20210505_Aula03_Victor.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "20210505_Aula03_Victor.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNJuvGjRDzIhoMvpccXGb5Y",
      "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/victorijsn/imersaodados3/blob/main/20210505_Aula03_Victor.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QCdJQJEcQonx"
      },
      "source": [
        "# Respostas aos desafios da aula 03 - ImersaoDados - Alura\n",
        "Victor Nunes Toscano\n",
        "\n",
        "Linkedin: https://www.linkedin.com/in/vntoscano/\n",
        "\n",
        "Data: 05/05/2021\n",
        "\n",
        "## Contexto\n",
        "\n",
        "- Visualizando os dados\n",
        "\n",
        "\n",
        "## Desafios:\n",
        "\n",
        "1. Desafio 01: Criar tabelas de frequência com pandas.groupby()\n",
        "2. Desafio 02: Normalizar o crosstab pela coluna.\n",
        "3. Desafio 03: Explorar outros agregadores.\n",
        "4. Desafio 04: Explorar o melt.\n",
        "5. Desafio 05: Calcular e analisar a correlação entre G e C. Refletir sobre os efeitos biológicos.\n",
        "6. Desafio 06: Estudar o código que plota a matriz de correlação (heatmap)\n",
        "7. Desafio 07: Resumo do que você aprendeu com os dados\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7vC0PwhyRh2b"
      },
      "source": [
        "Importar a biblioteca [pandas](https://pandas.pydata.org/docs/index.html), a base de dados, as bliblitecas de gráficos e algumas adequações."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oI6FJlFGQlF2"
      },
      "source": [
        "# Bibliotecas\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Config dos plots\n",
        "sns.set()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fkYSi2TBkWhb"
      },
      "source": [
        "# Importar os dados\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "dados = pd.read_csv(url_dados, compression = 'zip')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CFse2h0Vcrp4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "outputId": "b51bcc1a-11e4-4c23-d3a3-bad184eea0be"
      },
      "source": [
        "# Ajustes nos nomes das variáveis\n",
        "mapa = {'droga': 'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)\n",
        "dados.columns = dados.columns.str.replace('-','_')\n",
        "\n",
        "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>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": 58
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WwZLZN9aR6bQ"
      },
      "source": [
        "### Resposta 01\n",
        "#### Criar tabelas de frequência com pandas.groupby()\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "M2UZMGV1OCO2",
        "outputId": "18427ce4-b916-4073-f0c7-bc6f1b34ea29"
      },
      "source": [
        "# Criando uma tabela agrupada e contando valores\n",
        "dados[['id','dose','tempo', 'tratamento']].groupby(['tratamento','dose','tempo']).count()"
      ],
      "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></th>\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tratamento</th>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"6\" valign=\"top\">com_controle</th>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"6\" valign=\"top\">com_droga</th>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>3585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>4011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>3600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>3581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>3591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>3580</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                           id\n",
              "tratamento   dose tempo      \n",
              "com_controle D1   24      301\n",
              "                  48      343\n",
              "                  72      307\n",
              "             D2   24      305\n",
              "                  48      305\n",
              "                  72      305\n",
              "com_droga    D1   24     3585\n",
              "                  48     4011\n",
              "                  72     3600\n",
              "             D2   24     3581\n",
              "                  48     3591\n",
              "                  72     3580"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "Wcx7PNHOauUW",
        "outputId": "95eb350a-bcc0-4699-e96a-4b88caef3dd8"
      },
      "source": [
        "# Replicando a tabela obtida por crosstab\n",
        "dados.groupby(by=(['dose','tempo']))['tratamento'].value_counts().unstack() "
      ],
      "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>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": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KgrcgIGQSzAo"
      },
      "source": [
        "### Resposta 02\n",
        "#### Normalizar o crosstab pela coluna.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "xxMpD-dbS3-i",
        "outputId": "832d5b98-ef2b-4f64-be75-29fdc9be261a"
      },
      "source": [
        "pd.crosstab([dados['dose'], dados['tempo']],  dados['tratamento'], normalize='columns')"
      ],
      "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>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>0.161308</td>\n",
              "      <td>0.163341</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.183816</td>\n",
              "      <td>0.182750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.164523</td>\n",
              "      <td>0.164024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.163451</td>\n",
              "      <td>0.163158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.163451</td>\n",
              "      <td>0.163614</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.163451</td>\n",
              "      <td>0.163113</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.161308   0.163341\n",
              "     48         0.183816   0.182750\n",
              "     72         0.164523   0.164024\n",
              "D2   24         0.163451   0.163158\n",
              "     48         0.163451   0.163614\n",
              "     72         0.163451   0.163113"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f2PGQ5v2Tkb5"
      },
      "source": [
        "**Conclusão:** os dados estão normalizados."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tM1YnzZwTHVX"
      },
      "source": [
        "### Resposta 03\n",
        "#### Explorar outros agregadores."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "oie4WoBrTxoi",
        "outputId": "1bcfc21c-0ecf-4270-da5a-8631076d8f15"
      },
      "source": [
        "# Mediana\n",
        "pd.crosstab([dados['dose'], dados['tempo']],  dados['tratamento'], values=dados['g_0'], aggfunc='median')"
      ],
      "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>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>-0.2912</td>\n",
              "      <td>0.02700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-0.2145</td>\n",
              "      <td>0.01620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>-0.3655</td>\n",
              "      <td>0.02615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.0096</td>\n",
              "      <td>-0.02610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-0.0506</td>\n",
              "      <td>-0.02960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.0528</td>\n",
              "      <td>0.00015</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24          -0.2912    0.02700\n",
              "     48          -0.2145    0.01620\n",
              "     72          -0.3655    0.02615\n",
              "D2   24           0.0096   -0.02610\n",
              "     48          -0.0506   -0.02960\n",
              "     72           0.0528    0.00015"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "3b6FcWc-Vwnm",
        "outputId": "b4cd7aa4-9843-48cb-b645-6683d841b6dd"
      },
      "source": [
        "# Soma\n",
        "pd.crosstab([dados['dose'], dados['tempo']],  dados['tratamento'], values=dados['g_0'], aggfunc='sum')"
      ],
      "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>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>-75.7799</td>\n",
              "      <td>1319.2648</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-42.1113</td>\n",
              "      <td>1654.4150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>-90.6483</td>\n",
              "      <td>1030.5010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>3.2800</td>\n",
              "      <td>412.7202</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>4.0180</td>\n",
              "      <td>770.1980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>21.4262</td>\n",
              "      <td>907.3112</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         -75.7799  1319.2648\n",
              "     48         -42.1113  1654.4150\n",
              "     72         -90.6483  1030.5010\n",
              "D2   24           3.2800   412.7202\n",
              "     48           4.0180   770.1980\n",
              "     72          21.4262   907.3112"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "XDNuURkzV0uF",
        "outputId": "6b3a4ac4-48a4-43d2-d90a-528ee441d9c2"
      },
      "source": [
        "# Desvio padrão\n",
        "pd.crosstab([dados['dose'], dados['tempo']],  dados['tratamento'], values=dados['g_0'], aggfunc='std')"
      ],
      "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>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>0.751395</td>\n",
              "      <td>1.461954</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.853396</td>\n",
              "      <td>1.693903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.769294</td>\n",
              "      <td>1.458600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.836626</td>\n",
              "      <td>1.044999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.836845</td>\n",
              "      <td>1.315476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.878041</td>\n",
              "      <td>1.451532</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.751395   1.461954\n",
              "     48         0.853396   1.693903\n",
              "     72         0.769294   1.458600\n",
              "D2   24         0.836626   1.044999\n",
              "     48         0.836845   1.315476\n",
              "     72         0.878041   1.451532"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O_JRRHsPTio7"
      },
      "source": [
        "### Resposta 04\n",
        "#### Explorar o melt.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "7Tjz8Lk7WFM-",
        "outputId": "9a5622d1-526e-41f6-9668-bb83bc420cfd"
      },
      "source": [
        "base_tidy = pd.melt(dados, id_vars=['id','tratamento','dose','tempo','composto'], value_vars=['g_0'], value_name='valores', var_name='gene')\n",
        "base_tidy.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>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th>composto</th>\n",
              "      <th>gene</th>\n",
              "      <th>valores</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>D1</td>\n",
              "      <td>24</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>g_0</td>\n",
              "      <td>1.0620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>D1</td>\n",
              "      <td>72</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>g_0</td>\n",
              "      <td>0.0743</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>D1</td>\n",
              "      <td>48</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>g_0</td>\n",
              "      <td>0.6280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>D1</td>\n",
              "      <td>48</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>g_0</td>\n",
              "      <td>-0.5138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>D2</td>\n",
              "      <td>72</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>g_0</td>\n",
              "      <td>-0.3254</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento dose  tempo   composto gene  valores\n",
              "0  id_000644bb2  com_droga   D1     24  b68db1d53  g_0   1.0620\n",
              "1  id_000779bfc  com_droga   D1     72  df89a8e5a  g_0   0.0743\n",
              "2  id_000a6266a  com_droga   D1     48  18bb41b2c  g_0   0.6280\n",
              "3  id_0015fd391  com_droga   D1     48  8c7f86626  g_0  -0.5138\n",
              "4  id_001626bd3  com_droga   D2     72  7cbed3131  g_0  -0.3254"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "twJq4QXj1dNK",
        "outputId": "52808371-1978-4441-8eda-e2d87626b783"
      },
      "source": [
        "base_tidy['valores'].describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    23814.000000\n",
              "mean         0.248366\n",
              "std          1.393399\n",
              "min         -5.513000\n",
              "25%         -0.473075\n",
              "50%         -0.008850\n",
              "75%          0.525700\n",
              "max         10.000000\n",
              "Name: valores, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "loj6WHd5T3Uu"
      },
      "source": [
        "### Resposta 05\n",
        "#### Calcular e analisar a correlação entre G e C. Refletir sobre os efeitos biológicos."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BpWC1mM1h9Sy"
      },
      "source": [
        "genes = dados.loc[:,'g_0':'g_49']\n",
        "celulas = dados.loc[:,'c_0':'c_49']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        },
        "id": "eVk8yttNy7WG",
        "outputId": "c3752f6f-347d-436b-ae0f-8a375958e583"
      },
      "source": [
        "dados_c_g = pd.concat([genes,celulas], axis=1)\n",
        "dados_c_g.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>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>c_10</th>\n",
              "      <th>c_11</th>\n",
              "      <th>c_12</th>\n",
              "      <th>c_13</th>\n",
              "      <th>c_14</th>\n",
              "      <th>c_15</th>\n",
              "      <th>c_16</th>\n",
              "      <th>c_17</th>\n",
              "      <th>c_18</th>\n",
              "      <th>c_19</th>\n",
              "      <th>c_20</th>\n",
              "      <th>c_21</th>\n",
              "      <th>c_22</th>\n",
              "      <th>c_23</th>\n",
              "      <th>c_24</th>\n",
              "      <th>c_25</th>\n",
              "      <th>c_26</th>\n",
              "      <th>c_27</th>\n",
              "      <th>c_28</th>\n",
              "      <th>c_29</th>\n",
              "      <th>c_30</th>\n",
              "      <th>c_31</th>\n",
              "      <th>c_32</th>\n",
              "      <th>c_33</th>\n",
              "      <th>c_34</th>\n",
              "      <th>c_35</th>\n",
              "      <th>c_36</th>\n",
              "      <th>c_37</th>\n",
              "      <th>c_38</th>\n",
              "      <th>c_39</th>\n",
              "      <th>c_40</th>\n",
              "      <th>c_41</th>\n",
              "      <th>c_42</th>\n",
              "      <th>c_43</th>\n",
              "      <th>c_44</th>\n",
              "      <th>c_45</th>\n",
              "      <th>c_46</th>\n",
              "      <th>c_47</th>\n",
              "      <th>c_48</th>\n",
              "      <th>c_49</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\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>0.2198</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.5055</td>\n",
              "      <td>-0.5119</td>\n",
              "      <td>-0.2162</td>\n",
              "      <td>...</td>\n",
              "      <td>0.9084</td>\n",
              "      <td>0.6857</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.7602</td>\n",
              "      <td>-0.1048</td>\n",
              "      <td>0.3594</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.2798</td>\n",
              "      <td>-0.4010</td>\n",
              "      <td>0.6842</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.3522</td>\n",
              "      <td>-0.3971</td>\n",
              "      <td>-0.2115</td>\n",
              "      <td>-0.2687</td>\n",
              "      <td>0.5196</td>\n",
              "      <td>0.1594</td>\n",
              "      <td>0.8920</td>\n",
              "      <td>0.6485</td>\n",
              "      <td>0.6078</td>\n",
              "      <td>0.3799</td>\n",
              "      <td>-0.1727</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.3600</td>\n",
              "      <td>0.5124</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>0.6159</td>\n",
              "      <td>0.4689</td>\n",
              "      <td>-0.0773</td>\n",
              "      <td>0.4728</td>\n",
              "      <td>-0.0143</td>\n",
              "      <td>-0.5344</td>\n",
              "      <td>0.3578</td>\n",
              "      <td>0.3248</td>\n",
              "      <td>0.8903</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>1.3070</td>\n",
              "      <td>-1.0230</td>\n",
              "      <td>0.7709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\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>-0.2102</td>\n",
              "      <td>0.1656</td>\n",
              "      <td>0.5300</td>\n",
              "      <td>-0.2568</td>\n",
              "      <td>-0.0455</td>\n",
              "      <td>...</td>\n",
              "      <td>0.7787</td>\n",
              "      <td>0.2074</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>0.2433</td>\n",
              "      <td>0.2010</td>\n",
              "      <td>0.7094</td>\n",
              "      <td>-0.4210</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.4045</td>\n",
              "      <td>0.1138</td>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.0087</td>\n",
              "      <td>0.4864</td>\n",
              "      <td>-0.0140</td>\n",
              "      <td>0.0164</td>\n",
              "      <td>0.1759</td>\n",
              "      <td>0.6654</td>\n",
              "      <td>0.3556</td>\n",
              "      <td>0.8175</td>\n",
              "      <td>0.0474</td>\n",
              "      <td>0.5589</td>\n",
              "      <td>0.4481</td>\n",
              "      <td>0.1888</td>\n",
              "      <td>0.3712</td>\n",
              "      <td>0.7837</td>\n",
              "      <td>0.6860</td>\n",
              "      <td>0.4123</td>\n",
              "      <td>0.1560</td>\n",
              "      <td>-0.1203</td>\n",
              "      <td>-1.2780</td>\n",
              "      <td>0.6743</td>\n",
              "      <td>0.7358</td>\n",
              "      <td>0.1334</td>\n",
              "      <td>-0.5193</td>\n",
              "      <td>0.2281</td>\n",
              "      <td>0.0158</td>\n",
              "      <td>-0.5658</td>\n",
              "      <td>0.6065</td>\n",
              "      <td>0.6259</td>\n",
              "      <td>0.4716</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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>-1.1800</td>\n",
              "      <td>0.1256</td>\n",
              "      <td>-0.1219</td>\n",
              "      <td>5.4470</td>\n",
              "      <td>1.0310</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3084</td>\n",
              "      <td>-0.0899</td>\n",
              "      <td>-0.0397</td>\n",
              "      <td>-0.5077</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0100</td>\n",
              "      <td>-0.6915</td>\n",
              "      <td>0.0643</td>\n",
              "      <td>-0.8927</td>\n",
              "      <td>-0.2048</td>\n",
              "      <td>0.0773</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>-0.1602</td>\n",
              "      <td>-0.2028</td>\n",
              "      <td>-0.2216</td>\n",
              "      <td>-1.1380</td>\n",
              "      <td>0.3668</td>\n",
              "      <td>-1.0620</td>\n",
              "      <td>-0.7736</td>\n",
              "      <td>0.6225</td>\n",
              "      <td>0.6274</td>\n",
              "      <td>-0.3038</td>\n",
              "      <td>0.1171</td>\n",
              "      <td>-0.0550</td>\n",
              "      <td>-0.0289</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>-0.7937</td>\n",
              "      <td>-1.0610</td>\n",
              "      <td>-0.6409</td>\n",
              "      <td>0.3884</td>\n",
              "      <td>-1.0330</td>\n",
              "      <td>-0.0055</td>\n",
              "      <td>0.1212</td>\n",
              "      <td>-0.7020</td>\n",
              "      <td>-0.7065</td>\n",
              "      <td>-0.5192</td>\n",
              "      <td>-0.3181</td>\n",
              "      <td>0.1787</td>\n",
              "      <td>0.3354</td>\n",
              "      <td>0.1349</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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>-1.6740</td>\n",
              "      <td>-1.6720</td>\n",
              "      <td>-1.2690</td>\n",
              "      <td>3.0900</td>\n",
              "      <td>-0.3814</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.2730</td>\n",
              "      <td>-4.6920</td>\n",
              "      <td>-1.2750</td>\n",
              "      <td>-1.4970</td>\n",
              "      <td>-0.0156</td>\n",
              "      <td>-1.9350</td>\n",
              "      <td>-1.3430</td>\n",
              "      <td>-0.5252</td>\n",
              "      <td>-2.7210</td>\n",
              "      <td>-0.2524</td>\n",
              "      <td>0.9197</td>\n",
              "      <td>-3.1220</td>\n",
              "      <td>-1.9180</td>\n",
              "      <td>-0.6761</td>\n",
              "      <td>-2.8360</td>\n",
              "      <td>-1.6890</td>\n",
              "      <td>-4.4990</td>\n",
              "      <td>-1.5190</td>\n",
              "      <td>-2.2730</td>\n",
              "      <td>-0.3250</td>\n",
              "      <td>0.1895</td>\n",
              "      <td>-2.4220</td>\n",
              "      <td>0.0670</td>\n",
              "      <td>-1.9870</td>\n",
              "      <td>-0.6482</td>\n",
              "      <td>-0.0023</td>\n",
              "      <td>-1.9930</td>\n",
              "      <td>-0.8042</td>\n",
              "      <td>-3.6160</td>\n",
              "      <td>-0.3487</td>\n",
              "      <td>-1.2560</td>\n",
              "      <td>-2.7220</td>\n",
              "      <td>-2.1970</td>\n",
              "      <td>-2.9030</td>\n",
              "      <td>-1.1030</td>\n",
              "      <td>-2.3020</td>\n",
              "      <td>-2.0030</td>\n",
              "      <td>-1.3390</td>\n",
              "      <td>-3.0160</td>\n",
              "      <td>-3.0040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\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>-0.7110</td>\n",
              "      <td>-1.4470</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.7888</td>\n",
              "      <td>-0.0848</td>\n",
              "      <td>...</td>\n",
              "      <td>0.9642</td>\n",
              "      <td>-0.0853</td>\n",
              "      <td>0.1559</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>0.1197</td>\n",
              "      <td>0.6774</td>\n",
              "      <td>0.1332</td>\n",
              "      <td>-0.5176</td>\n",
              "      <td>0.1232</td>\n",
              "      <td>0.0827</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.5953</td>\n",
              "      <td>1.0600</td>\n",
              "      <td>-0.4255</td>\n",
              "      <td>0.8624</td>\n",
              "      <td>1.0010</td>\n",
              "      <td>0.0840</td>\n",
              "      <td>-0.6553</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5490</td>\n",
              "      <td>0.6331</td>\n",
              "      <td>0.5227</td>\n",
              "      <td>0.2186</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>0.8947</td>\n",
              "      <td>-0.0202</td>\n",
              "      <td>0.5966</td>\n",
              "      <td>0.2249</td>\n",
              "      <td>0.5671</td>\n",
              "      <td>0.6382</td>\n",
              "      <td>-0.3909</td>\n",
              "      <td>0.7040</td>\n",
              "      <td>0.1462</td>\n",
              "      <td>0.0655</td>\n",
              "      <td>-0.5605</td>\n",
              "      <td>0.5903</td>\n",
              "      <td>-0.2353</td>\n",
              "      <td>-0.1285</td>\n",
              "      <td>-0.1740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 100 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      g_0     g_1     g_2     g_3  ...    c_46    c_47    c_48    c_49\n",
              "0  1.0620  0.5577 -0.2479 -0.6208  ...  1.0340  1.3070 -1.0230  0.7709\n",
              "1  0.0743  0.4087  0.2991  0.0604  ... -0.5658  0.6065  0.6259  0.4716\n",
              "2  0.6280  0.5817  1.5540 -0.0764  ... -0.3181  0.1787  0.3354  0.1349\n",
              "3 -0.5138 -0.2491 -0.2656  0.5288  ... -2.0030 -1.3390 -3.0160 -3.0040\n",
              "4 -0.3254 -0.4009  0.9700  0.6919  ...  0.5903 -0.2353 -0.1285 -0.1740\n",
              "\n",
              "[5 rows x 100 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "HvpKWBNtzD9A",
        "outputId": "fce87e05-c0b5-4360-b7ae-d0bcb95ececb"
      },
      "source": [
        "corr_c_g = dados_c_g.corr()\n",
        "corr = corr_c_g.loc[:'g_49','c_0':]\n",
        "corr.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>c_0</th>\n",
              "      <th>c_1</th>\n",
              "      <th>c_2</th>\n",
              "      <th>c_3</th>\n",
              "      <th>c_4</th>\n",
              "      <th>c_5</th>\n",
              "      <th>c_6</th>\n",
              "      <th>c_7</th>\n",
              "      <th>c_8</th>\n",
              "      <th>c_9</th>\n",
              "      <th>c_10</th>\n",
              "      <th>c_11</th>\n",
              "      <th>c_12</th>\n",
              "      <th>c_13</th>\n",
              "      <th>c_14</th>\n",
              "      <th>c_15</th>\n",
              "      <th>c_16</th>\n",
              "      <th>c_17</th>\n",
              "      <th>c_18</th>\n",
              "      <th>c_19</th>\n",
              "      <th>c_20</th>\n",
              "      <th>c_21</th>\n",
              "      <th>c_22</th>\n",
              "      <th>c_23</th>\n",
              "      <th>c_24</th>\n",
              "      <th>c_25</th>\n",
              "      <th>c_26</th>\n",
              "      <th>c_27</th>\n",
              "      <th>c_28</th>\n",
              "      <th>c_29</th>\n",
              "      <th>c_30</th>\n",
              "      <th>c_31</th>\n",
              "      <th>c_32</th>\n",
              "      <th>c_33</th>\n",
              "      <th>c_34</th>\n",
              "      <th>c_35</th>\n",
              "      <th>c_36</th>\n",
              "      <th>c_37</th>\n",
              "      <th>c_38</th>\n",
              "      <th>c_39</th>\n",
              "      <th>c_40</th>\n",
              "      <th>c_41</th>\n",
              "      <th>c_42</th>\n",
              "      <th>c_43</th>\n",
              "      <th>c_44</th>\n",
              "      <th>c_45</th>\n",
              "      <th>c_46</th>\n",
              "      <th>c_47</th>\n",
              "      <th>c_48</th>\n",
              "      <th>c_49</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>g_0</th>\n",
              "      <td>-0.624116</td>\n",
              "      <td>-0.624810</td>\n",
              "      <td>-0.639789</td>\n",
              "      <td>-0.604041</td>\n",
              "      <td>-0.606231</td>\n",
              "      <td>-0.629189</td>\n",
              "      <td>-0.669697</td>\n",
              "      <td>-0.608954</td>\n",
              "      <td>-0.642211</td>\n",
              "      <td>-0.630989</td>\n",
              "      <td>-0.626020</td>\n",
              "      <td>-0.631486</td>\n",
              "      <td>-0.629841</td>\n",
              "      <td>-0.643529</td>\n",
              "      <td>-0.622502</td>\n",
              "      <td>-0.647751</td>\n",
              "      <td>-0.638829</td>\n",
              "      <td>-0.678957</td>\n",
              "      <td>-0.594877</td>\n",
              "      <td>-0.643239</td>\n",
              "      <td>-0.684132</td>\n",
              "      <td>-0.630950</td>\n",
              "      <td>-0.543857</td>\n",
              "      <td>-0.579103</td>\n",
              "      <td>-0.660192</td>\n",
              "      <td>-0.605740</td>\n",
              "      <td>-0.620731</td>\n",
              "      <td>-0.661781</td>\n",
              "      <td>-0.647510</td>\n",
              "      <td>-0.615229</td>\n",
              "      <td>-0.653816</td>\n",
              "      <td>-0.659935</td>\n",
              "      <td>-0.646008</td>\n",
              "      <td>-0.656088</td>\n",
              "      <td>-0.649368</td>\n",
              "      <td>-0.639943</td>\n",
              "      <td>-0.606850</td>\n",
              "      <td>-0.565831</td>\n",
              "      <td>-0.627974</td>\n",
              "      <td>-0.645185</td>\n",
              "      <td>-0.617530</td>\n",
              "      <td>-0.646511</td>\n",
              "      <td>-0.654105</td>\n",
              "      <td>-0.619767</td>\n",
              "      <td>-0.655768</td>\n",
              "      <td>-0.652930</td>\n",
              "      <td>-0.601610</td>\n",
              "      <td>-0.652579</td>\n",
              "      <td>-0.595291</td>\n",
              "      <td>-0.609109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_1</th>\n",
              "      <td>-0.037405</td>\n",
              "      <td>-0.030558</td>\n",
              "      <td>-0.039616</td>\n",
              "      <td>0.011899</td>\n",
              "      <td>-0.027014</td>\n",
              "      <td>-0.004664</td>\n",
              "      <td>-0.027941</td>\n",
              "      <td>-0.003155</td>\n",
              "      <td>-0.016199</td>\n",
              "      <td>0.012004</td>\n",
              "      <td>-0.011896</td>\n",
              "      <td>-0.028692</td>\n",
              "      <td>-0.016804</td>\n",
              "      <td>-0.039030</td>\n",
              "      <td>-0.018724</td>\n",
              "      <td>0.001283</td>\n",
              "      <td>-0.020506</td>\n",
              "      <td>-0.028191</td>\n",
              "      <td>-0.006079</td>\n",
              "      <td>-0.004661</td>\n",
              "      <td>-0.009059</td>\n",
              "      <td>-0.013806</td>\n",
              "      <td>0.052851</td>\n",
              "      <td>0.019902</td>\n",
              "      <td>-0.015551</td>\n",
              "      <td>0.020494</td>\n",
              "      <td>-0.021502</td>\n",
              "      <td>-0.023190</td>\n",
              "      <td>-0.026067</td>\n",
              "      <td>-0.016824</td>\n",
              "      <td>-0.008202</td>\n",
              "      <td>-0.035886</td>\n",
              "      <td>-0.020831</td>\n",
              "      <td>-0.016770</td>\n",
              "      <td>0.006563</td>\n",
              "      <td>-0.005731</td>\n",
              "      <td>-0.032461</td>\n",
              "      <td>-0.037041</td>\n",
              "      <td>-0.027810</td>\n",
              "      <td>0.001859</td>\n",
              "      <td>-0.033150</td>\n",
              "      <td>-0.013812</td>\n",
              "      <td>0.008141</td>\n",
              "      <td>-0.028824</td>\n",
              "      <td>-0.015203</td>\n",
              "      <td>-0.009619</td>\n",
              "      <td>-0.012841</td>\n",
              "      <td>-0.000760</td>\n",
              "      <td>-0.006228</td>\n",
              "      <td>0.027230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_2</th>\n",
              "      <td>-0.168656</td>\n",
              "      <td>-0.178692</td>\n",
              "      <td>-0.176733</td>\n",
              "      <td>-0.156894</td>\n",
              "      <td>-0.180127</td>\n",
              "      <td>-0.170701</td>\n",
              "      <td>-0.181008</td>\n",
              "      <td>-0.175473</td>\n",
              "      <td>-0.178634</td>\n",
              "      <td>-0.163261</td>\n",
              "      <td>-0.180958</td>\n",
              "      <td>-0.176356</td>\n",
              "      <td>-0.180042</td>\n",
              "      <td>-0.183370</td>\n",
              "      <td>-0.174772</td>\n",
              "      <td>-0.180545</td>\n",
              "      <td>-0.162327</td>\n",
              "      <td>-0.177785</td>\n",
              "      <td>-0.169176</td>\n",
              "      <td>-0.170238</td>\n",
              "      <td>-0.182883</td>\n",
              "      <td>-0.172854</td>\n",
              "      <td>-0.137744</td>\n",
              "      <td>-0.193688</td>\n",
              "      <td>-0.170649</td>\n",
              "      <td>-0.171545</td>\n",
              "      <td>-0.179031</td>\n",
              "      <td>-0.184632</td>\n",
              "      <td>-0.162529</td>\n",
              "      <td>-0.166055</td>\n",
              "      <td>-0.177225</td>\n",
              "      <td>-0.185423</td>\n",
              "      <td>-0.184273</td>\n",
              "      <td>-0.187304</td>\n",
              "      <td>-0.173426</td>\n",
              "      <td>-0.187504</td>\n",
              "      <td>-0.160625</td>\n",
              "      <td>-0.160252</td>\n",
              "      <td>-0.181268</td>\n",
              "      <td>-0.183121</td>\n",
              "      <td>-0.180550</td>\n",
              "      <td>-0.175385</td>\n",
              "      <td>-0.193517</td>\n",
              "      <td>-0.167275</td>\n",
              "      <td>-0.187155</td>\n",
              "      <td>-0.178427</td>\n",
              "      <td>-0.166280</td>\n",
              "      <td>-0.174605</td>\n",
              "      <td>-0.160305</td>\n",
              "      <td>-0.167884</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_3</th>\n",
              "      <td>-0.037342</td>\n",
              "      <td>-0.093505</td>\n",
              "      <td>-0.085298</td>\n",
              "      <td>-0.029079</td>\n",
              "      <td>-0.065964</td>\n",
              "      <td>-0.054947</td>\n",
              "      <td>-0.118651</td>\n",
              "      <td>-0.031232</td>\n",
              "      <td>-0.060544</td>\n",
              "      <td>-0.098435</td>\n",
              "      <td>-0.056865</td>\n",
              "      <td>-0.072926</td>\n",
              "      <td>-0.081498</td>\n",
              "      <td>-0.078792</td>\n",
              "      <td>-0.072001</td>\n",
              "      <td>-0.041614</td>\n",
              "      <td>-0.057309</td>\n",
              "      <td>-0.085462</td>\n",
              "      <td>-0.064829</td>\n",
              "      <td>-0.025428</td>\n",
              "      <td>-0.069663</td>\n",
              "      <td>-0.070663</td>\n",
              "      <td>0.070106</td>\n",
              "      <td>-0.001622</td>\n",
              "      <td>-0.060156</td>\n",
              "      <td>-0.007329</td>\n",
              "      <td>-0.108669</td>\n",
              "      <td>-0.068180</td>\n",
              "      <td>-0.084874</td>\n",
              "      <td>-0.038126</td>\n",
              "      <td>-0.057558</td>\n",
              "      <td>-0.096243</td>\n",
              "      <td>-0.040765</td>\n",
              "      <td>-0.091024</td>\n",
              "      <td>-0.042440</td>\n",
              "      <td>-0.048595</td>\n",
              "      <td>-0.077177</td>\n",
              "      <td>-0.033611</td>\n",
              "      <td>-0.101452</td>\n",
              "      <td>-0.028037</td>\n",
              "      <td>-0.085204</td>\n",
              "      <td>-0.045566</td>\n",
              "      <td>-0.067272</td>\n",
              "      <td>-0.067388</td>\n",
              "      <td>-0.062907</td>\n",
              "      <td>-0.073044</td>\n",
              "      <td>-0.031620</td>\n",
              "      <td>-0.068848</td>\n",
              "      <td>-0.058527</td>\n",
              "      <td>-0.033818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g_4</th>\n",
              "      <td>-0.403545</td>\n",
              "      <td>-0.379840</td>\n",
              "      <td>-0.392841</td>\n",
              "      <td>-0.357850</td>\n",
              "      <td>-0.365118</td>\n",
              "      <td>-0.384914</td>\n",
              "      <td>-0.364633</td>\n",
              "      <td>-0.378776</td>\n",
              "      <td>-0.383263</td>\n",
              "      <td>-0.346834</td>\n",
              "      <td>-0.379019</td>\n",
              "      <td>-0.384599</td>\n",
              "      <td>-0.379915</td>\n",
              "      <td>-0.389980</td>\n",
              "      <td>-0.395484</td>\n",
              "      <td>-0.382739</td>\n",
              "      <td>-0.387586</td>\n",
              "      <td>-0.390418</td>\n",
              "      <td>-0.342299</td>\n",
              "      <td>-0.394375</td>\n",
              "      <td>-0.404137</td>\n",
              "      <td>-0.378579</td>\n",
              "      <td>-0.319028</td>\n",
              "      <td>-0.351363</td>\n",
              "      <td>-0.393502</td>\n",
              "      <td>-0.372542</td>\n",
              "      <td>-0.357408</td>\n",
              "      <td>-0.406761</td>\n",
              "      <td>-0.382014</td>\n",
              "      <td>-0.381405</td>\n",
              "      <td>-0.376348</td>\n",
              "      <td>-0.390938</td>\n",
              "      <td>-0.415720</td>\n",
              "      <td>-0.369416</td>\n",
              "      <td>-0.393812</td>\n",
              "      <td>-0.380305</td>\n",
              "      <td>-0.385241</td>\n",
              "      <td>-0.360443</td>\n",
              "      <td>-0.365057</td>\n",
              "      <td>-0.386042</td>\n",
              "      <td>-0.382110</td>\n",
              "      <td>-0.387299</td>\n",
              "      <td>-0.356774</td>\n",
              "      <td>-0.392748</td>\n",
              "      <td>-0.388367</td>\n",
              "      <td>-0.389456</td>\n",
              "      <td>-0.355117</td>\n",
              "      <td>-0.393260</td>\n",
              "      <td>-0.349730</td>\n",
              "      <td>-0.349804</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          c_0       c_1       c_2  ...      c_47      c_48      c_49\n",
              "g_0 -0.624116 -0.624810 -0.639789  ... -0.652579 -0.595291 -0.609109\n",
              "g_1 -0.037405 -0.030558 -0.039616  ... -0.000760 -0.006228  0.027230\n",
              "g_2 -0.168656 -0.178692 -0.176733  ... -0.174605 -0.160305 -0.167884\n",
              "g_3 -0.037342 -0.093505 -0.085298  ... -0.068848 -0.058527 -0.033818\n",
              "g_4 -0.403545 -0.379840 -0.392841  ... -0.393260 -0.349730 -0.349804\n",
              "\n",
              "[5 rows x 50 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J1QaYFv1UOMo"
      },
      "source": [
        "### Resposta 06\n",
        "#### Estudar o código que plota a matriz de correlação (heatmap)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 529
        },
        "id": "r61SxcbCznDb",
        "outputId": "8c278590-c0bc-4265-cd0d-0c4739ee6f5c"
      },
      "source": [
        "# Generate a mask for the upper triangle\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "\n",
        "# Set up the matplotlib figure\n",
        "f, ax = plt.subplots(figsize=(10, 10))\n",
        "\n",
        "# Generate a custom diverging colormap\n",
        "cmap = sns.diverging_palette(20, 230, as_cmap=True)\n",
        "\n",
        "# Draw the heatmap with the mask and correct aspect ratio\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, center=0,\n",
        "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc74478cb50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "thgMC3Gfcore"
      },
      "source": [
        "### Resposta 07\n",
        "#### Resumo do que você aprendeu com os dados\n",
        "\n",
        "1. Ainda falta muito conhecimento para interpretar os gráficos.\n",
        "2. Algumas operações ainda são alienígenas pra mim. O comando melt é extremamente interessante e faz de forma eficiente a arrumação dos dados que uso no dia-a-dia.\n",
        "3. A matriz de correlação é sensacional, mas acredito que possa ser melhor aproveitada em outro contexto.\n",
        "\n"
      ]
    }
  ]
}