Aula_03.ipynb

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  "metadata": {
    "colab": {
      "name": "Aula_03.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOxa77I4tYs03DQs7gyqul0",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Gabrielchollet/imersao-dados-alura/blob/main/Aula_03.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NwEQlMMRGFwA"
      },
      "source": [
        "#Olá novamente Dev\n",
        "\n",
        "Nessa aula falaremos sobre **correlação**, **causalidade** e entender melhor as diversas relações entre as variáveis da nossa base de dados.\n",
        "\n",
        "Além disso veremos a interpenetração entre as diferentes áreas do conhecimento que a Ciência de Dados permite.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "waEzfZ8qH6DR"
      },
      "source": [
        "#Vamos importar a nossa base de dados novamente\n",
        "\n",
        "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"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UYxOWsiPH_b9"
      },
      "source": [
        "# Importar o seaborn \n",
        "import seaborn as sns\n",
        "\n",
        "#Importar a biblioteca matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Aplicar o tema padrão\n",
        "sns.set_theme()"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2vkVjCN0IH3o"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "Js961iVHIIT3",
        "outputId": "ea1a6159-0345-4a32-8fc8-115b2f5661bf"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <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",
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              "      <td>1.2390</td>\n",
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              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
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              "      <td>0.1093</td>\n",
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              "      <td>-0.7250</td>\n",
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              "      <td>0.6103</td>\n",
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              "      <td>-0.2187</td>\n",
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              "      <th>3</th>\n",
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              "      <td>48</td>\n",
              "      <td>D1</td>\n",
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              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
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              "      <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": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7zbHpDrAIMr3"
      },
      "source": [
        "Vamos começar relacionando os nossos dados de tratamento, qual foi o tipo de tratamento? Qual foi o tempo? Qual foi a dosagem?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9BShf2OoNJem"
      },
      "source": [
        "Vamos criar uma tabela de frequência com esses dados e para isso usaremos a função `.crosstab` da biblioteca *pandas*.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "m7Cu2NEIN3C-",
        "outputId": "3d4ceb5a-bc28-4f25-95be-fc068e62632b"
      },
      "source": [
        "pd.crosstab(dados['dose'], dados['tempo'])"
      ],
      "execution_count": 4,
      "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>tempo</th>\n",
              "      <th>24</th>\n",
              "      <th>48</th>\n",
              "      <th>72</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>D1</th>\n",
              "      <td>3886</td>\n",
              "      <td>4354</td>\n",
              "      <td>3907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>3886</td>\n",
              "      <td>3896</td>\n",
              "      <td>3885</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tempo    24    48    72\n",
              "dose                   \n",
              "D1     3886  4354  3907\n",
              "D2     3886  3896  3885"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4RsTnAO_7cBr"
      },
      "source": [
        "Para uma anánise mais clara, é interressante que separemos esses dadeos entre amostras que receberam o composto e as que não receberam.\n",
        "\n",
        "Para isso adicionaremos as informações de tratamento com `dados['tratamento']` assim como haviamos feito anteriormente."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "lriJCA287zWp",
        "outputId": "a5b23dde-28bf-48e9-a3a4-f529fcf2500a"
      },
      "source": [
        "#coluna => 'tratamento'\n",
        "#linhas => 'dose' & 'tempo'\n",
        "\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'])"
      ],
      "execution_count": 7,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>301</td>\n",
              "      <td>3585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>343</td>\n",
              "      <td>4011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>307</td>\n",
              "      <td>3600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>305</td>\n",
              "      <td>3581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>305</td>\n",
              "      <td>3591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>305</td>\n",
              "      <td>3580</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24              301       3585\n",
              "     48              343       4011\n",
              "     72              307       3600\n",
              "D2   24              305       3581\n",
              "     48              305       3591\n",
              "     72              305       3580"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WNKu5tyF8KQ_"
      },
      "source": [
        "Podemos observar uma certa proporcionalidade e para podermos observar mais claramente introduziremos nessa tabela as respectivas proporcionalidas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "5dwmwRRO96ep",
        "outputId": "55438d63-3a5f-40f8-f19c-72548a00652b"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize = True)"
      ],
      "execution_count": 8,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012640</td>\n",
              "      <td>0.150542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.014403</td>\n",
              "      <td>0.168430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012892</td>\n",
              "      <td>0.151172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150374</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150332</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.012640   0.150542\n",
              "     48         0.014403   0.168430\n",
              "     72         0.012892   0.151172\n",
              "D2   24         0.012808   0.150374\n",
              "     48         0.012808   0.150794\n",
              "     72         0.012808   0.150332"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "yYaQCjFW-SBf",
        "outputId": "ba0124f5-31e5-4a5b-e82e-cc152999ba58"
      },
      "source": [
        "#Na tabela acima a normalização foi feita em relação aos número total \n",
        "\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize = 'index')"
      ],
      "execution_count": 11,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.077458</td>\n",
              "      <td>0.922542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078778</td>\n",
              "      <td>0.921222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078577</td>\n",
              "      <td>0.921423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.078487</td>\n",
              "      <td>0.921513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078285</td>\n",
              "      <td>0.921715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078507</td>\n",
              "      <td>0.921493</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.077458   0.922542\n",
              "     48         0.078778   0.921222\n",
              "     72         0.078577   0.921423\n",
              "D2   24         0.078487   0.921513\n",
              "     48         0.078285   0.921715\n",
              "     72         0.078507   0.921493"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qrqtef1W_jNt"
      },
      "source": [
        "Não apensa conseguimos calcular a frequência, mas também conseguimos associar uma outra variável nessa tabela.\n",
        "\n",
        "Por exemplo: vamos ver a diferença em um determindado gene em específico. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "y_jYaikoBDw3",
        "outputId": "ebbc0acf-7b2d-4364-ea5d-3b1f496c71b3"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values = dados['g-0'], aggfunc = 'mean')"
      ],
      "execution_count": 14,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>-0.251760</td>\n",
              "      <td>0.367996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-0.122773</td>\n",
              "      <td>0.412469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>-0.295271</td>\n",
              "      <td>0.286250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.010754</td>\n",
              "      <td>0.115253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.013174</td>\n",
              "      <td>0.214480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.070250</td>\n",
              "      <td>0.253439</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24        -0.251760   0.367996\n",
              "     48        -0.122773   0.412469\n",
              "     72        -0.295271   0.286250\n",
              "D2   24         0.010754   0.115253\n",
              "     48         0.013174   0.214480\n",
              "     72         0.070250   0.253439"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Apo63S8XCNB6"
      },
      "source": [
        "Como podemos analisar a relação entre diferentes genes?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "RnzHBE9HD4nn",
        "outputId": "343d1da9-6e66-4bb2-ab05-906f6671064f"
      },
      "source": [
        "#Para facilitar a visualização vamos fazer um slice da base de dados apenas com a coluna 'g-0' e 'g-3'\n",
        "\n",
        "dados[['g-0', 'g-8']]"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-8</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>-0.4047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.0065</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.1321</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.8789</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>-0.4726</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.5112</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>-0.0340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.4299</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>3.0790</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g-0     g-8\n",
              "0      1.0620  0.5548\n",
              "1      0.0743 -0.4047\n",
              "2      0.6280  0.0065\n",
              "3     -0.5138 -0.1321\n",
              "4     -0.3254 -0.8789\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.4726\n",
              "23810 -1.3260  0.5112\n",
              "23811  0.3942 -0.0340\n",
              "23812  0.6660  0.4299\n",
              "23813 -0.8598  3.0790\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "MS4WTBQkCNi1",
        "outputId": "46c696af-9c89-461a-e893-822059079b0e"
      },
      "source": [
        "sns.scatterplot(x = 'g-0', y = 'g-8', data=dados)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fec49e75b10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        },
        {
          "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": "g52v8ibuE0HK"
      },
      "source": [
        "Podemos utilizar o método `lmplot` para realizar uma regressão linear para facilitar a visualização do comportamento dos dados."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "hsjd8KpoFoAs",
        "outputId": "a7c95210-3cef-49e1-d36b-6911f5d5bc71"
      },
      "source": [
        "sns.lmplot(x='g-0', y='g-8', data=dados, line_kws={'color': 'red'})"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fec49e17c50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c349cWClGXUI"
      },
      "source": [
        "É importante relembrar que estamos olhando a relação entre a expressividade dos genes 0 e 8 para todas aas informações contidas no banco de dados utilizado.\n",
        "\n",
        "Então é interessante também observar essa relação apenas para alguns parâmetros do banco de dados para e assim tirarmos conclusões mais consistentes."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 975
        },
        "id": "BYFc3eaMHP8R",
        "outputId": "8a0d902a-d337-47c6-fe4c-b90055b1d244"
      },
      "source": [
        "sns.lmplot(x='g-0', y='g-8', data=dados, line_kws={'color': 'red'}, col = 'tratamento', row='tempo')"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fec49ab2b90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x1080 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pCnX7QnWIP4o"
      },
      "source": [
        "É interessante observar que com camadas cada vez mais altas de visualização somos capazes de concluir cada vez mais coisas."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5HhczXpkJrX5"
      },
      "source": [
        "Assim como a média e outras estatísticas vistas até agora, existe uma que pode facilitar a nossa análise e resumir isso em um número, a **correlação**.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "d0BWkvVGKFId",
        "outputId": "90f10e57-8059-486a-fc50-8c395c8fccc1"
      },
      "source": [
        "dados.loc[:, 'g-0':'g-771'].corr()"
      ],
      "execution_count": 33,
      "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",
              "      <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>g-0</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.086032</td>\n",
              "      <td>0.176188</td>\n",
              "      <td>0.011266</td>\n",
              "      <td>0.403153</td>\n",
              "      <td>-0.165478</td>\n",
              "      <td>0.238348</td>\n",
              "      <td>-0.374451</td>\n",
              "      <td>-0.604212</td>\n",
              "      <td>-0.428779</td>\n",
              "      <td>-0.547606</td>\n",
              "      <td>0.219762</td>\n",
              "      <td>-0.199453</td>\n",
              "      <td>0.472223</td>\n",
              "      <td>-0.346179</td>\n",
              "      <td>-0.201323</td>\n",
              "      <td>-0.513026</td>\n",
              "      <td>-0.433536</td>\n",
              "      <td>-0.002073</td>\n",
              "      <td>-0.074622</td>\n",
              "      <td>-0.468599</td>\n",
              "      <td>0.052445</td>\n",
              "      <td>0.022269</td>\n",
              "      <td>-0.076298</td>\n",
              "      <td>-0.337522</td>\n",
              "      <td>-0.235191</td>\n",
              "      <td>-0.422814</td>\n",
              "      <td>0.148432</td>\n",
              "      <td>-0.471092</td>\n",
              "      <td>-0.296871</td>\n",
              "      <td>-0.528327</td>\n",
              "      <td>0.558136</td>\n",
              "      <td>-0.133229</td>\n",
              "      <td>-0.155987</td>\n",
              "      <td>-0.120247</td>\n",
              "      <td>0.327593</td>\n",
              "      <td>-0.147800</td>\n",
              "      <td>-0.591868</td>\n",
              "      <td>0.602623</td>\n",
              "      <td>0.450769</td>\n",
              "      <td>...</td>\n",
              "      <td>0.365095</td>\n",
              "      <td>-0.528006</td>\n",
              "      <td>0.295970</td>\n",
              "      <td>0.067108</td>\n",
              "      <td>-0.250243</td>\n",
              "      <td>-0.110665</td>\n",
              "      <td>-0.214344</td>\n",
              "      <td>-0.280492</td>\n",
              "      <td>-0.036098</td>\n",
              "      <td>-0.128288</td>\n",
              "      <td>-0.498922</td>\n",
              "      <td>-0.469595</td>\n",
              "      <td>0.673664</td>\n",
              "      <td>0.538050</td>\n",
              "      <td>0.297528</td>\n",
              "      <td>0.066530</td>\n",
              "      <td>0.240252</td>\n",
              "      <td>-0.170949</td>\n",
              "      <td>0.485924</td>\n",
              "      <td>-0.093815</td>\n",
              "      <td>0.397476</td>\n",
              "      <td>0.017923</td>\n",
              "      <td>0.321260</td>\n",
              "      <td>-0.131709</td>\n",
              "      <td>-0.133430</td>\n",
              "      <td>0.178220</td>\n",
              "      <td>0.201902</td>\n",
              "      <td>-0.205648</td>\n",
              "      <td>-0.676835</td>\n",
              "      <td>-0.433554</td>\n",
              "      <td>0.005085</td>\n",
              "      <td>-0.239410</td>\n",
              "      <td>0.548401</td>\n",
              "      <td>0.425222</td>\n",
              "      <td>-0.308095</td>\n",
              "      <td>-0.052622</td>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.514201</td>\n",
              "      <td>0.405908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-1</th>\n",
              "      <td>0.086032</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>-0.151590</td>\n",
              "      <td>-0.122541</td>\n",
              "      <td>0.144537</td>\n",
              "      <td>-0.009973</td>\n",
              "      <td>-0.047558</td>\n",
              "      <td>-0.009051</td>\n",
              "      <td>0.161274</td>\n",
              "      <td>0.037178</td>\n",
              "      <td>-0.009256</td>\n",
              "      <td>0.002632</td>\n",
              "      <td>-0.070193</td>\n",
              "      <td>-0.063414</td>\n",
              "      <td>-0.000944</td>\n",
              "      <td>-0.023748</td>\n",
              "      <td>-0.034714</td>\n",
              "      <td>-0.131031</td>\n",
              "      <td>0.196596</td>\n",
              "      <td>-0.061441</td>\n",
              "      <td>0.090620</td>\n",
              "      <td>-0.004299</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.019435</td>\n",
              "      <td>0.015661</td>\n",
              "      <td>-0.098907</td>\n",
              "      <td>-0.091071</td>\n",
              "      <td>-0.053331</td>\n",
              "      <td>-0.049514</td>\n",
              "      <td>0.187382</td>\n",
              "      <td>-0.091232</td>\n",
              "      <td>0.045417</td>\n",
              "      <td>0.044373</td>\n",
              "      <td>-0.077671</td>\n",
              "      <td>-0.005265</td>\n",
              "      <td>-0.042213</td>\n",
              "      <td>0.050546</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.015556</td>\n",
              "      <td>-0.017184</td>\n",
              "      <td>0.043104</td>\n",
              "      <td>-0.189662</td>\n",
              "      <td>-0.050194</td>\n",
              "      <td>-0.007878</td>\n",
              "      <td>-0.083539</td>\n",
              "      <td>-0.042175</td>\n",
              "      <td>0.014307</td>\n",
              "      <td>-0.134166</td>\n",
              "      <td>-0.026985</td>\n",
              "      <td>0.088382</td>\n",
              "      <td>-0.077453</td>\n",
              "      <td>0.015545</td>\n",
              "      <td>-0.027527</td>\n",
              "      <td>-0.071078</td>\n",
              "      <td>-0.095445</td>\n",
              "      <td>0.049612</td>\n",
              "      <td>-0.040518</td>\n",
              "      <td>-0.074277</td>\n",
              "      <td>-0.022356</td>\n",
              "      <td>0.125763</td>\n",
              "      <td>-0.082779</td>\n",
              "      <td>0.020292</td>\n",
              "      <td>-0.023171</td>\n",
              "      <td>-0.207192</td>\n",
              "      <td>-0.066570</td>\n",
              "      <td>-0.057007</td>\n",
              "      <td>0.002062</td>\n",
              "      <td>0.029795</td>\n",
              "      <td>-0.205998</td>\n",
              "      <td>0.060051</td>\n",
              "      <td>0.115071</td>\n",
              "      <td>0.160140</td>\n",
              "      <td>0.015098</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.032233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-2</th>\n",
              "      <td>0.176188</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>0.018516</td>\n",
              "      <td>0.015190</td>\n",
              "      <td>-0.144205</td>\n",
              "      <td>-0.128029</td>\n",
              "      <td>-0.081332</td>\n",
              "      <td>-0.105050</td>\n",
              "      <td>0.011198</td>\n",
              "      <td>-0.063501</td>\n",
              "      <td>0.082011</td>\n",
              "      <td>-0.082204</td>\n",
              "      <td>-0.059607</td>\n",
              "      <td>-0.137811</td>\n",
              "      <td>-0.085491</td>\n",
              "      <td>0.053335</td>\n",
              "      <td>0.028813</td>\n",
              "      <td>-0.061160</td>\n",
              "      <td>-0.129131</td>\n",
              "      <td>-0.007426</td>\n",
              "      <td>-0.034230</td>\n",
              "      <td>-0.128312</td>\n",
              "      <td>-0.067363</td>\n",
              "      <td>-0.126554</td>\n",
              "      <td>0.036984</td>\n",
              "      <td>-0.129481</td>\n",
              "      <td>-0.017941</td>\n",
              "      <td>-0.152288</td>\n",
              "      <td>0.172191</td>\n",
              "      <td>-0.100086</td>\n",
              "      <td>-0.033010</td>\n",
              "      <td>-0.015481</td>\n",
              "      <td>0.001098</td>\n",
              "      <td>-0.020374</td>\n",
              "      <td>-0.157977</td>\n",
              "      <td>0.169464</td>\n",
              "      <td>0.144449</td>\n",
              "      <td>...</td>\n",
              "      <td>0.089525</td>\n",
              "      <td>-0.140916</td>\n",
              "      <td>0.008587</td>\n",
              "      <td>0.042106</td>\n",
              "      <td>-0.018846</td>\n",
              "      <td>-0.008093</td>\n",
              "      <td>-0.074404</td>\n",
              "      <td>-0.080120</td>\n",
              "      <td>-0.020085</td>\n",
              "      <td>-0.028099</td>\n",
              "      <td>-0.098775</td>\n",
              "      <td>-0.113000</td>\n",
              "      <td>0.175916</td>\n",
              "      <td>0.119166</td>\n",
              "      <td>0.071051</td>\n",
              "      <td>0.025358</td>\n",
              "      <td>0.078971</td>\n",
              "      <td>-0.086326</td>\n",
              "      <td>0.149456</td>\n",
              "      <td>0.033432</td>\n",
              "      <td>0.124239</td>\n",
              "      <td>-0.006327</td>\n",
              "      <td>0.120148</td>\n",
              "      <td>-0.041162</td>\n",
              "      <td>-0.030040</td>\n",
              "      <td>0.048549</td>\n",
              "      <td>0.096369</td>\n",
              "      <td>0.000494</td>\n",
              "      <td>-0.172627</td>\n",
              "      <td>-0.130200</td>\n",
              "      <td>0.090115</td>\n",
              "      <td>-0.055655</td>\n",
              "      <td>0.138085</td>\n",
              "      <td>0.061574</td>\n",
              "      <td>-0.093631</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>0.103985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-3</th>\n",
              "      <td>0.011266</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>0.042231</td>\n",
              "      <td>-0.043177</td>\n",
              "      <td>-0.175692</td>\n",
              "      <td>-0.086167</td>\n",
              "      <td>-0.014052</td>\n",
              "      <td>-0.074101</td>\n",
              "      <td>0.181024</td>\n",
              "      <td>0.030539</td>\n",
              "      <td>0.192727</td>\n",
              "      <td>0.128792</td>\n",
              "      <td>-0.045688</td>\n",
              "      <td>0.033974</td>\n",
              "      <td>-0.070920</td>\n",
              "      <td>0.237669</td>\n",
              "      <td>0.112392</td>\n",
              "      <td>0.027867</td>\n",
              "      <td>-0.167263</td>\n",
              "      <td>0.197013</td>\n",
              "      <td>-0.049480</td>\n",
              "      <td>-0.113336</td>\n",
              "      <td>0.175615</td>\n",
              "      <td>0.111355</td>\n",
              "      <td>0.007168</td>\n",
              "      <td>-0.022381</td>\n",
              "      <td>-0.128269</td>\n",
              "      <td>-0.042827</td>\n",
              "      <td>0.098416</td>\n",
              "      <td>-0.091962</td>\n",
              "      <td>-0.083806</td>\n",
              "      <td>0.184985</td>\n",
              "      <td>-0.070933</td>\n",
              "      <td>-0.317859</td>\n",
              "      <td>-0.228039</td>\n",
              "      <td>0.084346</td>\n",
              "      <td>0.054827</td>\n",
              "      <td>...</td>\n",
              "      <td>0.039519</td>\n",
              "      <td>0.000851</td>\n",
              "      <td>0.011655</td>\n",
              "      <td>-0.116724</td>\n",
              "      <td>0.304819</td>\n",
              "      <td>-0.087159</td>\n",
              "      <td>-0.134135</td>\n",
              "      <td>-0.031211</td>\n",
              "      <td>0.174116</td>\n",
              "      <td>0.060289</td>\n",
              "      <td>-0.119276</td>\n",
              "      <td>-0.140391</td>\n",
              "      <td>0.110547</td>\n",
              "      <td>0.145925</td>\n",
              "      <td>0.155011</td>\n",
              "      <td>0.049182</td>\n",
              "      <td>-0.007754</td>\n",
              "      <td>-0.128488</td>\n",
              "      <td>0.078139</td>\n",
              "      <td>0.012422</td>\n",
              "      <td>0.040728</td>\n",
              "      <td>0.164467</td>\n",
              "      <td>0.171886</td>\n",
              "      <td>-0.069777</td>\n",
              "      <td>0.066560</td>\n",
              "      <td>0.102111</td>\n",
              "      <td>-0.036922</td>\n",
              "      <td>0.111994</td>\n",
              "      <td>-0.133740</td>\n",
              "      <td>-0.226928</td>\n",
              "      <td>0.075982</td>\n",
              "      <td>0.178422</td>\n",
              "      <td>0.016467</td>\n",
              "      <td>-0.089317</td>\n",
              "      <td>-0.166426</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>0.058219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-4</th>\n",
              "      <td>0.403153</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.057449</td>\n",
              "      <td>0.206405</td>\n",
              "      <td>-0.032748</td>\n",
              "      <td>-0.474828</td>\n",
              "      <td>-0.274167</td>\n",
              "      <td>-0.458021</td>\n",
              "      <td>0.116467</td>\n",
              "      <td>-0.207078</td>\n",
              "      <td>0.210440</td>\n",
              "      <td>-0.307280</td>\n",
              "      <td>0.019531</td>\n",
              "      <td>-0.275700</td>\n",
              "      <td>-0.422889</td>\n",
              "      <td>-0.012207</td>\n",
              "      <td>-0.088152</td>\n",
              "      <td>-0.311798</td>\n",
              "      <td>0.286106</td>\n",
              "      <td>-0.055368</td>\n",
              "      <td>-0.113396</td>\n",
              "      <td>-0.120743</td>\n",
              "      <td>-0.233682</td>\n",
              "      <td>-0.340708</td>\n",
              "      <td>0.070292</td>\n",
              "      <td>-0.360274</td>\n",
              "      <td>-0.225461</td>\n",
              "      <td>-0.402256</td>\n",
              "      <td>0.324362</td>\n",
              "      <td>0.091731</td>\n",
              "      <td>-0.052787</td>\n",
              "      <td>-0.073490</td>\n",
              "      <td>0.195062</td>\n",
              "      <td>-0.124394</td>\n",
              "      <td>-0.277002</td>\n",
              "      <td>0.285256</td>\n",
              "      <td>0.300517</td>\n",
              "      <td>...</td>\n",
              "      <td>0.215930</td>\n",
              "      <td>-0.292602</td>\n",
              "      <td>-0.008241</td>\n",
              "      <td>-0.005070</td>\n",
              "      <td>-0.284391</td>\n",
              "      <td>-0.116918</td>\n",
              "      <td>-0.252399</td>\n",
              "      <td>-0.250280</td>\n",
              "      <td>0.000141</td>\n",
              "      <td>-0.172896</td>\n",
              "      <td>-0.324769</td>\n",
              "      <td>-0.291644</td>\n",
              "      <td>0.302912</td>\n",
              "      <td>0.222951</td>\n",
              "      <td>0.144028</td>\n",
              "      <td>-0.020950</td>\n",
              "      <td>0.129354</td>\n",
              "      <td>-0.141319</td>\n",
              "      <td>0.215713</td>\n",
              "      <td>-0.060261</td>\n",
              "      <td>0.240649</td>\n",
              "      <td>-0.250950</td>\n",
              "      <td>0.144547</td>\n",
              "      <td>-0.045769</td>\n",
              "      <td>-0.083932</td>\n",
              "      <td>-0.100498</td>\n",
              "      <td>0.118725</td>\n",
              "      <td>-0.257704</td>\n",
              "      <td>-0.386764</td>\n",
              "      <td>-0.172222</td>\n",
              "      <td>-0.023752</td>\n",
              "      <td>-0.164868</td>\n",
              "      <td>0.404440</td>\n",
              "      <td>0.317500</td>\n",
              "      <td>-0.225094</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.250713</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>g-767</th>\n",
              "      <td>-0.052622</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>-0.081016</td>\n",
              "      <td>-0.000886</td>\n",
              "      <td>0.137336</td>\n",
              "      <td>-0.101191</td>\n",
              "      <td>-0.013157</td>\n",
              "      <td>-0.016431</td>\n",
              "      <td>-0.009570</td>\n",
              "      <td>-0.102954</td>\n",
              "      <td>-0.066698</td>\n",
              "      <td>-0.093822</td>\n",
              "      <td>0.244340</td>\n",
              "      <td>-0.069415</td>\n",
              "      <td>-0.094064</td>\n",
              "      <td>-0.127133</td>\n",
              "      <td>-0.080124</td>\n",
              "      <td>0.043800</td>\n",
              "      <td>0.077647</td>\n",
              "      <td>-0.163991</td>\n",
              "      <td>-0.007126</td>\n",
              "      <td>-0.059084</td>\n",
              "      <td>-0.105259</td>\n",
              "      <td>-0.023880</td>\n",
              "      <td>0.128335</td>\n",
              "      <td>-0.119971</td>\n",
              "      <td>-0.107446</td>\n",
              "      <td>-0.035556</td>\n",
              "      <td>0.094170</td>\n",
              "      <td>0.158429</td>\n",
              "      <td>0.108885</td>\n",
              "      <td>-0.077054</td>\n",
              "      <td>-0.067268</td>\n",
              "      <td>0.334189</td>\n",
              "      <td>0.217292</td>\n",
              "      <td>0.049036</td>\n",
              "      <td>-0.031135</td>\n",
              "      <td>...</td>\n",
              "      <td>0.052898</td>\n",
              "      <td>0.121333</td>\n",
              "      <td>-0.038647</td>\n",
              "      <td>0.140140</td>\n",
              "      <td>-0.246716</td>\n",
              "      <td>0.000084</td>\n",
              "      <td>-0.021733</td>\n",
              "      <td>-0.003739</td>\n",
              "      <td>-0.010499</td>\n",
              "      <td>-0.045364</td>\n",
              "      <td>0.103892</td>\n",
              "      <td>0.056790</td>\n",
              "      <td>-0.046818</td>\n",
              "      <td>-0.082454</td>\n",
              "      <td>-0.050249</td>\n",
              "      <td>0.043764</td>\n",
              "      <td>0.028057</td>\n",
              "      <td>0.107099</td>\n",
              "      <td>0.006368</td>\n",
              "      <td>0.071568</td>\n",
              "      <td>-0.041222</td>\n",
              "      <td>-0.271532</td>\n",
              "      <td>-0.134224</td>\n",
              "      <td>0.100008</td>\n",
              "      <td>0.023745</td>\n",
              "      <td>-0.179493</td>\n",
              "      <td>0.113520</td>\n",
              "      <td>-0.331936</td>\n",
              "      <td>-0.050898</td>\n",
              "      <td>0.190015</td>\n",
              "      <td>-0.010391</td>\n",
              "      <td>-0.180252</td>\n",
              "      <td>0.003976</td>\n",
              "      <td>-0.027425</td>\n",
              "      <td>0.153722</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.001136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-768</th>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.139000</td>\n",
              "      <td>-0.005791</td>\n",
              "      <td>-0.419437</td>\n",
              "      <td>-0.209968</td>\n",
              "      <td>-0.291836</td>\n",
              "      <td>-0.279889</td>\n",
              "      <td>0.208202</td>\n",
              "      <td>-0.166361</td>\n",
              "      <td>0.243048</td>\n",
              "      <td>-0.241234</td>\n",
              "      <td>-0.042026</td>\n",
              "      <td>-0.363465</td>\n",
              "      <td>-0.247474</td>\n",
              "      <td>0.078093</td>\n",
              "      <td>-0.055035</td>\n",
              "      <td>-0.155576</td>\n",
              "      <td>-0.164930</td>\n",
              "      <td>-0.086306</td>\n",
              "      <td>-0.125517</td>\n",
              "      <td>-0.286908</td>\n",
              "      <td>-0.139057</td>\n",
              "      <td>-0.341518</td>\n",
              "      <td>0.102919</td>\n",
              "      <td>-0.257007</td>\n",
              "      <td>-0.141094</td>\n",
              "      <td>-0.372977</td>\n",
              "      <td>0.369303</td>\n",
              "      <td>-0.365516</td>\n",
              "      <td>0.058365</td>\n",
              "      <td>-0.062415</td>\n",
              "      <td>0.076001</td>\n",
              "      <td>-0.208400</td>\n",
              "      <td>-0.450344</td>\n",
              "      <td>0.463732</td>\n",
              "      <td>0.451185</td>\n",
              "      <td>...</td>\n",
              "      <td>0.234354</td>\n",
              "      <td>-0.463277</td>\n",
              "      <td>0.073003</td>\n",
              "      <td>0.006763</td>\n",
              "      <td>-0.143979</td>\n",
              "      <td>-0.034694</td>\n",
              "      <td>-0.171279</td>\n",
              "      <td>-0.200669</td>\n",
              "      <td>-0.031907</td>\n",
              "      <td>-0.057287</td>\n",
              "      <td>-0.288026</td>\n",
              "      <td>-0.177108</td>\n",
              "      <td>0.459642</td>\n",
              "      <td>0.291729</td>\n",
              "      <td>0.202785</td>\n",
              "      <td>-0.028499</td>\n",
              "      <td>0.130907</td>\n",
              "      <td>-0.233472</td>\n",
              "      <td>0.455238</td>\n",
              "      <td>0.141002</td>\n",
              "      <td>0.222363</td>\n",
              "      <td>0.074620</td>\n",
              "      <td>0.087545</td>\n",
              "      <td>-0.203831</td>\n",
              "      <td>-0.095647</td>\n",
              "      <td>0.048008</td>\n",
              "      <td>0.253031</td>\n",
              "      <td>0.087674</td>\n",
              "      <td>-0.403336</td>\n",
              "      <td>-0.394520</td>\n",
              "      <td>0.077292</td>\n",
              "      <td>0.000048</td>\n",
              "      <td>0.403211</td>\n",
              "      <td>0.241509</td>\n",
              "      <td>-0.250512</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.351651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-769</th>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.068537</td>\n",
              "      <td>-0.278587</td>\n",
              "      <td>-0.082554</td>\n",
              "      <td>0.268571</td>\n",
              "      <td>0.037013</td>\n",
              "      <td>0.184833</td>\n",
              "      <td>0.029409</td>\n",
              "      <td>0.052328</td>\n",
              "      <td>-0.137248</td>\n",
              "      <td>-0.016769</td>\n",
              "      <td>0.006056</td>\n",
              "      <td>-0.010654</td>\n",
              "      <td>0.164345</td>\n",
              "      <td>-0.161975</td>\n",
              "      <td>-0.096549</td>\n",
              "      <td>0.043702</td>\n",
              "      <td>-0.160018</td>\n",
              "      <td>-0.104794</td>\n",
              "      <td>0.011050</td>\n",
              "      <td>-0.057823</td>\n",
              "      <td>-0.046833</td>\n",
              "      <td>0.015717</td>\n",
              "      <td>0.061872</td>\n",
              "      <td>0.107534</td>\n",
              "      <td>-0.032060</td>\n",
              "      <td>0.086102</td>\n",
              "      <td>-0.108052</td>\n",
              "      <td>-0.154845</td>\n",
              "      <td>0.120802</td>\n",
              "      <td>0.040181</td>\n",
              "      <td>-0.082272</td>\n",
              "      <td>0.087573</td>\n",
              "      <td>0.078753</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.061331</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.049599</td>\n",
              "      <td>0.017176</td>\n",
              "      <td>-0.005283</td>\n",
              "      <td>0.017348</td>\n",
              "      <td>-0.014663</td>\n",
              "      <td>0.101831</td>\n",
              "      <td>0.063218</td>\n",
              "      <td>0.151088</td>\n",
              "      <td>-0.116813</td>\n",
              "      <td>0.060308</td>\n",
              "      <td>0.087342</td>\n",
              "      <td>0.214832</td>\n",
              "      <td>-0.118092</td>\n",
              "      <td>-0.038540</td>\n",
              "      <td>-0.095170</td>\n",
              "      <td>-0.031114</td>\n",
              "      <td>-0.064939</td>\n",
              "      <td>0.044082</td>\n",
              "      <td>0.009613</td>\n",
              "      <td>0.146667</td>\n",
              "      <td>-0.059447</td>\n",
              "      <td>0.087822</td>\n",
              "      <td>-0.160610</td>\n",
              "      <td>0.041946</td>\n",
              "      <td>-0.001705</td>\n",
              "      <td>-0.116414</td>\n",
              "      <td>-0.033614</td>\n",
              "      <td>-0.029173</td>\n",
              "      <td>0.106610</td>\n",
              "      <td>-0.002356</td>\n",
              "      <td>0.020662</td>\n",
              "      <td>0.071082</td>\n",
              "      <td>0.013235</td>\n",
              "      <td>0.021152</td>\n",
              "      <td>0.151940</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>-0.083713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-770</th>\n",
              "      <td>-0.514201</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.144631</td>\n",
              "      <td>-0.143428</td>\n",
              "      <td>0.402451</td>\n",
              "      <td>0.441011</td>\n",
              "      <td>0.415967</td>\n",
              "      <td>0.550963</td>\n",
              "      <td>-0.238657</td>\n",
              "      <td>0.230249</td>\n",
              "      <td>-0.406279</td>\n",
              "      <td>0.386103</td>\n",
              "      <td>0.102904</td>\n",
              "      <td>0.406267</td>\n",
              "      <td>0.312653</td>\n",
              "      <td>-0.034036</td>\n",
              "      <td>0.091171</td>\n",
              "      <td>0.263679</td>\n",
              "      <td>-0.092925</td>\n",
              "      <td>0.008841</td>\n",
              "      <td>0.085105</td>\n",
              "      <td>0.370410</td>\n",
              "      <td>0.246689</td>\n",
              "      <td>0.550753</td>\n",
              "      <td>-0.190110</td>\n",
              "      <td>0.393393</td>\n",
              "      <td>0.295798</td>\n",
              "      <td>0.596868</td>\n",
              "      <td>-0.526634</td>\n",
              "      <td>0.231931</td>\n",
              "      <td>-0.039510</td>\n",
              "      <td>0.260259</td>\n",
              "      <td>-0.366389</td>\n",
              "      <td>0.228281</td>\n",
              "      <td>0.571426</td>\n",
              "      <td>-0.592994</td>\n",
              "      <td>-0.429418</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.370370</td>\n",
              "      <td>0.514880</td>\n",
              "      <td>-0.155936</td>\n",
              "      <td>-0.010076</td>\n",
              "      <td>0.375338</td>\n",
              "      <td>0.014833</td>\n",
              "      <td>0.343938</td>\n",
              "      <td>0.369822</td>\n",
              "      <td>0.077286</td>\n",
              "      <td>0.246165</td>\n",
              "      <td>0.439648</td>\n",
              "      <td>0.367189</td>\n",
              "      <td>-0.618890</td>\n",
              "      <td>-0.378256</td>\n",
              "      <td>-0.264342</td>\n",
              "      <td>0.081357</td>\n",
              "      <td>-0.240273</td>\n",
              "      <td>0.285457</td>\n",
              "      <td>-0.468321</td>\n",
              "      <td>0.077384</td>\n",
              "      <td>-0.270256</td>\n",
              "      <td>-0.015109</td>\n",
              "      <td>-0.077811</td>\n",
              "      <td>0.206666</td>\n",
              "      <td>0.238529</td>\n",
              "      <td>-0.184568</td>\n",
              "      <td>-0.126731</td>\n",
              "      <td>0.034281</td>\n",
              "      <td>0.601289</td>\n",
              "      <td>0.488580</td>\n",
              "      <td>0.014331</td>\n",
              "      <td>-0.010849</td>\n",
              "      <td>-0.498222</td>\n",
              "      <td>-0.489116</td>\n",
              "      <td>0.284882</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.425063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-771</th>\n",
              "      <td>0.405908</td>\n",
              "      <td>-0.032233</td>\n",
              "      <td>0.103985</td>\n",
              "      <td>0.058219</td>\n",
              "      <td>0.250713</td>\n",
              "      <td>-0.093237</td>\n",
              "      <td>0.075019</td>\n",
              "      <td>-0.441309</td>\n",
              "      <td>-0.450561</td>\n",
              "      <td>-0.295420</td>\n",
              "      <td>-0.432786</td>\n",
              "      <td>0.144358</td>\n",
              "      <td>-0.229938</td>\n",
              "      <td>0.404019</td>\n",
              "      <td>-0.298917</td>\n",
              "      <td>0.004588</td>\n",
              "      <td>-0.385330</td>\n",
              "      <td>-0.372534</td>\n",
              "      <td>0.073349</td>\n",
              "      <td>-0.110113</td>\n",
              "      <td>-0.288734</td>\n",
              "      <td>-0.127502</td>\n",
              "      <td>0.003787</td>\n",
              "      <td>-0.162129</td>\n",
              "      <td>-0.302231</td>\n",
              "      <td>-0.223294</td>\n",
              "      <td>-0.362299</td>\n",
              "      <td>0.158596</td>\n",
              "      <td>-0.392234</td>\n",
              "      <td>-0.138101</td>\n",
              "      <td>-0.419937</td>\n",
              "      <td>0.447443</td>\n",
              "      <td>-0.303933</td>\n",
              "      <td>0.048098</td>\n",
              "      <td>-0.040134</td>\n",
              "      <td>0.175169</td>\n",
              "      <td>-0.187705</td>\n",
              "      <td>-0.481214</td>\n",
              "      <td>0.540181</td>\n",
              "      <td>0.453666</td>\n",
              "      <td>...</td>\n",
              "      <td>0.269242</td>\n",
              "      <td>-0.542694</td>\n",
              "      <td>0.130851</td>\n",
              "      <td>0.026660</td>\n",
              "      <td>-0.232375</td>\n",
              "      <td>-0.079203</td>\n",
              "      <td>-0.154633</td>\n",
              "      <td>-0.212674</td>\n",
              "      <td>-0.012768</td>\n",
              "      <td>-0.035397</td>\n",
              "      <td>-0.358442</td>\n",
              "      <td>-0.379846</td>\n",
              "      <td>0.561525</td>\n",
              "      <td>0.327231</td>\n",
              "      <td>0.283659</td>\n",
              "      <td>0.083172</td>\n",
              "      <td>0.193545</td>\n",
              "      <td>-0.195285</td>\n",
              "      <td>0.459616</td>\n",
              "      <td>0.099866</td>\n",
              "      <td>0.318208</td>\n",
              "      <td>-0.046797</td>\n",
              "      <td>0.190287</td>\n",
              "      <td>-0.175624</td>\n",
              "      <td>-0.081839</td>\n",
              "      <td>0.175881</td>\n",
              "      <td>0.237110</td>\n",
              "      <td>-0.035015</td>\n",
              "      <td>-0.551324</td>\n",
              "      <td>-0.341807</td>\n",
              "      <td>0.076596</td>\n",
              "      <td>-0.085319</td>\n",
              "      <td>0.426342</td>\n",
              "      <td>0.337007</td>\n",
              "      <td>-0.249602</td>\n",
              "      <td>-0.001136</td>\n",
              "      <td>0.351651</td>\n",
              "      <td>-0.083713</td>\n",
              "      <td>-0.425063</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>772 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            g-0       g-1       g-2  ...     g-769     g-770     g-771\n",
              "g-0    1.000000  0.086032  0.176188  ... -0.127375 -0.514201  0.405908\n",
              "g-1    0.086032  1.000000 -0.054518  ... -0.006866 -0.095108 -0.032233\n",
              "g-2    0.176188 -0.054518  1.000000  ...  0.014489 -0.078661  0.103985\n",
              "g-3    0.011266 -0.027855  0.042633  ... -0.206077 -0.002142  0.058219\n",
              "g-4    0.403153  0.193647  0.013968  ... -0.172727 -0.363673  0.250713\n",
              "...         ...       ...       ...  ...       ...       ...       ...\n",
              "g-767 -0.052622 -0.003378 -0.053149  ...  0.065450  0.008603 -0.001136\n",
              "g-768  0.300241 -0.030756  0.115415  ...  0.079364 -0.382607  0.351651\n",
              "g-769 -0.127375 -0.006866  0.014489  ...  1.000000  0.135853 -0.083713\n",
              "g-770 -0.514201 -0.095108 -0.078661  ...  0.135853  1.000000 -0.425063\n",
              "g-771  0.405908 -0.032233  0.103985  ... -0.083713 -0.425063  1.000000\n",
              "\n",
              "[772 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2eAH8tYROp4E"
      },
      "source": [
        "# Calcula a matriz de correlação\n",
        "corr = dados.loc[:, 'g-0':'g-50'].corr()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 572
        },
        "id": "2rSjtN8cK12z",
        "outputId": "4c12a146-4784-4977-a9c7-69d7879e2399"
      },
      "source": [
        "# Vamos criar um gráfico para visualizar essas correlações\n",
        "\n",
        "import numpy as np\n",
        "\n",
        "# Gera uma máscara para o triângulo superior\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "\n",
        "# Configure a figura matplotlib\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "\n",
        "# Gerar um mapa de cores divergentes personalizado\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Desenhe o mapa de calor com a máscara e a proporção correta\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fec48f385d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AQS_b-T2PgH3"
      },
      "source": [
        "Agora vamos calcular a correlação dos tipos celulares "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5c91jk6KR-EA"
      },
      "source": [
        "corr_celular = dados.loc[:, 'c-0':'c-50'].corr()"
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "id": "GMXCTVooProf",
        "outputId": "443c1bac-b4ab-404b-8974-5b5a0100b0f1"
      },
      "source": [
        "# Gera uma máscara para o triângulo superior\n",
        "mask = np.triu(np.ones_like(corr_celular, dtype=bool))\n",
        "\n",
        "# Configure a figura matplotlib\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "\n",
        "# Gerar um mapa de cores divergentes personalizado\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "\n",
        "# Desenhe o mapa de calor com a máscara e a proporção correta\n",
        "sns.heatmap(corr_celular, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fec491aac50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bon48NO3RMui"
      },
      "source": [
        "É interessante destacar que o valor dos 'c's representa a viabilidade que é o quanto as células sobreviveram ou não a exposição a um determinado composto."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aBajQmDl-7O2"
      },
      "source": [
        "##Desafio 01: Criar tabelas de frequencia com o pandas.groupby()\n",
        "\n",
        "##Desafio 02: Normalizar o crosstab pela coluna\n",
        "\n",
        "##Desafio 03: Explorar outros agregadores. \n",
        "\n",
        "##Desafio 04: Explorar o melt\n",
        "\n",
        "##Desafio 05: Calcular a correlação entre as expressões gênicas (G) e os tipos celulares (C) Refletir sobre os efeitos biológicos.\n",
        "\n",
        "##Desafio 06: Estudar o código usado para plotar a matriz de correlação (*heatmap*).\n",
        "\n",
        "##Desafio 07: Resumo sobre o que aprendeu com os dados."
      ]
    }
  ]
}