV+65Ur3/+XHFRAXp0MnCRtdRl0cXb1L/nuHq3yNcEaH+KiguV/q/T8jiY9aYIbGSJH8/i35xz1AtfG2bfvL7D3XjNT0U3TlIF8oqdTqnRJ/tydJTP7ymwavrOocF6KHbk/Tiv77SY0s/UsqwOEWFB6qgqEz/3ntWj989RL1iO6lfj3BNv6m/Xt9wUI//4SONuipWEaH+OldcriOnCvXFgWy9s3hKg89p8qgE/eH1LzXnL5/phmHdVVJeqQ3/PqEu4YE658G5RiOvjNH/rtuv3/71c428Ilql5XZ9vOt0i19QEB8dqude/0I3Xduz+nYjR/L06VeZSuodqdGDY13j7p+UqN2Hc7Twte2aNDJB0Z2DtPdovrbuPqNBvSI17jt+u0hctxAF+Fm07tPj8vP1UVCArzoF++mqvvVfYSpJ8TGdNOcvn2rSqARFhPprW8ZZ7T6cqxuGddeA+G8u6Hno9iT99/JP9etln+iWUQkKD/HTjn3Z+vJgjsYO6d7glaySFBxo1b0TB+hvaXv1qxe2KiU5ThW2Kr3/+XFFdw6u9TVk992cqP3HCrRoxQ5d91Ws+vcMl8XHrNxzpdq5P1u9u4c1ejXrg1Oqe/7VC1t1y6gE161J6vqAMe7qHvpwxym9/dER5Zwr06BekcrKu6B1nx2rPk/u5m+uym6r9xvQEMIcUI+N26r3+oy4sv6b2vaMDlVsVJC27jqtB29LavJ5VrN+MEx/f3eftu89q492nlJMVLAemDxQkkmHTu5qVt+3j+2tLw7kKO2To7pQZldYsFX9e0bornF93a4+HDqgi577+Vi9temwPvritM5fqFBwgFXdIgN1+9jeio9p/Dy2SSMT1C0ySO98dERpnxxVpd2hiFB/XdU3yu2+bPdMGKA+cWFK23pUa7d8rXJblcKCreoRHaof335FA1uodv2wOBWcL9e7nx7TK2v3qltkoKbd2F8mk0kHPdgr+r2LV2Ru3HZSL6/JUHion0ZfFavx1/TQo4vrvzCjqXrFdtKMKYO04v39Wv/ZcQX6+2ryqATdNynR7fBul4hALf3ZGK1MP6DNX57ShbJKRXYK0NRxffX9Om7Q21R+vj761X3JWvH+fv01tfo2Ikm9IxsNc8MHdXPdNPh0TonCgq26+8Z+tb61o29cuJbMHK2V6w9o3afHXDcN/uEtA3X79Z6d13bH9X3k72dR6sdH9I/39isqLEB3XN9HQf6WWhcKBAX4atHM67Tm46/1ye4z2paRJR8fkyI7BWhgQqRuGl7/B64aA+Ij9MzDI/SP9/bprU2HFeTvq5FXRmvSyAQ9tvQjt7EWH7Pm/3iE3vjgkLbuPqPP92QqKKD6JsP3TUx0+07htny/AfUxOes68xcA0CT1fUuFEdT1rRAAjINz5gAAAAyMMAcAAGBghDkAAAAD45w5AAAAA2PPHAAAgIF1+FuTnDt3wfWFyXWJjAxWfn7Tv+z8csM8MAcSc1CDeWAOajAPzIHUNnNgNpsUHl73t6t0+DDncDgbDHM1Y8A8SMyBxBzUYB6YgxrMA3MgeXcOOMwKAABgYIQ5AAAAA+vwh1kBAIDxOJ1OnTuXK5utXJJ3D/Pm5JjlcDhaYE0mWa3+Cg+Pkslkanz4RYQ5AABgOCUlRTKZTOratbtMJu8eaLRYzLLbv3uYczodKizMU0lJkUJCwjx+HIdZAQCA4ZSVlSgkJMzrQa4lmUxmhYSEq6ysaVfGXj4zAAAAOgyHo0o+PpffAUYfH4scjqomPYYwBwAADKkp55UZRXOeE2EOAADAwAhzAACgQ1u48Ld6+eXl3m6j2QhzAAAABkaYAwAAMLDL7zIQAACABhw6dEC///0zOnXqlEaMGKVLrzlYu/YdrVz5D50/f15XXnmVZs9+Up07R8npdOqFF57Thg3rZbPZ1K1bN/32twvVq1cf2Ww2LV/+Z23atFGVlZUaM+Z6/exnT8jPz79Nng975gAAQIdRWVmp//7vWZowYZLef3+TbrhhnDZv3iRJ+uKLHXrppT9r/vzfKzV1vbp1i9a8eU9KkrZv/7d2796lVav+pfT0zZo///cKDa2+se/y5c/r1KkT+vvfX9cbb7yj3NxcvfbaK232nAhzAACgw9i7d4/sdru+//3pslgsuuGG8UpMHCRJ2rDhfd1yyxT17z9AVqtVDz/8mDIyvlJWVqYsFotKS0t14sRxOZ1OxccnqHPnznI6nVqz5l/62c9+qdDQTgoMDNL99z+gDz/c0GbPicOsAACgw8jLy1VUVBe3+7l17drt4rI89es3wFUPDAxUp05hys3N0bBhV+vOO7+v555bpOzsLI0Zk6LHHntcNptN5eXlmjHjXtfjnE5nC31Xq2cIcwAAoMOIjOys3NwcOZ1OV6DLyTmr2Nju6ty5s7Kzs1xjy8rKVFRUqKioLpKkqVOnaerUaTp3rkBPP/0bvf76Cs2Y8bD8/Py1YsWbrnFtjcOsAACgw0hKulI+Pj765z9Xy2636+OPN2nfvr2SpPHjJ2jdujQdPnxQNptNL720TAMHJik6Okb79+/V3r0Zstvt8vcPkNXqJ7PZLLPZrNtuu0PPP/+czp0rkCTl5uZo27bP2+w5sWcOAAB0GL6+vvrd75Zo0aIF+utf/6IRI0Zp7NgUSdLVVw/Xgw/+RE899SsVFxfriiuu1P/8z+8kSRcuXNALLzynzMwzslqtuuaaEbrnnvskST/96c/0yisv68c/fuDinrwo3X77XRo+fESbPCeT0+l0tsmW2qn8/BI5HPVPQVRUiHJzi9uwo/aJeejYc2BzOFVcWimr1SKbzS5JCgn0ldV8+X0voic68muhBnNQjXnw3hycPXtC3br1bPPt1sViMctub7lz5Op6bmazSZGRwXVvv8W2DOCyUBPcLuVwOvVa2l75+lpUWVkd5mZMSVJksNUbLQIALkGYA+CmuLRSr67NcKvdN2mgl7oBADSGCyAAAAAMjDAHAABgYIQ5AAAAAyPMAQAAGBhhDgAAwMC4mhUAAFwWQjsFyM/a8tGmwmbX+aKyBsfcddetslqt8vW1qry8TAkJvfSDH/yXrrjiKh0+fFDPPbdIhw4d1IgRo7RgweIW7Y8wBwAALgt+Votm/+njFl/vksfHejRuwYJF6tWrjyTp4483afbsx/WHP/xZXbt21WOPPaHDhw9q585tLd4fh1kBAABa2NixKbrttju1atUKde4cpUGDkmS1ts6N1glzAAAArWDgwCQdP3601bdDmAMAAGgV9X/3e0tqszB37tw5PfTQQ5owYYJuvfVWPfbYYyooKJAk7d69W1OmTNGECRP0ox/9SPn5+a7HNXcZAACAN+3fv08JCb1bfTttFuZMJpMefPBBpaenKy0tTXFxcVq6dKkcDodmz56tuXPnKj09XcnJyVq6dKkkNXsZAACAN23dullr1ryladPubfVttdnVrGFhYRo+fLjr58GDB2vVqlXKyMiQn5+fkpOTJUnTpk3TuHHj9OyzzzZ7GQAA6HgqbHaPrzxt6no9MWfOr123JomPT9CSJX/SoEFJysrK1KOPPqjy8nLZbBW6445JmjHjx5o8+fYW6c8rtyZxOBxatWqVUlJSlJWVpZiYGNeyiIgIORwOFRYWNntZWFiYx71ERgY3OiYqKsTj9V3OmIeOMQfFtiL5+rr/02A2m1y1mt+tVkuHmI/6dOTnXoM5qMY8eGcOcnLMsljcDzCWXqhQ6YWKVtnet7f1bWvWvFfvsri47kpLW+/xtsxmc5Pm1Cth7plnnlFgYKDuvfdebdy40RstuOTnl8jhqP8ExaioEOXmFrdhR+0T89Bx5sBms6uy0v1TqMPhVGWlXb6+Ftcym83eIeajLh3ltdAQ5qAa8+C9OXA4HLLbHW2+3bpYLOYW7cXhcNSaU7PZVO8OqDYPc4sWLdKJEyf04osvymw2Kzo6WpmZma7lBQUFMpvNCgsLa/YyAACAjqJNb03y3HPPKSMjQ8uWLXPdOC8pKUnl5eXauXOnJGn16tWaOHHid1oGAADQUbTZnrnDhw/rpZdeUnx8vKZNmyZJ6t69u5YtW6bFixdr3rx5qqioUGxsrJYsWSKp+phxc5YBaJzN4VRxaWWtusPZNvdFAgC0jDYLc3379tXBgwfrXDZ06FClpaW16DIADSsurdSrazNq1e+bNNAL3QAAmotvgAAAADAwr1zNCgAA0NIiOvnJpxW+zL7KZlNBUevc8qQlEOYAAMBlwcdq1Ym/PdXi6+35o4WSGg5zd911q6xWq+umwQkJvfSDH/yXrrjiKq1d+47efvsNOZ1OmUwmTZ9+vyZMmNRi/RHmAAAAWsCCBYvUq1cfSdLHH2/S7NmP6w9/+LO6d4/TCy+8pNDQTsrJydYDD0zXlVcOVnR0TCNr9AznzAEAALSwsWNTdNttd2rVqhUaOjRZoaGdJEldunRVZGRn5eTktNi2CHMAAACtYODAJB0/ftSt9uWXO1VSUqIBAwa02HYIcwAAAK3C/b6dx44d1YIF8zRv3kL5+fm32FYIcwAAAK1g//59SkjoLUk6deqkZs9+XLNnP6mrrhrcotshzAEAALSwrVs3a82atzRt2r06c+a0nnhipn7+81kaMWJUi2+Lq1kBAMBlocpmu3gbkZZfryfmzPm169Yk8fEJWrLkTxo0KElz5vxa588X6pVXXtIrr7wkSXrkkZkaPnxEi/RHmAMAAJeF6hv7eufmvm+9Vf/Xiy5YsKhVt81hVgAAAAMjzAEAABgYYQ4AABiS0+lsfJDBNOc5EeYAAIDhWCxWXbhw/rIKdE6nUxcunJfFYm3S47gAAkCzWCxm5Ze4X+EVEugrq9nkpY4AdCTh4VE6dy5XJSWF3m5FZrNZDoejRdZlsVgVHh7VtMe0yJYBdDil5XatWLfPrTZjSpIig5v2iRIAmsPHx6LOnaO93YYkKSoqRLm5xV7bPodZAQAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMEtbbmzRokVKT0/XmTNnlJaWpn79+un06dP66U9/6hpTXFyskpISbd++XZKUkpIiq9UqPz8/SdKsWbM0evRoSdLu3bs1d+5cVVRUKDY2VkuWLFFkZGRbPiUAAACvatMwN27cON1///36wQ9+4Kp1795dqamprp8XLlyoqqoqt8c9//zz6tevn1vN4XBo9uzZevbZZ5WcnKzly5dr6dKlevbZZ1v3SQAAALQjbXqYNTk5WdHR0fUut9lsSktL05133tnoujIyMuTn56fk5GRJ0rRp07R+/foW6xUAAMAI2nTPXGM2bdqkrl27atCgQW71WbNmyel0atiwYXriiScUGhqqrKwsxcTEuMZERETI4XCosLBQYWFhbd06AACAV7SrMPf222/X2iu3cuVKRUdHy2azaeHChZo/f76WLl3aYtuMjAxudExUVEiLbc/ImIfLaw6KbUXy9a39T4DZbKpVv7RW83td46xWy2U1Rw3pKM+zIcxBNeaBOZC8OwftJsxlZ2drx44dWrx4sVu95rCs1WrV9OnT9cgjj7jqmZmZrnEFBQUym81N3iuXn18ih8NZ7/KoqBDl5hY3aZ2XIzPWeB8AACAASURBVObh8psDm82uykp7rbrD4axVr6n5+lpcy+oaZ7PZL6s5qs/l9lpoDuagGvPAHEhtMwdms6neHVDt5tYk77zzjsaOHavw8HBXrbS0VMXF1ZPjdDq1bt06JSYmSpKSkpJUXl6unTt3SpJWr16tiRMntn3jAAAAXtSme+YWLFigDRs2KC8vTw888IDCwsL03nvvSaoOc0899ZTb+Pz8fM2cOVNVVVVyOBzq3bu35s2bJ0kym81avHix5s2b53ZrEgAAgI6kTcPcnDlzNGfOnDqXpaen16rFxcVpzZo19a5v6NChSktLa7H+AAAAjKbdnDMHoPXYHE4Vl1a61RzO+s8VBQAYB2EO6ACKSyv16toMt9p9kwZ6qRsAQEtqNxdAAAAAoOkIcwAAAAZGmAMAADAwwhwAAICBEeYAAAAMjDAHAABgYIQ5AAAAAyPMAQAAGBg3DQbQYiwWs/JLbG61kEBfWc0mL3UEAJc/whyAFlNabteKdfvcajOmJCky2OqljgDg8sdhVgAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwsDYNc4sWLVJKSor69++vQ4cOueopKSmaOHGibrvtNt12223aunWra9nu3bs1ZcoUTZgwQT/60Y+Un5/v0TIAAICOoE3D3Lhx47Ry5UrFxsbWWvb8888rNTVVqampGj16tCTJ4XBo9uzZmjt3rtLT05WcnKylS5c2ugwAAKCjaNMwl5ycrOjoaI/HZ2RkyM/PT8nJyZKkadOmaf369Y0uAwAA6Cgs3m6gxqxZs+R0OjVs2DA98cQTCg0NVVZWlmJiYlxjIiIi5HA4VFhY2OCysLAwj7cbGRnc6JioqJCmPZnLFPNg3DkothXJ19f97W42m2rV6qtfWqv5vbFxNaxWi2HnrSGX43NqKuagGvPAHEjenYN2EeZWrlyp6Oho2Ww2LVy4UPPnz2+zQ6b5+SVyOJz1Lo+KClFubnGb9NKeMQ/GmQObw6ni0kq3msPpVGWl3b3mqF2rr15T8/W1uJY1NM6tH5vdEPPWFEZ5LbQm5qAa88AcSG0zB2azqd4dUO0izNUcerVarZo+fboeeeQRVz0zM9M1rqCgQGazWWFhYQ0uAzqy4tJKvbo2w61236SBXuoGANDavH5rktLSUhUXV6dZp9OpdevWKTExUZKUlJSk8vJy7dy5U5K0evVqTZw4sdFlAAAAHUWb7plbsGCBNmzYoLy8PD3wwAMKCwvTiy++qJkzZ6qqqkoOh0O9e/fWvHnzJElms1mLFy/WvHnzVFFRodjYWC1ZsqTRZQAAAB1Fm4a5OXPmaM6cObXqa9asqfcxQ4cOVVpaWpOXAQAAdAReP8wKAACA5iPMAQAAGBhhDgAAwMAIcwAAAAZGmAMAADAwwhwAAICBEeYAAAAMjDAHAABgYIQ5AAAAAyPMAQAAGBhhDgAAwMAIcwAAAAZGmAMAADAwwhwAAICBEeYAAAAMzOLtBgBc3iwWs/JLbG61kEBfWc0mL3UEAJcXwhyAVlVabteKdfvcajOmJCky2OqljgDg8sJhVgAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADMzi6cDjWee1/vPjysq/oMfvHqKIUH99vidLXcID1Lt7WCu2CAAAgPp4tGfuy4M5euKPHyu/qExfHc6TrbJKknQ2/4JWbTjYqg0CAACgfh6FuZXr92vGlCQ99cBw+VpMrvoVvTvr8KlzrdYcAAAAGuZRmDtxtljJiV1r1YMDfVVcWtniTQEAAMAzHoW5kABf5ReV1ap/faZInTsFtHhTAAAA8IxHYW7s0O56LW2v8grLJJlU5XBqz9d5+lvaXt2QHNfKLQIAAKA+Hl3Neu/Nifrjql2asWCDnJIeXbxJcjo1Zmh3fX98v1ZuEQAAAPXxKMxZfMyade8w3XvzAH19ukgOp1O9YzspJiq4tfsDAABAAzy+z5wkdYsMUrfIIElSZl6JbJVVsvr6tEpjAAAAaJxHYe5/1+1TbFSwxl3dQ06nU3Nf+lz/OZKrQH9f/c9D16p/zwiPNrZo0SKlp6frzJkzSktLU79+/XTu3Dn96le/0smTJ2W1WtWzZ0/Nnz9fERHV6+zfv7/69esns7n69L7Fixerf//+kqRNmzZp8eLFqqqq0qBBg/Tss88qIIALMgAAQMfh0QUQm788rdgu1YdUvziQo6OZRVr6szFKSY7TP97b7/HGxo0bp5UrVyo2NtZVM5lMevDBB5Wenq60tDTFxcVp6dKlbo9bvXq1UlNTlZqa6gpyFy5c0NNPP60XX3xRGzduVFBQkF599VWPewEAALgceBTmCosrXLcg2bk/W9ddFaN+PcI1+boEHT1T6PHGkpOTFR0d7VYLCwvT8OHDXT8PHjxYmZmZja5ry5YtSkpKUnx8vCRp2rRpev/99z3uBQAA4HLg0WHWkECrcs6VqnNYgHYdzNF/3TJQklRV5ZSzBZtxOBxatWqVUlJS3Or33XefqqqqNGbMGM2cOVNWq1VZWVmKiYlxjYmJiVFWVlaTtxkZ2fhFHFFRIU1e7+WIeTDGHBTbiuTr6/7WNptNHtU8GVvzu6frrKtmtVoMMZcNMXr/LYE5qMY8MAeSd+fAozA38spoLV35hWI7B6u4tFJD+3eRJB3LLFJ056AWa+aZZ55RYGCg7r33Xldt8+bNio6OVklJiWbPnq1ly5bpF7/4RYttMz+/RA5H/ZE0KipEubnFLbY9o2IejDMHNptdlZV2t5rD4fSo1thYX1+La5mn66yrZrPZDTGX9THKa6E1MQfVmAfmQGqbOTCbTfXugPIozD04JUldwgOVW1imH04eKH+/6ocVnK/QzSMSWqTJRYsW6cSJE3rxxRddFztIch2WDQ4O1tSpU/Xaa6+56tu2bXONy8zMrHUIFwAA4HLnUZjz8THrjuv71KrfPrZ3izTx3HPPKSMjQy+//LKsVqurXlRUJD8/P/n7+8tutys9PV2JiYmSpNGjR+uZZ57R8ePHFR8fr9WrV+vmm29ukX4AAACMwuP7zJ0rLtd7nx7TqeximWRSXNcQ3TIqQWEhfh5vbMGCBdqwYYPy8vL0wAMPKCwsTH/84x/10ksvKT4+XtOmTZMkde/eXcuWLdPRo0c1d+5cmUwm2e12DRkyRI8//rik6j118+fP18MPPyyHw6HExEQ99dRTTXz6AAAAxuZRmNt3LF+//evnCgv2V//4cEnSx1+eVuqWrzX/xyM0IN6z+8zNmTNHc+bMqVU/ePBgneOHDBmitLS0etc3fvx4jR8/3qNtAwAAXI48CnN/S9urMUO669E7r5LZbJJUfVLz8rf/o1fXZmjJz8a0apMAAACom0f3mTt2pki3j+3tCnJS9VUVt43praNnilqtOQAAADTMozAXGOCr7ILSWvXsglIFBfi2eFMAAADwjEeHWccMjtXzb+zWA5MHus6P23+8QH9/d5/GDOneqg0CAACgfh6FuR9OHiSnpD+9sVsOh0NS9e1Kbh4Z7/o2CAAAALQ9j8Kcr8WsH99+he6flKiz+dWHW7tFBsrf6vGdTQAAANAKmpTGKmxVigj1V2iQtfHBAAAAaHWNhrnC4gr9/b29+nfGWZWVV0qSAvx9NfKKaN0/aWCTbhoMAACAltVgmCuvsOvXf96q4tJKpSTHKa5riOR06uTZYn2864z2HSvQH38x1vVdrQAAAGhbDaawtE+Oyu5watnsGxQe6u+2bOr4fpr9wla9++kx3ZXSt1WbBAAAQN0avM/cjn3Z+v64vrWCnCRFhPprakpfbd97ttWaAwAAQMMaDHOnc4o1MCGy3uUDEyJ0Oqe4xZsCAACAZxoMc6XldgUH1v8NDyGBVpWW21u8KQAAAHimwTDndDplNpnqH2CqHgMAAADvaPACCKek/17+iXzMdWe+qovfBgEAAADvaDDM3XNj/7bqAwAAAM3QcJibMKCt+gAAAEAzNHjOHAAAANo3whwAAICBEeYAAAAMjDAHAABgYIQ5AAAAA2vwatZL7dyfrfc+Pabsggv6n4dGKio8QOn/PqFuEYG6ql9Ua/YIAACAeni0Z27zF6e0eMUOxUQFKTu/1HWzYIfTqbc/OtyqDQKon83hVH6Jze2Xg29lAYAOxaM9c29/dESPTR2sMUO6a+O2E676gJ7hen39gVZrDkDDiksr9eraDLfafZMGeqkbAIA3eLRnLjPvggb0jKhV97daVFpe2eJNAQAAwDMehbnIUH+dyS2pVd97NE/dOge1eFMAAADwjEdhbsK1PfXymj3adyxfkpRbWKYPd5zUa+/u06QR8a3ZHwAAABrg0Tlzd6b01YXySj390ueqtFfpqb98Kl8fs+64vo9uua5Xa/cIwMuC/X300C19ZDab5HBUX2BR9R1ubGSxmJVfYnOrhQT6ymo2fZc2AaBD8vjWJPdPGqjvj++nU9nFcjqluK4hCvDz+OEADMxeUSa/Lcvla/VRpa1KklQx5tFmr6+03K4V6/a51WZMSVJksPU79QkAHVGT0pi/1aK+ceGt1QsAAACaqN4w9+TyT2Xy8IjHwkdGtVQ/AAAAaIJ6w1zPbiGuP1c5nfr4y9MKD/FTvx7Ve+YOnSzUueJyXT+0e+t3CQAAgDrVG+Ye/t6Vrj//NXWPUpLj9OPbr5Dpkt11f12zR9xrHri81FzscKlOASaVe6kfAEDDPLoe7aOdpzT5ul5uQU6SJo1K0Ec7T7VKYwC8o+Zih0t/BVcWeLstAEA9PApzTqd0POt8rXpdNQAAALQdj65mHX9ND73w5m5l5pa4vtbrwIkC/eujIxp/TY9WbRAAAAD18yjMPTB5kMKC/bR261GteH+/JCk8xF93pfTV7df3aeTRAAAAaC0ehTmz2aQ7U/rqzpS+Ki2vlCQF+vu2amMAAABoXJO/woEQBwAA0H58h29XBAAAgLe1WZhbtGiRUlJS1L9/fx06dMhVP3bsmO6++25NmDBBd999t44fP/6dlwEAAHQUbRbmxo0bp5UrVyo2NtatPm/ePE2fPl3p6emaPn265s6d+52XAQAAdBRtFuaSk5MVHR3tVsvPz9e+ffs0efJkSdLkyZO1b98+FRQUNHsZAABAR+LxBRDHMov0zuYjOpVdLJlM6tE1RN+7vo96Roc2e+NZWVnq2rWrfHx8JEk+Pj7q0qWLsrKy5HQ6m7UsIiKiST1ERgY3OiYqKqTRMR0B89D+5qDYViRfX/e3sdlsanbNVbf6uNdM39Rqfq/8Dtupq2a1Wtrd/DbESL22FuagGvPAHEjenQOPwty2jCz97h87NCghUsMGdJUk7TtWoMef26wnf3iNrhnUrVWbbE35+SVyOOr/htmoqBDl5ha3YUftE/PQPufAZrOrstLuVnM4nB7VAq1m/fCm+FrrDPGTym1V7o93OlVpq5Kv1UeVF5d5uh1Pazabvd3Nb33a42uhrTEH1ZgH5kBqmzkwm0317oDyKMz93/oD+v64fvrBxAHfqu/Xivf3NzvMRUdHKzs7W1VVVfLx8VFVVZVycnIUHR0tp9PZrGUAPFPzHazfFpxyj8q90A8AoHk8OmfuTG6JbkjuXqueMixOZ3JLmr3xyMhIJSYm6t1335Ukvfvuu0pMTFRERESzlwEAAHQkHu2Z6xTsp69PFSmms/vuvSOnCxUW4ufRhhYsWKANGzYoLy9PDzzwgMLCwvTee+/pt7/9rX7zm99o+fLlCg0N1aJFi1yPae4yAACAjsKjMDfh2p5a9tZuZeaXKDG+eu/X/mMFemfzEd1xg2ffzTpnzhzNmTOnVr1379765z//WedjmrsMAACgo/AozN09vp/8rRat+fiIVq4/IEmKCPXX9AkDdOvoXq3aIAAAAOrnUZgzmUy6fWxv3T62t0rLKyXxHa1ARxcW6KuHbnHfM1/FFwQCQJvz+D5zkpSVd0Gncqovve3RNUTdIoNapSkA7V+QLUdlW1a51SrGPOqlbgCg4/IozJ2/YNPzb+zS9n1nZTKZqotOp64e2E0/u3uIQoOsrdkjAAAA6uFRmHvhzV3Kyr+g3//0OvXvES5JOnjynP7y9lf68z9368kfXtOqTQIAAKBuHp3h8uXBXM2cOlgDEyLl42OWj49ZAxMi9dO7rtKXB3Nau0cAAADUw6Mw1ynYKr9vfVejJPlZfRQSyCFWAAAAb/EozE27sb9eSc1QflGZq5ZfVKZX12Zo2o39W605AAAANMyjc+bWbvlaOedKNWPBRkV28pck5ReVy+prVlGJTe9+ctQ19oVZN7ROpwAAAKjFozA36sqY1u4DAAAAzeBRmLtnwoDW7gMAAADNwP3aAQAADKzePXPff/I9/fXJ8eoU7KfvP/muJFO9K3nzd7e0Rm8AAABoRL1h7uE7rlCgv+Xin69ss4YAAADguXrD3Lire+hPq3fpoduTNO7qHm3ZEwAAADzU4Dlzm3aelK3S0Va9AAAAoIkaDHPOtuoCAAAAzdLorUlM9V/3AKAN2RxOFZdWutUcTj5yAUBH12iYu/+36xtdSerS21qkGQD1Ky6t1KtrM9xq900a6KVuAADtRaNh7qdTBysowLctegEAAEATNRrmrhnYTWEhfm3RC4BWEuzvo4du6eNW6xRgUrmX+gEAtJwGwxynywGXB3tFmfy2LHerBafcQ5gDgMtAg2GOU6sBtBWLxaz8EptbLSTQV1YzHysBoCENhrm1XNgAoI2Ultu1Yt0+t9qMKUmKDLZ6qSMAMIYG7zMHAACA9o0wBwAAYGCNXs0KAJ4KC/StddVsFR8ZAaBVEeYAtJggW47Ktqxyq1WMedRL3QBAx8BnZgAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGZvF2A5J0+vRp/fSnP3X9XFxcrJKSEm3fvl0pKSmyWq3y8/OTJM2aNUujR4+WJO3evVtz585VRUWFYmNjtWTJEkVGRnrlOQAAAHhDuwhz3bt3V2pqquvnhQsXqqqqyvXz888/r379+rk9xuFwaPbs2Xr22WeVnJys5cuXa+nSpXr22WfbrG8AAABva3eHWW02m9LS0nTnnXc2OC4jI0N+fn5KTk6WJE2bNk3r169vixYBAADajXaxZ+5SmzZtUteuXTVo0CBXbdasWXI6nRo2bJieeOIJhYaGKisrSzExMa4xERERcjgcKiwsVFhYmDdaBwAAaHPtLsy9/fbbbnvlVq5cqejoaNlsNi1cuFDz58/X0qVLW2x7kZHBjY6Jigppse0ZGfPg3TkothXJ19f9LWs2mzyvWX3ca6batfrql9Zqfm9sXI3KpvT4rZrVamm3r7v22ldbYg6qMQ/MgeTdOWhXYS47O1s7duzQ4sWLXbXo6GhJktVq1fTp0/XII4+46pmZma5xBQUFMpvNTd4rl59fIofDWe/yqKgQ5eYWN2mdlyPmwftzYLPZVVlpd6s5HE7Pa7Yq95qzdq2+ek3N1+rjWtbQuGb3+K2azWZvl687b78W2gPmoBrzwBxIbTMHZrOp3h1Q7eqcuXfeeUdjx45VeHi4JKm0tFTFxdWT43Q6tW7dOiUmJkqSkpKSVF5erp07d0qSVq9erYkTJ3qncQAAAC9pV3vm3nnnHT311FOun/Pz8zVz5kxVVVXJ4XCod+/emjdvniTJbDZr8eLFmjdvntutSQAAADqSdhXm0tPT3X6Oi4vTmjVr6h0/dOhQpaWltXZbgKEE+/vooVv6uNU6BZhU7qV+AACtq12FOQDfnb2iTH5blrvVglPu8VqYCwv0rRUuq9rVCR4AYGyEOQCtKsiWo7Itq9xqFWMe9VI3AHD54fMxAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGB8NyuAdstiMSu/xOZWCwn0ldVs8lJHAND+EOYAtFul5XatWLfPrTZjSpIig61e6ggA2h8OswIAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgRHmAAAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGRpgDAAAwMMIcAACAgVm83QCA2mwOp4pLK91qDqfTS90AANozwhzQDhWXVurVtRlutfsmDfRSNwCA9ozDrAAAAAZGmAMAADAwwhwAAICBEeYAAAAMjDAHAABgYIQ5AAAAA+PWJADaXFigrx66pY9brYqPlgDQLIQ5AG0uyJajsi2r3GoVYx71UjcAYGx8FgYAADAw9swBBhbs71PrcGWnAJPKvdQPAKDtEeYAA7NXlMlvy3K3WnDKPYQ5AOhA2k2YS0lJkdVqlZ+fnyRp1qxZGj16tHbv3q25c+eqoqJCsbGxWrJkiSIjIyWpwWUAAAAdQbs6Z+75559XamqqUlNTNXr0aDkcDs2ePVtz585Venq6kpOTtXTpUklqcBkAAEBH0a7C3LdlZGTIz89PycnJkqRp06Zp/fr1jS4DAADoKNrNYVap+tCq0+nUsGHD9MQTTygrK0sxMTGu5REREXI4HCosLGxwWVhYmMfbjIwMbnRMVFRI057IZYp5aLs5KLYVydfX/e1pNpvqrll93Gum5tc8GVvz+3fZTl21yvqe37dqVqulXbwW20MP3sYcVGMemAPJu3PQbsLcypUrFR0dLZvNpoULF2r+/Pm68cYbW327+fklcjic9S6PigpRbm5xq/fR3jEPbTsHNptdlZV2t5rD4ay7ZqtyrzmbX2tsrK/Vx7Xsu2ynzlp9z69WzaEDx/LdaiGBvrKaTbWeS2vh/cAc1GAemAOpbebAbDbVuwOq3YS56OhoSZLVatX06dP1yCOP6P7771dmZqZrTEFBgcxms8LCwhQdHV3vMgCXr9Jyu1as2+dWmzElSZHBVi91BADe1S7OmSstLVVxcXWidTqdWrdunRITE5WUlKTy8nLt3LlTkrR69WpNnDhRkhpcBgAA0FG0iz1z+fn5mjlzpqqqquRwONS7d2/NmzdPZrNZixcv1rx589xuPyKpwWUAAAAdRbsIc3FxcVqzZk2dy4YOHaq0tLQmLwMAAOgI2sVhVgAAADQPYQ4AAMDACHMAAAAG1i7OmQOAsEBfPXRLH7daFR83AaBRhDkA7UKQLUdlW1a51SrGPOqlbgDAOAhzgEEE+/vU2nPVKcCkci/1AwBoHwhzgEHYK8rkt2W5Wy045R7CHAB0cJyRAgAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGxtWsgJfZHE4Vl1a61RxOp5e6AQAYDWEO8LLi0kq9ujbDrXbfpIFe6gYAYDQcZgUAADAwwhwAAICBEeYAAAAMjDAHAABgYIQ5AAAAAyPMAQAAGBhhDgAAwMAIcwAAAAZGmAMAADAwwhwAAICBEeYAAAAMjDAHAABgYBZvNwAA35XFYlZ+ic2tFhLoK6vZ5KWOAKDtEOYAGF5puV0r1u1zq82YkqTIYKuXOgKAtsNhVgAAAAMjzAEAABgYYQ4AAMDAOGcOQLsVFuirh27p41ar4iMoALghzAFot4JsOSrbssqtVjHmUS91AwDtE59xAQAADIwwBwAAYGCEOQAAAAMjzAEAABgYYQ4AAMDACHMAAAAGxq1JAFyWLBaz8ktsbrWQQF9ZzSYvdQQArYMwB7RDwf4+tW6W2ynApHIv9WNEpeV2rVi3z602Y0qSIoOtXuoIAFpHuwhz586d069+9SudPHlSVqtVPXv21Pz58xUREaH+/furX79+MpurjwgvXrxY/fv3lyRt2rRJixcvVlVVlQYNGqRnn31WAQEB3nwqQIuwV5TJb8tyt1pwyj2EOQBALe3inDmTyaQHH3xQ6enpSktLU1xcnJYuXepavnr1aqWmpio1NdUV5C5cuKCnn35aL774ojZu3KigoCC9+uqr3noKgEdsDqfyS2xuvxxOp7fbAgAYWLsIc2FhYRo+fLjr58GDByszM7PBx2zZskVJSUmKj4+XJE2bNk3vv/9+a7YJfGfFpZV6dW2G2y97FWEOANB87eIw66UcDodWrVqllJQUV+2+++5TVVWVxowZo5kzZ8pqtSorK0sxMTGuMTExMcrKymry9iIjgxsdExUV0uT1Xo6Yh+8+B8W2Ivn6ur/tzGZT3TWrj3vN1Po1T8bW/N4W/dRVq6xvvjyoWa2WFnsd835gDmowD8yB5N05aHdh7plnnlFgYKDuvfdeSdLmzZsVHR2tkpISzZ49W8uWLdMvfvGLFttefn6JHI7694xERYUoN7e4xbZnVMxDy8yBzWZXZaXdreZwOOuu2arca87WrzU21tfq41rWFv3UWatvvjyo2Wz2Fnkd835gDmowD8yB1DZzYDab6t0B1S4Os9ZYtGiRTpw4oT/+8Y+uCx6io6MlScHBwZo6daq+/PJLV/3SQ7GZmZmusQAAAB1Fuwlzzz33nDIyMrRs2TJZrdW3DigqKlJ5efX1e3a7Xenp6UpMTJQkjR49Wnv27NHx48clVV8kcfPNN3uldwAAAG9pF4dZDx8+rJdeeknx8fGaNm2aJKl79+568MEHNXfuXJlMJtntdg0ZMkSPP/64pOo9dfPnz9fDDz8sh8OhxMREPfXUU958aVJ0/QAAEudJREFUGgDaQFigb6178FW1m4+lAND22kWY69u3rw4ePFjnsrS0tHof9//bu/ewqMp9D+DfuXGZGXBgDIFQEY8Samkb3Ka7vVGkJA8X61Rejp4b5a4eSzu750jtx8y0ozydSs/R0sr0pGadOmUKbdM2annJbZoQ4i1Ew81NB9ARhBlm1vmDAzmwwLGBeVkz38/z+DzystbMz3Fmre+873rflZqaitTU1N4qi4j6IIOtBte/3urS1vy7pwRVQ0QkHr/PEhERESkYwxwRERGRgjHMERERESkYwxwRERGRgjHMERERESlYn5jNSkTkDVqtGpZrNpe2EL0OAWqVoIqIiDzHMEckmDFI02ndtH7BKjQJqseXNTa1YNMXJS5t2ZmjYDYGCKqIiMhzDHNEgrU0X0fg12+6tBlTZjLMERGRW3jNHBEREZGCMcwRERERKRjDHBEREZGC8Zo5IvJrnOFKRErHMEdEimfS6zrNCHa4Oe7AGa5EpHQMc0SkeAZbDa5/vdWlrfl3TwmqhojIu3jNHBEREZGCsWeOqJfYnBKsjXaXNqckCaqGiIh8FcMcUS+xNtqxfnuxS9ucqSMEVUNERL6Kw6xERERECsYwR0RERKRgDHNERERECsZr5ojIJ3my9pzcQsIAFxMmor6JYY6IfJIna8/JLSQMAL9/6C5YW5yw2q7AZmsBwIBHROIxzBF5kTFI06m3qF+wCk2C6qFb0xbydDot7PbWMMe7RRCRaAxzRF7U0nwdgV+/6dJmTJnJMKdgvLcrEYnGMEdE5AHe25WIRGOYI+oBvNsDERGJwjBH1AN4twciIhKFYY6I/IYny5UQEfVVDHNE5DfklisJTpvPgEdEisYwR0R+zZP16LrS0zNc5a7J5IxZImrDMEdE1MPkZri2LTh8I3cDmdw1mZwxS0RtGOaIegkXCKYbuRvw9EFaNDa1uLRxZjQRdYdhjqiXcIFg5ZKbKAH0/LV0cgFvztQRsm0dcbFiImrDMEd0i7imnO+Tu44O+HmyhFqtgtPZ+n8uarJETw/leguv/yPqeQxzRLeIa8r5r7aQpwvQwG5zAPB8skRPcvduFHKBSm5491ZClrshTe7z4+5wM0MfkTyGOSIiDyhx7bquvpB4clsyd0OaXC+2u8PN7tbD3j/yNwxzRN248aRgtV2BzdbCIVVy4e7SJnITYrwR+uSurfP0PWxzSjj319bPQ3eP2VVI622c/Uv+hmGOqBs3nhR0Oi3s9hbZkxFnrtKN5HrrDOomNHWYEOONIVpPApVcEARag9vmnadht/8c5kRdauDJNazswSNfwTBH1AM4c5VuJNdb58n7oad79dx9PLkgCPSta0TdvYa1qx7KDTtOuLT1xiQShkbqbQxzRLeIvXDUU+R68PQGrVu9enK3IZPbVy6kyX358LSX0BvDyJ4MGbvbQ+npLOGuegp7MjQyHFJHDHPkl9w9GJqCVe0nqLblKOROrOyFo19CrgcvLGUmHG706rm7r1zok/vy4elEjp4OiHLh0G5vwXs7vH8NXncBr+1a2jZywc2T0NjVItIdn4PXBPo3xYe5srIy5OTkoL6+HiaTCbm5uYiNjRVdFvVx7s68MwXY209QbctRMLiRkrg75Cu3nVwQBNwPee72PLrbG+nuxBJ3eyg96U1sC2Nt19K28SRc9vQi0p4s78Lev64ZtHZo1K49wo7GqwDEvTaKD3OLFy/GrFmzkJWVhc8//xwvvvgi3n//fdFlUR8hd0ACAIPMQTxICzQ2u57iVAI/nESidbd48r+kDWlfOBmQ7+1zt/fQ3d5IOXI9gnKPJxcE5fb1ZPj6VvR0CO2q17Ine/+62rfjzGa5xwPkw6C7ax72pXUHHVYLLn210aUtcupjgKa/12tpo+gwZ7FYUFJSgg0bNgAA0tPTsXTpUtTW1iI8PNytx1C78UZwZ5uu2J0SGjq8AYMCNWhqdri0GYK00HV4Hrl95bbril7bArXK9duDSq2B5HR9bqekQmOL61uh474tDVdgDJA6becJuX+fOUSLYLVrm9WmwZXrrjXLvYZybcGBGgSoOoe5IFULVMc+cGkLn5AJHNvu0hYyIRN2owkAoNFp4AxwQKXVQfP/bW18pe1m27a9Bn2tbm+/Nv7+OhiddZAK82G3//x5u/Gz0lvPHR4SiCez4l3aQoJUaO7BfY3OOtg6HAfkjg1Byf+MJ7PiXe4GAgDB+oBOzyPXFqKzo/nQzY9Bbc9zs33ltpOtJVCN645mlzadRtvpOBlsCHZ7X6e9CQE3nC/kHg8AjIE6BHU4vl+zqdHcYVu5/eXa5B7P3fOF3LnG3fOjSqPt/LnQaD3KCu7o7vFVkqTcRbOKi4uxcOFC5Ofnt7dNnToVr776KkaOHCmwMiIiIiLv6OPrlBMRERFRdxQd5qKiolBdXQ2Ho7Vb1OFwoKamBlFRUYIrIyIiIvIORYc5s9mMhIQE5OXlAQDy8vKQkJDg9vVyREREREqn6GvmAKC0tBQ5OTm4evUqQkNDkZubi7i4ONFlEREREXmF4sMcERERkT9T9DArERERkb9jmCMiIiJSMIY5IiIiIgVjmCMiIiJSMIY5N23atAlpaWnIyMhAVlaW6HKEOnz4MBISErB582bRpXjdkiVLkJaWhszMTMyYMQM//PCD6JK8pqysDNOnT8eUKVMwffp0nD9/XnRJXlVXV4fHH38cU6ZMQUZGBubNm4fa2lrRZQmzevVqxMfH48yZM6JLEaK5uRmLFy/G/fffj4yMDCxatEh0SV63Z88eTJs2DVlZWcjMzMSuXbtEl+QVubm5SElJ6fT+F3qMlOimvvzyS2nWrFmS1WqVJEmSLl26JLgicaxWq/Twww9Lc+fOlTZt2iS6HK8rKCiQbDZb+98nT54suCLvmTNnjrRt2zZJkiRp27Zt0pw5cwRX5F11dXXSt99+2/7zihUrpOeff15gReIUFxdL2dnZ0qRJk6TTp0+LLkeIpUuXSq+88orkdDolSfK/84LT6ZSSkpLa//9PnjwpjRkzRnI4HIIr631HjhyRKioqOr3/RR4j2TPnhvfeew/z5s2D0WgEAPTv319wReKsWLEC2dnZCAsLE12KEJMmTYJOpwMAjBkzBlVVVXA6nYKr6n0WiwUlJSVIT08HAKSnp6OkpMSveqZMJhPGjRvX/vOYMWNQUVEhsCIxbDYbXn75Zbz00kuiSxGmoaEB27Ztw/z586FStd783B/PC2q1GlarFQBgtVoREREBtdr3Y0VSUlKnO02JPkZqvfIsCldaWorCwkKsWrUKNpsNM2bMwKOPPiq6LK/bt28frFYr0tLSsHfvXtHlCLdlyxZMnDjRLw5elZWVGDBgADQaDQBAo9EgIiIClZWVfnnHFafTia1btyIlJUV0KV63atUqZGZmIiYmRnQpwpSXl8NkMmH16tU4fPgwDAYD5s+fj6SkJNGleY1KpcLKlSvx1FNPQa/Xo6GhAW+//bbosoQRfYxkmAPw4IMPdvkN++DBg3A4HKisrMQHH3yAuro6zJw5E0OGDMHYsWO9XGnv6u512LlzJ1577TVs2LDBy1V5183eC20f1Pz8fOzYsQNbtmzxZnnURyxduhR6vR6zZ88WXYpXff/99yguLsZzzz0nuhShHA4HysvLMWLECCxcuBCFhYV44oknsHv37vYRHF/X0tKCdevW4c0330RiYiKOHj2KBQsWID8/HwaDQXR5fodhDsBnn33W7e+jo6ORnp4OtVoNs9mMCRMmoKioyOfCXHevw3fffYdLly7hkUceAdB6MfiePXtQX1+PefPmeavEXnez9wIA7N69G2+88QY2btzoN0MrUVFRqK6uhsPhgEajgcPhQE1NTaehBn+Qm5uLCxcuYO3atX7RK3ujI0eOoLS0FJMnTwYAVFVVITs7G8uXL8e9994ruDrviYqKglarbR9SGz16NMLCwlBWVoY777xTcHXecfLkSdTU1CAxMREAkJiYiODgYJSWluKuu+4SXJ33iT5G+teR6BdKT0/HN998AwBobGzE0aNHcccddwiuyruSkpJw6NAhFBQUoKCgAFOmTMHTTz/tU0HOHXv27MHy5cuxfv16vxpmMpvNSEhIQF5eHgAgLy8PCQkJfjfE+vrrr6O4uBhr1qxBQECA6HK8bu7cudi/f3/7cSAyMhLr16/3qyAHAOHh4Rg3bhwOHDgAoHUWo8ViweDBgwVX5j2RkZGoqqrCuXPnALRejmSxWDBo0CDBlYkh+hjJe7O6oampCYsWLUJJSQkAICsrC3PnzhVclVg5OTkYNWqU3w0z3XPPPdDpdC4f0I0bN/rFhJDS0lLk5OTg6tWrCA0NRW5uLuLi4kSX5TVnz55Feno6YmNjERQUBACIiYnBmjVrBFcmTkpKCtauXYvhw4eLLsXrysvL8cILL6C+vh5arRYLFixAcnKy6LK8avv27XjnnXfaJ4E888wzSE1NFVxV71u2bBl27dqFy5cvIywsDCaTCfn5+UKPkQxzRERERArGYVYiIiIiBWOYIyIiIlIwhjkiIiIiBWOYIyIiIlIwhjkiIiIiBWOYIyIC0Nhkx9Zdp1FT2yi6FCKiW8IwR0QE4D8/Oo6rDc2ICNe3t/3w42Vk/OFzXLnW7Pbj/JJ9iIg8wdt5EZFPqrM24eM/n8WRkipcrm9CqCEAsdGhyLg3DkkJA1y23f5NKQDg8Sxl3YrpfOVVrP20CGd/qoNRH4C08bGYcd/w9kVcicg/MMwRkc+prm3Ev/3XNwgO1OIfpo7AkOhQSBJQePYS1nxSiA2L7nfZPvO3Q5H526GCqv1lGpvsWLTuIEbGmfH6gmRcrLmGVR8dQ1CABg9O/BvR5RGRFzHMEZHPeet/CwEAbzybjODAnw9zAweEYGLiwPafG67bsSHvBL4troTN7kDc7SZkZ47EsIHyt2f76i8/Yd1nRfh4eXp72w8/XsYLbx3A5iVp6GcM7LTP1QYb1n1ahBNlFlgbbBhgNuChiUOR+uvu7+N5pKQK67cXo6buOoYPCsPUCbF4dfNRvPvH+zAgXI+9xy6i2ebAszN/hUCdBoOjQnGxxopt+0oxLXkoe+eI/AjDHBH5FGujDcdO12B2WoJLkGtjDNYBACRJwpJ3v4UhWIcXs++BUa9DwZFy/PGtg1ibMxnhoUE9Uo+9xYGhMf3wdynDoA/S4viZ1t7B20x6jB5+m+w+NXWN+PeNR/C3vxmCtPGDcaHSine3F7tsc+p8LUbGmRGo07S33R0fgc07T6G6thGRZkOP1E9EfR8nQBCRT6m83ABJAgYOMHa7XdGPl1FWcQU5/zgWwweFIbq/EbMfSECkWY8935X3WD3mfsF4aNIwxN3eD5FmA9LGx2L8ndHY9/3FLvf508HziDTr8VjWKMREhOA3o6PxwPhYl23qrM0wdegJNIW0/lxv5eQLIn/Cnjki8imSJLm1XenFejTbHZj94p9c2m0tTlRaGnqsHodTwicFZ7D/eAUsV67D3uJEi8OJUUP7d7nPxRorhg00ubTFD5If+iUiYpgjIp8SfZsRKhVQXn0N47uZnOqUAJMxECvm3dvpd/pAnew+ajXQMSq2OJzd1vPZ3h+xbW8pHp92J2KjQhEUqMH7X5z0eOmSsJBA1Hd4jLYeubYeOiLyDxxmJSKfEqIPwN3xEcg/cA7Xm1s6/f7adTsAYOjt/VB/rRlqlQrR/Y0uf7oKQ6GGQDTbHGhssre3lVVc6baekjILfj0yEilJAxF3ez9EmQ2ouHSt231iIkLw48V6l7Yz5XUuP98RG44T5yyw2R3tbcfPXEJ4aBAG3LBWHhH5PoY5IvI5Tz50FyQJePaNfdhf+FdcrLGivNqKLw6W4en/2AMAGDP8NiTEhmPZe4fx3clqVFkacOp8LbbsPIUT5yyyjxs/OAxBARr8d34JKi5fw4GiCuQfPN9tLbffZkTh2Us4cc6C8mor1n5ahOqb3GXigfGxqLzciPXbi3GxxoqDRRXYeaj1edrmqCbfHYPAAA1Wfvg9LlRexcGiCnxScJYzWYn8EIdZicjnRJoNWPmvE/HxV2ewMa8ElitNCDXoEBvdD/MeGQ0AUKlUWPzYPdi88xRWf3wcV661TihIGGJGStJA2ccN0QfgD3+fiA07TuCrv/yEkXFmzE67A69/cKzLWqanDkd1bSOWvHsIAToNJicNQvKvYlBebe1yn4hwPZ7/p7FY/3kx8g+UYdhAE2beH49VHx2HTtf6HdwQrMPS30/A2k+L8OzKfTAG6/Bg8lBMS1bWenlE5DmV5O7VwkREJMz2r0ux5ctT+HDZVPa8EZEL9swREfVB+fvPYdigMIQaAnD6Qh0+3H0Gk8cOYpAjok4Y5oiI+qAKSwP+589nYW20oX+/YDwwIRYz7osXXRYR9UEcZiUiIiJSMM5mJSIiIlIwhjkiIiIiBWOYIyIiIlIwhjkiIiIiBWOYIyIiIlKw/wN7bXlYIt995AAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}