Imersão_Dados_Alura_Aula_02.ipynb

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      "name": "Imersão Dados - Alura - Aula_02.ipynb",
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    {
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      "metadata": {
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      "source": [
        "<a href=\"https://colab.research.google.com/github/LuizJoca/Imers-o-Dados-Alura/blob/main/Imers%C3%A3o_Dados_Alura_Aula_02.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "87yE0HvTNY6u"
      },
      "source": [
        "#Aula 02"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xFXfW7vFvfK-"
      },
      "source": [
        "Olá!\n",
        "\n",
        "Seja bem vindo e bem vinda a aula 02!\n",
        "\n",
        "Na aula 01, nós começamos a explorar um conjunto de dados relacionados à industria farmacêutica. Para isso nós utilizamos uma biblioteca muito conhecida no mundo de DataScience: o Pandas.\n",
        "\n",
        "Nós utilizamos o Pandas para abrir o dataset, que estava no formato CSV, e para gerar um dataframe, uma tabela, para então começarmos a analisar e entender o que significava cada coluna. Com a ajuda da Vanessa, especialista na área, identificamos que temos colunas que nos remetem a dados que estão sob tratamento(droga) e com controle. Além disso, temos também diversas colunas que remetem aos genes.\n",
        "\n",
        "Começamos nossa análise olhando para cada coluna de forma separada e também geramos gráficos, para auxiliar nossa análise.\n",
        "\n",
        "E você? Como se saiu na resolução dos desafios?\n",
        "\n",
        "Agora, vamos mergulhar juntos na aula 02!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
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        "id": "Ha42O_qGWtzN",
        "outputId": "14764cd1-d31c-4746-f061-8d2181f60420"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "\n",
        "dados = pd.read_csv(url_dados, compression = 'zip')\n",
        "dados"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "hB3O-zZW9ZYw",
        "outputId": "a60b5289-cc5d-4d29-cb8e-ab99ceb9a476"
      },
      "source": [
        "dados"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGB4Kq8JvmZ5"
      },
      "source": [
        "A base de dados que usamos até o momento tem uma variável chamada ```composto```mas entendemos, com a ajuda da Vanessa, que essa não é a melhor nomenclatura para representa-la. \n",
        "Por isso, vamos usar a função ```map``` da biblioteca Pandas para renomear essa coluna.\n",
        "É importante destacar que passamos o parâmetro ```inplace = True```, esse parâmetro faz com que os dados sejam modificados no local e o dataframe será atualizado. \n",
        "Caso esse parâmetro não seja declarado, o default é ```inplace = False``` e o retorno será uma cópia do objeto e caso você queira, precisa salva-lo com um outro nome."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CFse2h0Vcrp4"
      },
      "source": [
        "mapa = {'droga': 'composto'}\n",
        "dados.rename(columns=mapa, inplace=True)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lq5EDpC4w_rS"
      },
      "source": [
        "Aqui, estamos usando a função ```head``` para apresentar as 5 primeiras linhas da base de dados e assim, podemos conferir se a renomeação aconteceu da maneira que estavámos esperando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 243
        },
        "id": "VX73K_tLcoQg",
        "outputId": "1081b0e7-21a3-4d7f-e0b3-5c0ea0744798"
      },
      "source": [
        "dados.head()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<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",
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              "      <th>g-26</th>\n",
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              "      <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",
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              "      <td>-0.2853</td>\n",
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              "      <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",
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              "      <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",
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              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
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              "      <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": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i7mgnrykiMNb"
      },
      "source": [
        "Queremos melhorar a visualização do nosso histograma de compostos e, como existem mais de 3.000 variações na nossa base de dados, decidimos elencar os 5 compostos que mais aparecem.\n",
        "Para isso, vamos usar a função ```value_counts``` (função presente na biblioteca Pandas e que conta a ocorrência dos diferentes valores) e, como queremos saber somente os 5 elementos mais frequentes, também declaramos o ```index[0:5]```. Essa parte final, faz com que o ```value_counts```se atenha à contagem dos maiores valores e apresente como resultado apenas o index do  intervalo [0, 5[, ou seja, o nome dos 5 maiores valores. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D5hK5mcVej_G"
      },
      "source": [
        "cod_compostos = dados['composto'].value_counts().index[0:5]"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hrOGPnbP4cE_"
      },
      "source": [
        "Na célula acima, declaramos a variável ```cod_compostos``` e definimos a função que está atrelada à ela. \n",
        "E agora, executamos a nossa nova variável para verificar o resultado."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LgrRw3eSfLYu",
        "outputId": "73d9d558-2ab6-4f58-8700-89b663a708be"
      },
      "source": [
        "cod_compostos"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1JANbNGx4wQO"
      },
      "source": [
        "Exitem algumas maneiras de filtrar uma base de dados e optamos em usar a função ```query``` do Pandas e, somente a título de curiosidade, essa função é bastante análoga ao SQL (linguagem de programação para bancos de dados).\n",
        "A estrutura dela é bastante simplificada, precisamos apenas definir o dataframe, chamar a função e passar como parâmetro a condição que deve ser \n",
        "filtrada no nosso conjunto de dados.\n",
        "\n",
        "Nesta parte do projeto, queremos realizar um filtro em nossos dados, selecionando apenas as linhas nas quais o composto esteja dentro da nossa lista ```cod_composto``` (lista que representa os 5 compostos mais testados no experimento) e vamos utilizar o método ```query``` para resolver este problema. \n",
        "\n",
        "Como parâmetro da função, passamos uma string contendo a lógica para realização da seleção dos dados. O que queremos é o seguinte: o ```query```precisa retornar para nós todas as linhas contendo os 5 compostos mais utilizados. Logo, a string necessária para isso é: ```composto in @cod_compostos```. \n",
        "\n",
        "Usamos ```composto``` porque essa é a coluna a ser verificada no dataframe e ```cod_compostos``` por ser a lista com os top 5 compostos, o detalhe aqui é que o ```@``` é necessário para informar o ```query``` que ```cod_composto``` é uma variável que já foi definida fora da função."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "_GlSwTMGfpFs",
        "outputId": "9c502a32-7341-4969-fc7e-4ac31600ac06"
      },
      "source": [
        "dados.query('composto in @cod_compostos')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>id_002fb9c19</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>8.7380</td>\n",
              "      <td>0.1914</td>\n",
              "      <td>2.4380</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>3.2010</td>\n",
              "      <td>1.4910</td>\n",
              "      <td>5.3920</td>\n",
              "      <td>-1.0420</td>\n",
              "      <td>-8.4860</td>\n",
              "      <td>-2.5790</td>\n",
              "      <td>-6.7470</td>\n",
              "      <td>3.6150</td>\n",
              "      <td>-1.4510</td>\n",
              "      <td>0.6909</td>\n",
              "      <td>-0.7623</td>\n",
              "      <td>-2.9400</td>\n",
              "      <td>-9.2850</td>\n",
              "      <td>-6.7110</td>\n",
              "      <td>-0.4195</td>\n",
              "      <td>1.1600</td>\n",
              "      <td>-1.3180</td>\n",
              "      <td>1.3660</td>\n",
              "      <td>-1.4020</td>\n",
              "      <td>-2.6220</td>\n",
              "      <td>0.7204</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-4.0630</td>\n",
              "      <td>-0.8282</td>\n",
              "      <td>-3.5000</td>\n",
              "      <td>0.9206</td>\n",
              "      <td>-5.1450</td>\n",
              "      <td>9.8040</td>\n",
              "      <td>-2.6840</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>-0.1427</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-9.5910</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.8870</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-4.9020</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-5.5520</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.7960</td>\n",
              "      <td>-8.1770</td>\n",
              "      <td>-9.8990</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-6.7840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23793</th>\n",
              "      <td>id_ffd26f361</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.6008</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>-0.3319</td>\n",
              "      <td>-0.8782</td>\n",
              "      <td>0.9281</td>\n",
              "      <td>0.7535</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>1.6350</td>\n",
              "      <td>-0.3146</td>\n",
              "      <td>0.4984</td>\n",
              "      <td>-1.1890</td>\n",
              "      <td>0.3772</td>\n",
              "      <td>-0.8196</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-2.0350</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.7586</td>\n",
              "      <td>-0.4024</td>\n",
              "      <td>-0.0449</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.2358</td>\n",
              "      <td>0.7919</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>0.4232</td>\n",
              "      <td>1.8460</td>\n",
              "      <td>-2.0940</td>\n",
              "      <td>0.1438</td>\n",
              "      <td>-0.6604</td>\n",
              "      <td>0.7243</td>\n",
              "      <td>0.0338</td>\n",
              "      <td>-0.0182</td>\n",
              "      <td>-0.2022</td>\n",
              "      <td>0.8827</td>\n",
              "      <td>0.3147</td>\n",
              "      <td>-0.9263</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1934</td>\n",
              "      <td>1.2240</td>\n",
              "      <td>-0.1178</td>\n",
              "      <td>0.1459</td>\n",
              "      <td>-0.1242</td>\n",
              "      <td>0.3106</td>\n",
              "      <td>-0.7959</td>\n",
              "      <td>0.5681</td>\n",
              "      <td>0.3663</td>\n",
              "      <td>0.4874</td>\n",
              "      <td>-0.0548</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>1.3470</td>\n",
              "      <td>1.6210</td>\n",
              "      <td>-0.8260</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>0.3264</td>\n",
              "      <td>0.9241</td>\n",
              "      <td>0.3012</td>\n",
              "      <td>1.2980</td>\n",
              "      <td>-0.2789</td>\n",
              "      <td>0.7019</td>\n",
              "      <td>-0.3528</td>\n",
              "      <td>0.7383</td>\n",
              "      <td>1.0300</td>\n",
              "      <td>0.6527</td>\n",
              "      <td>1.6750</td>\n",
              "      <td>-0.5046</td>\n",
              "      <td>0.2942</td>\n",
              "      <td>0.2950</td>\n",
              "      <td>1.2470</td>\n",
              "      <td>0.9569</td>\n",
              "      <td>-0.2065</td>\n",
              "      <td>-0.4918</td>\n",
              "      <td>0.7863</td>\n",
              "      <td>0.0504</td>\n",
              "      <td>0.8813</td>\n",
              "      <td>0.7757</td>\n",
              "      <td>-0.5272</td>\n",
              "      <td>0.7082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23802</th>\n",
              "      <td>id_fff3976bd</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>3.2890</td>\n",
              "      <td>2.1270</td>\n",
              "      <td>0.9770</td>\n",
              "      <td>2.0490</td>\n",
              "      <td>2.3170</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>-0.6357</td>\n",
              "      <td>-6.9060</td>\n",
              "      <td>-4.4830</td>\n",
              "      <td>-2.8400</td>\n",
              "      <td>-5.3310</td>\n",
              "      <td>0.6547</td>\n",
              "      <td>-2.2080</td>\n",
              "      <td>3.6030</td>\n",
              "      <td>0.6380</td>\n",
              "      <td>-2.1280</td>\n",
              "      <td>-3.1680</td>\n",
              "      <td>-4.2180</td>\n",
              "      <td>-0.3170</td>\n",
              "      <td>0.2140</td>\n",
              "      <td>-1.7660</td>\n",
              "      <td>-1.9700</td>\n",
              "      <td>-1.4820</td>\n",
              "      <td>-1.3710</td>\n",
              "      <td>-0.2628</td>\n",
              "      <td>-0.5276</td>\n",
              "      <td>-2.4160</td>\n",
              "      <td>-0.4638</td>\n",
              "      <td>-3.8630</td>\n",
              "      <td>-0.8880</td>\n",
              "      <td>-1.9850</td>\n",
              "      <td>2.0530</td>\n",
              "      <td>-1.4700</td>\n",
              "      <td>-3.3220</td>\n",
              "      <td>1.8800</td>\n",
              "      <td>...</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.0200</td>\n",
              "      <td>-6.7560</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.1240</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-5.7500</td>\n",
              "      <td>-8.4760</td>\n",
              "      <td>-6.9470</td>\n",
              "      <td>-4.7650</td>\n",
              "      <td>-9.7690</td>\n",
              "      <td>-5.7900</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-5.7450</td>\n",
              "      <td>-2.3570</td>\n",
              "      <td>-9.1190</td>\n",
              "      <td>-4.5980</td>\n",
              "      <td>-8.7760</td>\n",
              "      <td>-7.7980</td>\n",
              "      <td>-4.1620</td>\n",
              "      <td>-6.1510</td>\n",
              "      <td>-5.7400</td>\n",
              "      <td>-6.8700</td>\n",
              "      <td>-9.1000</td>\n",
              "      <td>-3.3360</td>\n",
              "      <td>-6.6420</td>\n",
              "      <td>-2.2750</td>\n",
              "      <td>-3.4720</td>\n",
              "      <td>-6.2670</td>\n",
              "      <td>-6.3980</td>\n",
              "      <td>-8.6300</td>\n",
              "      <td>-8.1490</td>\n",
              "      <td>-6.2900</td>\n",
              "      <td>-8.0970</td>\n",
              "      <td>-8.7330</td>\n",
              "      <td>-2.3780</td>\n",
              "      <td>-8.4480</td>\n",
              "      <td>-4.4550</td>\n",
              "      <td>-5.7930</td>\n",
              "      <td>-3.7000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23805</th>\n",
              "      <td>id_fff6df1c5</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>5628cb3ee</td>\n",
              "      <td>1.7380</td>\n",
              "      <td>-1.2900</td>\n",
              "      <td>-0.4533</td>\n",
              "      <td>-1.1640</td>\n",
              "      <td>-0.4841</td>\n",
              "      <td>-0.2392</td>\n",
              "      <td>-0.1774</td>\n",
              "      <td>-1.3980</td>\n",
              "      <td>-0.4059</td>\n",
              "      <td>0.1553</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-0.8020</td>\n",
              "      <td>-0.5039</td>\n",
              "      <td>-0.7167</td>\n",
              "      <td>-0.5016</td>\n",
              "      <td>-0.9369</td>\n",
              "      <td>-0.5864</td>\n",
              "      <td>-0.1009</td>\n",
              "      <td>0.8987</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>-1.3460</td>\n",
              "      <td>-0.5087</td>\n",
              "      <td>-0.0892</td>\n",
              "      <td>-0.6559</td>\n",
              "      <td>0.0864</td>\n",
              "      <td>-0.6251</td>\n",
              "      <td>0.2471</td>\n",
              "      <td>-0.4523</td>\n",
              "      <td>-0.0389</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.0796</td>\n",
              "      <td>-0.2560</td>\n",
              "      <td>-0.7851</td>\n",
              "      <td>-0.1687</td>\n",
              "      <td>-1.2890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2866</td>\n",
              "      <td>0.3854</td>\n",
              "      <td>-0.4986</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.5843</td>\n",
              "      <td>0.0907</td>\n",
              "      <td>-0.9303</td>\n",
              "      <td>0.1981</td>\n",
              "      <td>0.6515</td>\n",
              "      <td>0.2877</td>\n",
              "      <td>0.4389</td>\n",
              "      <td>-0.3859</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>-1.1070</td>\n",
              "      <td>2.3870</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-0.6434</td>\n",
              "      <td>-0.9722</td>\n",
              "      <td>-0.4200</td>\n",
              "      <td>-0.5693</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>-0.5117</td>\n",
              "      <td>-1.2130</td>\n",
              "      <td>0.3769</td>\n",
              "      <td>0.5296</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>1.0150</td>\n",
              "      <td>-0.7669</td>\n",
              "      <td>0.2865</td>\n",
              "      <td>0.5974</td>\n",
              "      <td>-0.2727</td>\n",
              "      <td>0.1188</td>\n",
              "      <td>1.0770</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>0.1516</td>\n",
              "      <td>0.4503</td>\n",
              "      <td>-0.6312</td>\n",
              "      <td>-0.8302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3235 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n",
              "25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n",
              "23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n",
              "23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "\n",
              "[3235 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p9FQo1EuFF8M"
      },
      "source": [
        "Agora que vimos que a nossa filtragem funcionou e que temos como retorno uma base de dados com 3.235 linhas, podemos usar a função ```query```como parâmetro para o ```countplot```, o nosso gráfico de barras.\n",
        "O ```countplot``` é um gráfico pré-programado da biblioteca ```Seaborn```e, por isso, precisaremos fazer a importação padrão da mesma (```import seaborn as sns```). Adicionalmente, aqui no Google Colaboratory, para que possamos enxergar o gráfico com os padrões de configuração da biblioteca, precisamos rodar ```sns.set()```.\n",
        "Além disso, para refinar a apresentação do gráfico, podemos utilizar algumas funcionalidades da biblioteca ```Matplotlib``` (fazendo, primeiramente, sua importação - ```import matplotlib.pyplt as plt```).\n",
        "Também estamos definindo o tamanho do gráfico através da função ```figure``` e seu parâmetro ```figsize=(x, y))``` e o título através do ```set_title('Título')```.\n",
        "Como comentado na aula, usualmente, armazenamos o nosso gráfico em uma variável ```ax``` e então, definimos as demais configurações (por exemplo, ```ax.set_title('Título')```.\n",
        "E, finalmente, para visualizar o gráfico de barras, usamos o ```plt.show()```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        },
        "id": "IePUr98kdgED",
        "outputId": "c238d326-41d3-46f8-b33f-ac65320aff00"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "sns.set()\n",
        "plt.figure(figsize=(10, 8))\n",
        "ax = sns.countplot(x = 'composto', data=dados.query('composto in @cod_compostos'))\n",
        "ax.set_title('Top 5 compostos')\n",
        "plt.show()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bA_RUClHM6I8"
      },
      "source": [
        "Até o momento analisamos os dados de tempo, dose, compostos e afins. Entretanto, não analisamos os dados de expressões gênicas (G's) e viabilidade celular (C's). Será que podemos criar um gráfico de barras para esses dados?\n",
        "Vamos pensar que a nossa base de dados apresenta mais de 3.000 compostos. Mas quantos desses compostos aparecem na coluna ```g-0```? \n",
        "Para responder essa questão, vamos usar a função ```unique()``` do Pandas que conta os valores únicos presentes na coluna em questão. Como resposta padrão, o retorno será uma lista com arrays (os nomes dos compostos) mas, nosso objetivo é saber o tamanho dessa lista e, por isso, usamos o ```len```, pois assim, ele contará o tamanho desta lista de arrays."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DkQ2wH9Gj-w7",
        "outputId": "2abfe103-7199-4e96-f9eb-9d229b6cf32b"
      },
      "source": [
        "len(dados['g-0'].unique())"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14367"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wM4yn28tRflX"
      },
      "source": [
        "Como temos diversos compostos únicos dentro da coluna ```g-0```, não é viável que façamos o mesmo gráfico utilizado anteriormente. \n",
        "Por isso, precisamos traçar uma nova estratégia para visualizar os nossos dadose aqui, usaremos um histograma.\n",
        "O primeiro passo, é identificar qual o valor mínimo (```min()```) e o valor máximo (```max()```) para entender qual o intervalo númerico com o qual estamos trabalhando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mCC5DpK1kmiX",
        "outputId": "388669ea-0b94-4b43-d562-bc23107088a9"
      },
      "source": [
        "dados['g-0'].min()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-5.513"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qzH4Jl0OksuL",
        "outputId": "840787d0-9a72-4ea4-d863-f16c54549112"
      },
      "source": [
        "dados['g-0'].max()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-Tp7M_wWUCU8"
      },
      "source": [
        "Depois que reconhecemos que o nosso intervalo vai de ~5,5 a 10,0, podemos partir para o histograma e a função que usaremos para plotar é do Pandas (```dataframe['variável'].hist()```).\n",
        "Assim que rodamos essa função, percebemos que a visualização destes dados ainda não está boa pois, a divisão padrão das barras do histograma, representam intervalos muito grandes que atrapalham o entendimento dos dados.\n",
        "Por isso, acresentamos um parâmetro dentro da função ```(bins = número de quebras)``` para melhor dividir e, consequentemente visualizar os dados.\n",
        "Quando definimos os bins em 100, podemos perceber que a forma se aproxima bastante de uma curva bastante conhecida: a curva normal."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "RnjRPpubk1z0",
        "outputId": "60f94bad-cd61-4b06-aeef-c79d245a49b0"
      },
      "source": [
        "dados['g-0'].hist(bins = 100)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bf170b50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ILTZmvd2fczV"
      },
      "source": [
        "Aqui, estamos testando o mesmo histograma para outro gene, o ```g-19```. E queremos fazer uma comparação entre os gráficos e podemos fazer algumas considerações sobre ambos os gráficos.\n",
        "Percebemos, por exemplo, que a imagem seguem a mesma tendência de curva mas há um deslocamento para a direita."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "1_aedkvToYlB",
        "outputId": "1fb80d8d-3a09-4433-e220-fe35cf995a41"
      },
      "source": [
        "dados['g-19'].hist(bins = 100)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bf12b350>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i8HZHcicEJ0F"
      },
      "source": [
        "Como concluimos que plotar os gráficos de todos os genes é inviável, vamos analisar resumidamente algumas estatísticas sobre eles. \n",
        "Para isso, vamos usar a função ```describe``` do Pandas que já calcula e descreve algumas estatísticas importantes para o entendimento dos dados (contagem, média, desvio padrão, mínimo, alguns quartis e máximo).\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "id": "Kv-2zPLBprgD",
        "outputId": "9968a9fc-9780-4ded-fc89-22f1caad14b0"
      },
      "source": [
        "dados.describe()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tempo</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.020156</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.517397</td>\n",
              "      <td>-0.360770</td>\n",
              "      <td>-0.435752</td>\n",
              "      <td>-0.613591</td>\n",
              "      <td>-0.402083</td>\n",
              "      <td>-0.619682</td>\n",
              "      <td>-0.452265</td>\n",
              "      <td>-0.497164</td>\n",
              "      <td>-0.413836</td>\n",
              "      <td>-0.277029</td>\n",
              "      <td>-0.547845</td>\n",
              "      <td>-0.358611</td>\n",
              "      <td>-0.442906</td>\n",
              "      <td>-0.475194</td>\n",
              "      <td>-0.010404</td>\n",
              "      <td>-0.467001</td>\n",
              "      <td>-0.276963</td>\n",
              "      <td>-0.455848</td>\n",
              "      <td>-0.412918</td>\n",
              "      <td>-0.456404</td>\n",
              "      <td>-0.472514</td>\n",
              "      <td>-0.505481</td>\n",
              "      <td>-0.492735</td>\n",
              "      <td>-0.446836</td>\n",
              "      <td>-0.463029</td>\n",
              "      <td>-0.409310</td>\n",
              "      <td>-0.333124</td>\n",
              "      <td>-0.295009</td>\n",
              "      <td>-0.328342</td>\n",
              "      <td>-0.401615</td>\n",
              "      <td>-0.469244</td>\n",
              "      <td>-0.461411</td>\n",
              "      <td>-0.513256</td>\n",
              "      <td>-0.500142</td>\n",
              "      <td>-0.507093</td>\n",
              "      <td>-0.353726</td>\n",
              "      <td>-0.463485</td>\n",
              "      <td>-0.378241</td>\n",
              "      <td>-0.470252</td>\n",
              "      <td>-0.301505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>19.402807</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>...</td>\n",
              "      <td>2.122318</td>\n",
              "      <td>1.710725</td>\n",
              "      <td>1.898871</td>\n",
              "      <td>2.307820</td>\n",
              "      <td>1.785055</td>\n",
              "      <td>2.225596</td>\n",
              "      <td>1.991021</td>\n",
              "      <td>2.063896</td>\n",
              "      <td>1.887001</td>\n",
              "      <td>1.459639</td>\n",
              "      <td>2.187835</td>\n",
              "      <td>1.730634</td>\n",
              "      <td>1.924716</td>\n",
              "      <td>2.021927</td>\n",
              "      <td>1.029820</td>\n",
              "      <td>2.004317</td>\n",
              "      <td>1.429340</td>\n",
              "      <td>1.924263</td>\n",
              "      <td>1.888788</td>\n",
              "      <td>1.832863</td>\n",
              "      <td>2.011396</td>\n",
              "      <td>2.091353</td>\n",
              "      <td>2.055624</td>\n",
              "      <td>1.987476</td>\n",
              "      <td>2.014045</td>\n",
              "      <td>1.883974</td>\n",
              "      <td>1.647241</td>\n",
              "      <td>1.634073</td>\n",
              "      <td>1.663170</td>\n",
              "      <td>1.832794</td>\n",
              "      <td>2.000488</td>\n",
              "      <td>2.042475</td>\n",
              "      <td>2.001714</td>\n",
              "      <td>2.107105</td>\n",
              "      <td>2.159589</td>\n",
              "      <td>1.629291</td>\n",
              "      <td>2.059725</td>\n",
              "      <td>1.703615</td>\n",
              "      <td>1.834828</td>\n",
              "      <td>1.407918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.839000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.452000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.938000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.588075</td>\n",
              "      <td>-0.564025</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.583250</td>\n",
              "      <td>-0.566500</td>\n",
              "      <td>-0.603200</td>\n",
              "      <td>-0.541575</td>\n",
              "      <td>-0.560825</td>\n",
              "      <td>-0.555200</td>\n",
              "      <td>-0.534500</td>\n",
              "      <td>-0.569100</td>\n",
              "      <td>-0.558300</td>\n",
              "      <td>-0.573350</td>\n",
              "      <td>-0.594275</td>\n",
              "      <td>-0.389925</td>\n",
              "      <td>-0.551200</td>\n",
              "      <td>-0.544150</td>\n",
              "      <td>-0.575075</td>\n",
              "      <td>-0.568275</td>\n",
              "      <td>-0.582650</td>\n",
              "      <td>-0.558575</td>\n",
              "      <td>-0.562375</td>\n",
              "      <td>-0.572800</td>\n",
              "      <td>-0.561225</td>\n",
              "      <td>-0.560675</td>\n",
              "      <td>-0.560100</td>\n",
              "      <td>-0.533700</td>\n",
              "      <td>-0.504575</td>\n",
              "      <td>-0.544275</td>\n",
              "      <td>-0.569150</td>\n",
              "      <td>-0.566175</td>\n",
              "      <td>-0.565975</td>\n",
              "      <td>-0.589975</td>\n",
              "      <td>-0.568700</td>\n",
              "      <td>-0.563775</td>\n",
              "      <td>-0.567975</td>\n",
              "      <td>-0.552575</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.592600</td>\n",
              "      <td>-0.562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017650</td>\n",
              "      <td>-0.041550</td>\n",
              "      <td>-0.002950</td>\n",
              "      <td>-0.012650</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.004950</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.023800</td>\n",
              "      <td>-0.011450</td>\n",
              "      <td>-0.007100</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.009300</td>\n",
              "      <td>0.081550</td>\n",
              "      <td>-0.006900</td>\n",
              "      <td>0.018400</td>\n",
              "      <td>-0.014650</td>\n",
              "      <td>-0.014350</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>-0.005300</td>\n",
              "      <td>-0.004050</td>\n",
              "      <td>0.003300</td>\n",
              "      <td>-0.007900</td>\n",
              "      <td>-0.004600</td>\n",
              "      <td>-0.002400</td>\n",
              "      <td>0.007850</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>-0.020600</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>-0.009900</td>\n",
              "      <td>0.003250</td>\n",
              "      <td>-0.009100</td>\n",
              "      <td>-0.013750</td>\n",
              "      <td>-0.003300</td>\n",
              "      <td>-0.010250</td>\n",
              "      <td>-0.001250</td>\n",
              "      <td>-0.006800</td>\n",
              "      <td>0.014000</td>\n",
              "      <td>-0.019500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>...</td>\n",
              "      <td>0.452675</td>\n",
              "      <td>0.427675</td>\n",
              "      <td>0.462175</td>\n",
              "      <td>0.447975</td>\n",
              "      <td>0.447150</td>\n",
              "      <td>0.441250</td>\n",
              "      <td>0.470600</td>\n",
              "      <td>0.458550</td>\n",
              "      <td>0.441000</td>\n",
              "      <td>0.460075</td>\n",
              "      <td>0.460950</td>\n",
              "      <td>0.449975</td>\n",
              "      <td>0.445200</td>\n",
              "      <td>0.473200</td>\n",
              "      <td>0.563575</td>\n",
              "      <td>0.456350</td>\n",
              "      <td>0.493400</td>\n",
              "      <td>0.448375</td>\n",
              "      <td>0.451975</td>\n",
              "      <td>0.463075</td>\n",
              "      <td>0.447675</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.468900</td>\n",
              "      <td>0.452375</td>\n",
              "      <td>0.460475</td>\n",
              "      <td>0.461675</td>\n",
              "      <td>0.465950</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.450075</td>\n",
              "      <td>0.430875</td>\n",
              "      <td>0.457750</td>\n",
              "      <td>0.461500</td>\n",
              "      <td>0.445675</td>\n",
              "      <td>0.452900</td>\n",
              "      <td>0.470900</td>\n",
              "      <td>0.444750</td>\n",
              "      <td>0.465225</td>\n",
              "      <td>0.446400</td>\n",
              "      <td>0.461275</td>\n",
              "      <td>0.438650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>3.888000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>4.857000</td>\n",
              "      <td>3.549000</td>\n",
              "      <td>3.382000</td>\n",
              "      <td>3.328000</td>\n",
              "      <td>4.157000</td>\n",
              "      <td>3.736000</td>\n",
              "      <td>3.582000</td>\n",
              "      <td>3.119000</td>\n",
              "      <td>3.323000</td>\n",
              "      <td>5.014000</td>\n",
              "      <td>2.898000</td>\n",
              "      <td>4.185000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>3.276000</td>\n",
              "      <td>4.992000</td>\n",
              "      <td>3.770000</td>\n",
              "      <td>2.851000</td>\n",
              "      <td>3.211000</td>\n",
              "      <td>4.534000</td>\n",
              "      <td>3.890000</td>\n",
              "      <td>3.994000</td>\n",
              "      <td>4.321000</td>\n",
              "      <td>4.020000</td>\n",
              "      <td>3.738000</td>\n",
              "      <td>3.252000</td>\n",
              "      <td>5.406000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>3.320000</td>\n",
              "      <td>4.069000</td>\n",
              "      <td>3.960000</td>\n",
              "      <td>3.927000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>3.747000</td>\n",
              "      <td>2.814000</td>\n",
              "      <td>3.505000</td>\n",
              "      <td>2.924000</td>\n",
              "      <td>3.111000</td>\n",
              "      <td>3.805000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 873 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              tempo           g-0  ...          c-98          c-99\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean      48.020156      0.248366  ...     -0.470252     -0.301505\n",
              "std       19.402807      1.393399  ...      1.834828      1.407918\n",
              "min       24.000000     -5.513000  ...    -10.000000    -10.000000\n",
              "25%       24.000000     -0.473075  ...     -0.592600     -0.562900\n",
              "50%       48.000000     -0.008850  ...      0.014000     -0.019500\n",
              "75%       72.000000      0.525700  ...      0.461275      0.438650\n",
              "max       72.000000     10.000000  ...      3.111000      3.805000\n",
              "\n",
              "[8 rows x 873 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G4mCKUkUFYhb"
      },
      "source": [
        "Neste ponto, vamos separar as variáveis que queremos analisar da base de dados (exemplo: ```g-0``` e ```g-1```) através de uma lista de arrays.\n",
        "Entretanto, apesar desta ser uma ótima estratégia para a separação, temos 771 genes e escrevê-los um a um seria muito trabalhoso e podemos fazer de uma outra forma."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "id": "OAkjbZdkqPlR",
        "outputId": "1f7cfb30-4c6a-4921-c7e3-b37767d89f96"
      },
      "source": [
        "dados[['g-0', 'g-1']]"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g-0     g-1\n",
              "0      1.0620  0.5577\n",
              "1      0.0743  0.4087\n",
              "2      0.6280  0.5817\n",
              "3     -0.5138 -0.2491\n",
              "4     -0.3254 -0.4009\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.0636\n",
              "23810 -1.3260  0.3478\n",
              "23811  0.3942  0.3756\n",
              "23812  0.6660  0.2324\n",
              "23813 -0.8598  1.0240\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0LHi_9AUGFmS"
      },
      "source": [
        "Uma estratégia mais direta em que não precisaremos escrever a lista gene a gene, é o uso da função ```loc[]``` do Pandas.\n",
        "Como argumentos, passamos primeiramente o ```:```, os dois pontos faz com que o ```loc[]```retorne todos os elementos de uma determinada coluna, isso é importante quando não sabemos qual a quantidade de linhas de um dataframe. E, o segundo elemento, passamos as colunas que são de nosso interesse. No caso, queremos que a função nos retorne todos os elementos das colunas ```g-0```até ```g-771```.\n",
        "E, por fim, podemos declarar a nossa função de interesse a partir deste filtro realizado nos dados, o ```describe()```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "id": "dQX0KOhUqm66",
        "outputId": "9966282b-ee3b-4852-a094-227c3cce5262"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>g-39</th>\n",
              "      <th>...</th>\n",
              "      <th>g-732</th>\n",
              "      <th>g-733</th>\n",
              "      <th>g-734</th>\n",
              "      <th>g-735</th>\n",
              "      <th>g-736</th>\n",
              "      <th>g-737</th>\n",
              "      <th>g-738</th>\n",
              "      <th>g-739</th>\n",
              "      <th>g-740</th>\n",
              "      <th>g-741</th>\n",
              "      <th>g-742</th>\n",
              "      <th>g-743</th>\n",
              "      <th>g-744</th>\n",
              "      <th>g-745</th>\n",
              "      <th>g-746</th>\n",
              "      <th>g-747</th>\n",
              "      <th>g-748</th>\n",
              "      <th>g-749</th>\n",
              "      <th>g-750</th>\n",
              "      <th>g-751</th>\n",
              "      <th>g-752</th>\n",
              "      <th>g-753</th>\n",
              "      <th>g-754</th>\n",
              "      <th>g-755</th>\n",
              "      <th>g-756</th>\n",
              "      <th>g-757</th>\n",
              "      <th>g-758</th>\n",
              "      <th>g-759</th>\n",
              "      <th>g-760</th>\n",
              "      <th>g-761</th>\n",
              "      <th>g-762</th>\n",
              "      <th>g-763</th>\n",
              "      <th>g-764</th>\n",
              "      <th>g-765</th>\n",
              "      <th>g-766</th>\n",
              "      <th>g-767</th>\n",
              "      <th>g-768</th>\n",
              "      <th>g-769</th>\n",
              "      <th>g-770</th>\n",
              "      <th>g-771</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>0.132026</td>\n",
              "      <td>...</td>\n",
              "      <td>0.263569</td>\n",
              "      <td>-0.242638</td>\n",
              "      <td>0.110180</td>\n",
              "      <td>-0.039868</td>\n",
              "      <td>-0.064056</td>\n",
              "      <td>0.193629</td>\n",
              "      <td>0.004470</td>\n",
              "      <td>-0.187085</td>\n",
              "      <td>0.067186</td>\n",
              "      <td>0.006159</td>\n",
              "      <td>-0.201189</td>\n",
              "      <td>-0.243317</td>\n",
              "      <td>0.548903</td>\n",
              "      <td>0.247065</td>\n",
              "      <td>0.085950</td>\n",
              "      <td>0.090544</td>\n",
              "      <td>0.215525</td>\n",
              "      <td>-0.007705</td>\n",
              "      <td>0.236954</td>\n",
              "      <td>0.022785</td>\n",
              "      <td>0.103224</td>\n",
              "      <td>0.048402</td>\n",
              "      <td>0.109367</td>\n",
              "      <td>-0.103262</td>\n",
              "      <td>0.004129</td>\n",
              "      <td>0.066211</td>\n",
              "      <td>0.072773</td>\n",
              "      <td>-0.033051</td>\n",
              "      <td>-0.400643</td>\n",
              "      <td>-0.338978</td>\n",
              "      <td>0.207299</td>\n",
              "      <td>0.009161</td>\n",
              "      <td>0.171027</td>\n",
              "      <td>0.002316</td>\n",
              "      <td>-0.209799</td>\n",
              "      <td>-0.076251</td>\n",
              "      <td>0.134162</td>\n",
              "      <td>-0.128018</td>\n",
              "      <td>-0.219210</td>\n",
              "      <td>0.101524</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>0.990477</td>\n",
              "      <td>...</td>\n",
              "      <td>1.075809</td>\n",
              "      <td>1.309482</td>\n",
              "      <td>0.881283</td>\n",
              "      <td>0.917119</td>\n",
              "      <td>1.186966</td>\n",
              "      <td>1.212621</td>\n",
              "      <td>1.175611</td>\n",
              "      <td>1.182180</td>\n",
              "      <td>1.057292</td>\n",
              "      <td>0.996940</td>\n",
              "      <td>1.029370</td>\n",
              "      <td>1.378815</td>\n",
              "      <td>2.023791</td>\n",
              "      <td>1.639307</td>\n",
              "      <td>1.238753</td>\n",
              "      <td>0.961212</td>\n",
              "      <td>1.293783</td>\n",
              "      <td>0.966213</td>\n",
              "      <td>1.284074</td>\n",
              "      <td>1.015557</td>\n",
              "      <td>1.035968</td>\n",
              "      <td>1.048645</td>\n",
              "      <td>0.856080</td>\n",
              "      <td>1.175372</td>\n",
              "      <td>0.701031</td>\n",
              "      <td>0.996914</td>\n",
              "      <td>1.077310</td>\n",
              "      <td>1.579948</td>\n",
              "      <td>1.913468</td>\n",
              "      <td>1.701554</td>\n",
              "      <td>1.096488</td>\n",
              "      <td>1.200395</td>\n",
              "      <td>1.357701</td>\n",
              "      <td>1.052771</td>\n",
              "      <td>1.201918</td>\n",
              "      <td>1.115477</td>\n",
              "      <td>0.951264</td>\n",
              "      <td>1.230636</td>\n",
              "      <td>1.326193</td>\n",
              "      <td>1.417674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.223000</td>\n",
              "      <td>...</td>\n",
              "      <td>-5.504000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-3.790000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.920000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.462000</td>\n",
              "      <td>-6.634000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.912000</td>\n",
              "      <td>-9.833000</td>\n",
              "      <td>-7.227000</td>\n",
              "      <td>-5.561000</td>\n",
              "      <td>-8.393000</td>\n",
              "      <td>-5.790000</td>\n",
              "      <td>-4.915000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-7.918000</td>\n",
              "      <td>-5.255000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.264000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.505000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.193000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.795000</td>\n",
              "      <td>-8.180000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.269000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>-0.401700</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.390700</td>\n",
              "      <td>-0.565075</td>\n",
              "      <td>-0.433275</td>\n",
              "      <td>-0.498650</td>\n",
              "      <td>-0.526300</td>\n",
              "      <td>-0.430750</td>\n",
              "      <td>-0.488775</td>\n",
              "      <td>-0.593125</td>\n",
              "      <td>-0.498275</td>\n",
              "      <td>-0.489800</td>\n",
              "      <td>-0.564100</td>\n",
              "      <td>-0.538000</td>\n",
              "      <td>-0.464000</td>\n",
              "      <td>-0.521975</td>\n",
              "      <td>-0.488600</td>\n",
              "      <td>-0.442925</td>\n",
              "      <td>-0.457200</td>\n",
              "      <td>-0.477900</td>\n",
              "      <td>-0.458175</td>\n",
              "      <td>-0.479075</td>\n",
              "      <td>-0.478825</td>\n",
              "      <td>-0.489300</td>\n",
              "      <td>-0.327500</td>\n",
              "      <td>-0.576775</td>\n",
              "      <td>-0.278275</td>\n",
              "      <td>-0.492700</td>\n",
              "      <td>-0.501575</td>\n",
              "      <td>-0.526450</td>\n",
              "      <td>-0.507375</td>\n",
              "      <td>-0.559175</td>\n",
              "      <td>-0.433875</td>\n",
              "      <td>-0.502250</td>\n",
              "      <td>-0.537075</td>\n",
              "      <td>-0.508775</td>\n",
              "      <td>-0.606175</td>\n",
              "      <td>-0.506200</td>\n",
              "      <td>-0.353100</td>\n",
              "      <td>-0.544600</td>\n",
              "      <td>-0.554400</td>\n",
              "      <td>-0.523800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>0.007400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.065650</td>\n",
              "      <td>-0.014100</td>\n",
              "      <td>0.030850</td>\n",
              "      <td>-0.001800</td>\n",
              "      <td>-0.008400</td>\n",
              "      <td>0.101400</td>\n",
              "      <td>0.033400</td>\n",
              "      <td>-0.001600</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>0.014800</td>\n",
              "      <td>-0.044000</td>\n",
              "      <td>0.017400</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>-0.015550</td>\n",
              "      <td>0.025350</td>\n",
              "      <td>0.017750</td>\n",
              "      <td>0.053450</td>\n",
              "      <td>0.027700</td>\n",
              "      <td>-0.002100</td>\n",
              "      <td>0.009500</td>\n",
              "      <td>-0.004450</td>\n",
              "      <td>-0.000050</td>\n",
              "      <td>0.002400</td>\n",
              "      <td>0.024250</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>0.013600</td>\n",
              "      <td>0.001350</td>\n",
              "      <td>0.007350</td>\n",
              "      <td>0.038700</td>\n",
              "      <td>0.059600</td>\n",
              "      <td>-0.005900</td>\n",
              "      <td>-0.013600</td>\n",
              "      <td>-0.027700</td>\n",
              "      <td>-0.011850</td>\n",
              "      <td>0.009900</td>\n",
              "      <td>0.005400</td>\n",
              "      <td>0.000600</td>\n",
              "      <td>0.028700</td>\n",
              "      <td>-0.006500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>0.439400</td>\n",
              "      <td>...</td>\n",
              "      <td>0.646900</td>\n",
              "      <td>0.467900</td>\n",
              "      <td>0.543400</td>\n",
              "      <td>0.477200</td>\n",
              "      <td>0.497400</td>\n",
              "      <td>0.846400</td>\n",
              "      <td>0.573875</td>\n",
              "      <td>0.501675</td>\n",
              "      <td>0.519825</td>\n",
              "      <td>0.515000</td>\n",
              "      <td>0.412375</td>\n",
              "      <td>0.479400</td>\n",
              "      <td>0.646325</td>\n",
              "      <td>0.565200</td>\n",
              "      <td>0.610075</td>\n",
              "      <td>0.506975</td>\n",
              "      <td>0.671725</td>\n",
              "      <td>0.514175</td>\n",
              "      <td>0.524175</td>\n",
              "      <td>0.501325</td>\n",
              "      <td>0.516975</td>\n",
              "      <td>0.517475</td>\n",
              "      <td>0.375275</td>\n",
              "      <td>0.572250</td>\n",
              "      <td>0.251600</td>\n",
              "      <td>0.540950</td>\n",
              "      <td>0.530900</td>\n",
              "      <td>0.527900</td>\n",
              "      <td>0.475275</td>\n",
              "      <td>0.522075</td>\n",
              "      <td>0.648500</td>\n",
              "      <td>0.492150</td>\n",
              "      <td>0.522500</td>\n",
              "      <td>0.457000</td>\n",
              "      <td>0.483000</td>\n",
              "      <td>0.511175</td>\n",
              "      <td>0.409075</td>\n",
              "      <td>0.498500</td>\n",
              "      <td>0.496400</td>\n",
              "      <td>0.536950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.889000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.635000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.664000</td>\n",
              "      <td>9.566000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.497000</td>\n",
              "      <td>6.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.323000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.533000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.008000</td>\n",
              "      <td>5.900000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.552000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.346000</td>\n",
              "      <td>5.444000</td>\n",
              "      <td>6.317000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.911000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                g-0           g-1  ...         g-770         g-771\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean       0.248366     -0.095684  ...     -0.219210      0.101524\n",
              "std        1.393399      0.812363  ...      1.326193      1.417674\n",
              "min       -5.513000     -5.737000  ...    -10.000000    -10.000000\n",
              "25%       -0.473075     -0.562200  ...     -0.554400     -0.523800\n",
              "50%       -0.008850     -0.046600  ...      0.028700     -0.006500\n",
              "75%        0.525700      0.403075  ...      0.496400      0.536950\n",
              "max       10.000000      5.039000  ...     10.000000     10.000000\n",
              "\n",
              "[8 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8mp610qzHQGY"
      },
      "source": [
        "Apesar do describe reunir as nossas estatísticas de interesse, é bastante complexo analisar o dataframe resposta. Para facilitar o nosso entendimento, vamos plotar histogramas que nos ajudaram na visualização das estatísticas de todas as colunas selecionadas.\n",
        "Olhando o dataframe original, anteriormente, fizemos o histograma de apenas uma coluna. Mas agora, nosso conjunto de dados de interesse é o ```describe()``` que fizemos a partir do ```loc[]``` e, deste ponto de vista, não queremos mais fazer o histograma coluna a coluna (genes), queremos que ele seja a partir das linhas (estatísticas). Por isso, vamos transpor as linhas e colunas (transformar as linhas em colunas e vice-versa).\n",
        "Para isso, vamos usar o ```.T[]``` no código anterior que produzimos para organizar o ```describe()```.\n",
        "Ou seja, vamos manter todo o código até o ```describe()``` e, ao final, acrescentaremos o ```.T[]```. Mas, ao rodarmos essa linha, percebemos que temos como devolutiva o mesmo dataframe mas transposto. E, como aqui, nosso interesse é produzir histogramas, acrescentamos como argumento do ```.T[]``` a estatística alvo (```.T['estatística']```) e, por último, acrescentamos o ```.hist(bins = número de quebras)``` para que o histograma seja observado.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "ij9QVxGArZsd",
        "outputId": "d0594cfd-08a0-4035-da4a-69360e4b263b"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['mean'].hist(bins=30)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bed17f10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qbINMiTKKNqK"
      },
      "source": [
        "A seguir, reproduzimos o código acima apenas alterando o parâmetro estatístico a ser analisado (mínimo e máximo, por exemplo). \n",
        "E assim, podemos perceber as nuances de cada métrica."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "u31uRxYWr2PG",
        "outputId": "d2e77e40-f825-4826-a8a8-d764398d9dbe"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['min'].hist(bins=30)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bebee0d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "bYnsG81Sr8mc",
        "outputId": "128f1443-6844-4043-a12d-b9e9fbe32a4b"
      },
      "source": [
        "dados.loc[:,'g-0':'g-771'].describe().T['max'].hist(bins=30)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bf0c1c90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g8FvuJapKhco"
      },
      "source": [
        "É muito interessante que a gente replique a análise desenvolvida para os ```genes (g)```, nos ```tipos celulares (c)```. \n",
        "Por isso, vamos copiar a linha de código que produz os histogramas mas aqui, vamos modificar o argumento ```loc[:,'g-0':'g-771'] -> loc[:,'c-0':'c-99']``` e a quantidade de bins ```hist(bins=100) -> hist(bins=50)```."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "hu2jZ2snuJ09",
        "outputId": "bc773912-7bf2-49de-e099-0b406b6ed129"
      },
      "source": [
        "dados.loc[:,'c-0':'c-99'].describe().T['mean'].hist(bins=50)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bec6b2d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kUCr17j6xpu5"
      },
      "source": [
        "Um outro tipo de gráfico super interessante e útil é o boxplot. \n",
        "Para visualizá-lo, vamos usar a função ```boxplot```do Seaborn e, como argumentos dessa função vamos passar um ```x```, onde ```x = coluna que será plotada neste eixo``` e a base de dados ```data = conjunto de dados```.\n",
        "O boxplot apresenta uma caixa no meio onde podemos identificar a mediana (linha no meio da caixa que é o ponto onde metade dos dados estão na direita e a outra metade para a esquerda), os outliers (pontos acima ou abaixo do eixo principal do gráfico que representam valores discrepantes para mais ou para menos), a maior concentração dos dados (caixa principal que representa onde está a mior parte dos dados - primeiro quartil (25%) e terceiro quartil (75%)) e os máximos e mínimos desconsiderando os outliers (linhas laterais à caixa principal).\n",
        "O boxplot é uma importante ferramenta na visualização de dados porque em apenas um gráfico, podemos identificar várias métricas estatísticas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "R9LHaY0yv29K",
        "outputId": "3527f845-0c42-440b-d3f0-f49a7b942ffe"
      },
      "source": [
        "sns.boxplot(x='g-0' , data=dados)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2be8ba590>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4kvTdIE3d0W"
      },
      "source": [
        "Podemos também, além de definir apenas os dados que irão no eixo x, definimos os dados para o outro eixo, atribuindo um valor para o parâmetro ```y``` (```y = variável que vai ser plotada neste eixo```).\n",
        "Como podemos perceber, no boxplot que representa o ```tratamento = com_droga``` apresenta muitos outliers e isso gera uma discussão bastante interessante pois, do ponto de vista biológico a investigação desses pontos é importante mas, dependendo da área que estamos trabalhando, esse ponto pode apresentar outras soluções. \n",
        "Dito isso, é importante para um cientista de dados não só entender e manipular a base de dados mas também saber acerca do negócio que estamos tratando."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "h87JI4a_yNa1",
        "outputId": "029511d6-7c98-4af5-be72-2020ca41c860"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.boxplot(y='g-0', x='tratamento' , data=dados)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc2bec21cd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KbXSuyvbqdTE"
      },
      "source": [
        "# **Desafios - Aula 2**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X_Lg2XTu20ND"
      },
      "source": [
        "## **Desafio 01: Ordenar o gráfico countplot**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "Ip2zBJG3GDt0",
        "outputId": "9a9d352c-d41b-4db3-c7a5-052318fba424"
      },
      "source": [
        "top_compostos = dados.query('composto in @cod_compostos')\n",
        "top_compostos"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>composto</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>id_0020d0484</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.2711</td>\n",
              "      <td>0.5133</td>\n",
              "      <td>-0.1327</td>\n",
              "      <td>2.5950</td>\n",
              "      <td>0.6980</td>\n",
              "      <td>0.5846</td>\n",
              "      <td>-0.2633</td>\n",
              "      <td>-2.1490</td>\n",
              "      <td>0.4881</td>\n",
              "      <td>1.4750</td>\n",
              "      <td>-0.0488</td>\n",
              "      <td>-0.0561</td>\n",
              "      <td>0.1641</td>\n",
              "      <td>0.1749</td>\n",
              "      <td>-0.3464</td>\n",
              "      <td>-0.1811</td>\n",
              "      <td>0.5685</td>\n",
              "      <td>1.2970</td>\n",
              "      <td>1.0510</td>\n",
              "      <td>-0.9585</td>\n",
              "      <td>0.7911</td>\n",
              "      <td>-0.2991</td>\n",
              "      <td>2.7420</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>-1.0240</td>\n",
              "      <td>0.7268</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>-1.9730</td>\n",
              "      <td>1.1340</td>\n",
              "      <td>-2.5720</td>\n",
              "      <td>0.2068</td>\n",
              "      <td>0.9992</td>\n",
              "      <td>-0.1958</td>\n",
              "      <td>0.2262</td>\n",
              "      <td>1.0140</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2623</td>\n",
              "      <td>-0.5500</td>\n",
              "      <td>-0.0530</td>\n",
              "      <td>0.2077</td>\n",
              "      <td>-0.0825</td>\n",
              "      <td>0.2156</td>\n",
              "      <td>0.8142</td>\n",
              "      <td>1.0990</td>\n",
              "      <td>1.0860</td>\n",
              "      <td>0.4011</td>\n",
              "      <td>-0.1342</td>\n",
              "      <td>0.4653</td>\n",
              "      <td>-0.1104</td>\n",
              "      <td>0.3935</td>\n",
              "      <td>1.2370</td>\n",
              "      <td>-0.5072</td>\n",
              "      <td>0.0351</td>\n",
              "      <td>0.5084</td>\n",
              "      <td>-0.1248</td>\n",
              "      <td>0.4351</td>\n",
              "      <td>0.1389</td>\n",
              "      <td>0.6726</td>\n",
              "      <td>0.6070</td>\n",
              "      <td>0.3431</td>\n",
              "      <td>-0.4116</td>\n",
              "      <td>0.1194</td>\n",
              "      <td>0.3420</td>\n",
              "      <td>0.1331</td>\n",
              "      <td>0.8541</td>\n",
              "      <td>0.6282</td>\n",
              "      <td>0.3230</td>\n",
              "      <td>-0.4140</td>\n",
              "      <td>0.2532</td>\n",
              "      <td>0.0513</td>\n",
              "      <td>0.8600</td>\n",
              "      <td>1.4250</td>\n",
              "      <td>0.6633</td>\n",
              "      <td>0.4562</td>\n",
              "      <td>-0.9622</td>\n",
              "      <td>0.0260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>id_002fb9c19</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>8.7380</td>\n",
              "      <td>0.1914</td>\n",
              "      <td>2.4380</td>\n",
              "      <td>-0.2930</td>\n",
              "      <td>3.2010</td>\n",
              "      <td>1.4910</td>\n",
              "      <td>5.3920</td>\n",
              "      <td>-1.0420</td>\n",
              "      <td>-8.4860</td>\n",
              "      <td>-2.5790</td>\n",
              "      <td>-6.7470</td>\n",
              "      <td>3.6150</td>\n",
              "      <td>-1.4510</td>\n",
              "      <td>0.6909</td>\n",
              "      <td>-0.7623</td>\n",
              "      <td>-2.9400</td>\n",
              "      <td>-9.2850</td>\n",
              "      <td>-6.7110</td>\n",
              "      <td>-0.4195</td>\n",
              "      <td>1.1600</td>\n",
              "      <td>-1.3180</td>\n",
              "      <td>1.3660</td>\n",
              "      <td>-1.4020</td>\n",
              "      <td>-2.6220</td>\n",
              "      <td>0.7204</td>\n",
              "      <td>-2.5930</td>\n",
              "      <td>-4.0630</td>\n",
              "      <td>-0.8282</td>\n",
              "      <td>-3.5000</td>\n",
              "      <td>0.9206</td>\n",
              "      <td>-5.1450</td>\n",
              "      <td>9.8040</td>\n",
              "      <td>-2.6840</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>-0.1427</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-9.5910</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-8.8870</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-10.0000</td>\n",
              "      <td>-4.9020</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-5.5520</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.7960</td>\n",
              "      <td>-8.1770</td>\n",
              "      <td>-9.8990</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-9.9840</td>\n",
              "      <td>-6.7840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>id_0054388ec</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.6696</td>\n",
              "      <td>-0.2718</td>\n",
              "      <td>-1.2230</td>\n",
              "      <td>-0.6226</td>\n",
              "      <td>-0.7220</td>\n",
              "      <td>0.1588</td>\n",
              "      <td>0.7785</td>\n",
              "      <td>0.7062</td>\n",
              "      <td>-0.7951</td>\n",
              "      <td>1.3770</td>\n",
              "      <td>0.2856</td>\n",
              "      <td>-0.8331</td>\n",
              "      <td>0.3879</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>-0.4746</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>-0.2745</td>\n",
              "      <td>-0.1093</td>\n",
              "      <td>0.2603</td>\n",
              "      <td>0.7386</td>\n",
              "      <td>-0.6665</td>\n",
              "      <td>-1.6520</td>\n",
              "      <td>-0.9262</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.6310</td>\n",
              "      <td>-0.2933</td>\n",
              "      <td>0.2043</td>\n",
              "      <td>-2.2070</td>\n",
              "      <td>0.1383</td>\n",
              "      <td>-0.4966</td>\n",
              "      <td>0.6922</td>\n",
              "      <td>-0.4077</td>\n",
              "      <td>0.2303</td>\n",
              "      <td>-0.0456</td>\n",
              "      <td>-0.7447</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>-0.0178</td>\n",
              "      <td>0.3768</td>\n",
              "      <td>0.4318</td>\n",
              "      <td>-0.1051</td>\n",
              "      <td>0.3933</td>\n",
              "      <td>-0.3189</td>\n",
              "      <td>0.4128</td>\n",
              "      <td>-0.2116</td>\n",
              "      <td>-1.0410</td>\n",
              "      <td>0.7798</td>\n",
              "      <td>0.1579</td>\n",
              "      <td>1.7250</td>\n",
              "      <td>1.4490</td>\n",
              "      <td>0.9117</td>\n",
              "      <td>-0.0754</td>\n",
              "      <td>-0.8396</td>\n",
              "      <td>0.7640</td>\n",
              "      <td>1.2080</td>\n",
              "      <td>1.1890</td>\n",
              "      <td>0.2114</td>\n",
              "      <td>0.6335</td>\n",
              "      <td>0.3265</td>\n",
              "      <td>-0.1056</td>\n",
              "      <td>0.5478</td>\n",
              "      <td>0.7477</td>\n",
              "      <td>1.2340</td>\n",
              "      <td>0.5035</td>\n",
              "      <td>-0.6591</td>\n",
              "      <td>0.3023</td>\n",
              "      <td>0.6171</td>\n",
              "      <td>0.6405</td>\n",
              "      <td>0.5429</td>\n",
              "      <td>0.3562</td>\n",
              "      <td>1.3290</td>\n",
              "      <td>0.5573</td>\n",
              "      <td>0.8837</td>\n",
              "      <td>0.5534</td>\n",
              "      <td>0.8976</td>\n",
              "      <td>1.0050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>id_0079af0fb</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-0.1636</td>\n",
              "      <td>-1.8230</td>\n",
              "      <td>-0.5211</td>\n",
              "      <td>0.3054</td>\n",
              "      <td>-1.1280</td>\n",
              "      <td>0.6041</td>\n",
              "      <td>0.3856</td>\n",
              "      <td>-0.1670</td>\n",
              "      <td>-0.5400</td>\n",
              "      <td>0.2721</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>0.0761</td>\n",
              "      <td>-0.4054</td>\n",
              "      <td>2.9760</td>\n",
              "      <td>-0.7679</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>0.0752</td>\n",
              "      <td>0.5943</td>\n",
              "      <td>0.4266</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1.0410</td>\n",
              "      <td>-0.1131</td>\n",
              "      <td>0.6593</td>\n",
              "      <td>-0.6890</td>\n",
              "      <td>0.5115</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>-1.3810</td>\n",
              "      <td>0.1419</td>\n",
              "      <td>-0.0363</td>\n",
              "      <td>0.2559</td>\n",
              "      <td>2.5290</td>\n",
              "      <td>0.2853</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.3626</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.3420</td>\n",
              "      <td>0.2815</td>\n",
              "      <td>-0.7493</td>\n",
              "      <td>-0.2701</td>\n",
              "      <td>0.1205</td>\n",
              "      <td>0.2396</td>\n",
              "      <td>0.3506</td>\n",
              "      <td>-0.9233</td>\n",
              "      <td>0.2490</td>\n",
              "      <td>-0.0824</td>\n",
              "      <td>0.4841</td>\n",
              "      <td>1.1940</td>\n",
              "      <td>-1.1650</td>\n",
              "      <td>-0.4853</td>\n",
              "      <td>1.1080</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>0.7438</td>\n",
              "      <td>0.2050</td>\n",
              "      <td>-0.2761</td>\n",
              "      <td>-0.1748</td>\n",
              "      <td>0.3385</td>\n",
              "      <td>-0.3500</td>\n",
              "      <td>-0.0309</td>\n",
              "      <td>-0.0409</td>\n",
              "      <td>-0.0735</td>\n",
              "      <td>0.2732</td>\n",
              "      <td>-1.2100</td>\n",
              "      <td>0.0089</td>\n",
              "      <td>0.0317</td>\n",
              "      <td>0.4721</td>\n",
              "      <td>-0.3880</td>\n",
              "      <td>-0.6828</td>\n",
              "      <td>-0.6594</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>-0.1319</td>\n",
              "      <td>0.2187</td>\n",
              "      <td>0.0737</td>\n",
              "      <td>0.6498</td>\n",
              "      <td>-1.4820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>id_007bfbb91</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>-1.3200</td>\n",
              "      <td>-1.7340</td>\n",
              "      <td>-0.0741</td>\n",
              "      <td>1.5440</td>\n",
              "      <td>-1.8290</td>\n",
              "      <td>-0.0951</td>\n",
              "      <td>0.3829</td>\n",
              "      <td>-1.8700</td>\n",
              "      <td>-0.0324</td>\n",
              "      <td>2.7670</td>\n",
              "      <td>-0.0438</td>\n",
              "      <td>-0.0147</td>\n",
              "      <td>0.1276</td>\n",
              "      <td>0.2968</td>\n",
              "      <td>-0.0704</td>\n",
              "      <td>-0.3767</td>\n",
              "      <td>2.5790</td>\n",
              "      <td>0.4069</td>\n",
              "      <td>-0.3868</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>1.8180</td>\n",
              "      <td>-2.9390</td>\n",
              "      <td>-0.1150</td>\n",
              "      <td>-0.8009</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>0.5412</td>\n",
              "      <td>-0.0804</td>\n",
              "      <td>-0.4444</td>\n",
              "      <td>2.9230</td>\n",
              "      <td>2.8270</td>\n",
              "      <td>-0.3437</td>\n",
              "      <td>1.6570</td>\n",
              "      <td>-1.9200</td>\n",
              "      <td>0.3442</td>\n",
              "      <td>1.7160</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4009</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2789</td>\n",
              "      <td>0.4465</td>\n",
              "      <td>0.9492</td>\n",
              "      <td>0.6385</td>\n",
              "      <td>1.5510</td>\n",
              "      <td>-0.1220</td>\n",
              "      <td>0.6688</td>\n",
              "      <td>0.4396</td>\n",
              "      <td>0.6947</td>\n",
              "      <td>0.9761</td>\n",
              "      <td>1.2430</td>\n",
              "      <td>1.4770</td>\n",
              "      <td>-0.0081</td>\n",
              "      <td>1.0040</td>\n",
              "      <td>1.4420</td>\n",
              "      <td>-0.3482</td>\n",
              "      <td>0.3297</td>\n",
              "      <td>1.2070</td>\n",
              "      <td>0.0524</td>\n",
              "      <td>0.5346</td>\n",
              "      <td>0.7643</td>\n",
              "      <td>0.4067</td>\n",
              "      <td>0.3817</td>\n",
              "      <td>0.4566</td>\n",
              "      <td>0.7736</td>\n",
              "      <td>0.5316</td>\n",
              "      <td>0.2790</td>\n",
              "      <td>0.9735</td>\n",
              "      <td>0.7412</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.7393</td>\n",
              "      <td>1.1020</td>\n",
              "      <td>0.3786</td>\n",
              "      <td>0.2636</td>\n",
              "      <td>-0.5751</td>\n",
              "      <td>0.3362</td>\n",
              "      <td>0.8543</td>\n",
              "      <td>0.9180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23793</th>\n",
              "      <td>id_ffd26f361</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.6008</td>\n",
              "      <td>0.2781</td>\n",
              "      <td>-0.3319</td>\n",
              "      <td>-0.8782</td>\n",
              "      <td>0.9281</td>\n",
              "      <td>0.7535</td>\n",
              "      <td>0.5971</td>\n",
              "      <td>1.6350</td>\n",
              "      <td>-0.3146</td>\n",
              "      <td>0.4984</td>\n",
              "      <td>-1.1890</td>\n",
              "      <td>0.3772</td>\n",
              "      <td>-0.8196</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-2.0350</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.7586</td>\n",
              "      <td>-0.4024</td>\n",
              "      <td>-0.0449</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.2358</td>\n",
              "      <td>0.7919</td>\n",
              "      <td>-0.8775</td>\n",
              "      <td>0.4232</td>\n",
              "      <td>1.8460</td>\n",
              "      <td>-2.0940</td>\n",
              "      <td>0.1438</td>\n",
              "      <td>-0.6604</td>\n",
              "      <td>0.7243</td>\n",
              "      <td>0.0338</td>\n",
              "      <td>-0.0182</td>\n",
              "      <td>-0.2022</td>\n",
              "      <td>0.8827</td>\n",
              "      <td>0.3147</td>\n",
              "      <td>-0.9263</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1934</td>\n",
              "      <td>1.2240</td>\n",
              "      <td>-0.1178</td>\n",
              "      <td>0.1459</td>\n",
              "      <td>-0.1242</td>\n",
              "      <td>0.3106</td>\n",
              "      <td>-0.7959</td>\n",
              "      <td>0.5681</td>\n",
              "      <td>0.3663</td>\n",
              "      <td>0.4874</td>\n",
              "      <td>-0.0548</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>1.3470</td>\n",
              "      <td>1.6210</td>\n",
              "      <td>-0.8260</td>\n",
              "      <td>0.3377</td>\n",
              "      <td>0.3264</td>\n",
              "      <td>0.9241</td>\n",
              "      <td>0.3012</td>\n",
              "      <td>1.2980</td>\n",
              "      <td>-0.2789</td>\n",
              "      <td>0.7019</td>\n",
              "      <td>-0.3528</td>\n",
              "      <td>0.7383</td>\n",
              "      <td>1.0300</td>\n",
              "      <td>0.6527</td>\n",
              "      <td>1.6750</td>\n",
              "      <td>-0.5046</td>\n",
              "      <td>0.2942</td>\n",
              "      <td>0.2950</td>\n",
              "      <td>1.2470</td>\n",
              "      <td>0.9569</td>\n",
              "      <td>-0.2065</td>\n",
              "      <td>-0.4918</td>\n",
              "      <td>0.7863</td>\n",
              "      <td>0.0504</td>\n",
              "      <td>0.8813</td>\n",
              "      <td>0.7757</td>\n",
              "      <td>-0.5272</td>\n",
              "      <td>0.7082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23802</th>\n",
              "      <td>id_fff3976bd</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>87d714366</td>\n",
              "      <td>3.2890</td>\n",
              "      <td>2.1270</td>\n",
              "      <td>0.9770</td>\n",
              "      <td>2.0490</td>\n",
              "      <td>2.3170</td>\n",
              "      <td>-0.5355</td>\n",
              "      <td>-0.6357</td>\n",
              "      <td>-6.9060</td>\n",
              "      <td>-4.4830</td>\n",
              "      <td>-2.8400</td>\n",
              "      <td>-5.3310</td>\n",
              "      <td>0.6547</td>\n",
              "      <td>-2.2080</td>\n",
              "      <td>3.6030</td>\n",
              "      <td>0.6380</td>\n",
              "      <td>-2.1280</td>\n",
              "      <td>-3.1680</td>\n",
              "      <td>-4.2180</td>\n",
              "      <td>-0.3170</td>\n",
              "      <td>0.2140</td>\n",
              "      <td>-1.7660</td>\n",
              "      <td>-1.9700</td>\n",
              "      <td>-1.4820</td>\n",
              "      <td>-1.3710</td>\n",
              "      <td>-0.2628</td>\n",
              "      <td>-0.5276</td>\n",
              "      <td>-2.4160</td>\n",
              "      <td>-0.4638</td>\n",
              "      <td>-3.8630</td>\n",
              "      <td>-0.8880</td>\n",
              "      <td>-1.9850</td>\n",
              "      <td>2.0530</td>\n",
              "      <td>-1.4700</td>\n",
              "      <td>-3.3220</td>\n",
              "      <td>1.8800</td>\n",
              "      <td>...</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.0200</td>\n",
              "      <td>-6.7560</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-4.1240</td>\n",
              "      <td>-8.5110</td>\n",
              "      <td>-5.7500</td>\n",
              "      <td>-8.4760</td>\n",
              "      <td>-6.9470</td>\n",
              "      <td>-4.7650</td>\n",
              "      <td>-9.7690</td>\n",
              "      <td>-5.7900</td>\n",
              "      <td>-9.9170</td>\n",
              "      <td>-5.7450</td>\n",
              "      <td>-2.3570</td>\n",
              "      <td>-9.1190</td>\n",
              "      <td>-4.5980</td>\n",
              "      <td>-8.7760</td>\n",
              "      <td>-7.7980</td>\n",
              "      <td>-4.1620</td>\n",
              "      <td>-6.1510</td>\n",
              "      <td>-5.7400</td>\n",
              "      <td>-6.8700</td>\n",
              "      <td>-9.1000</td>\n",
              "      <td>-3.3360</td>\n",
              "      <td>-6.6420</td>\n",
              "      <td>-2.2750</td>\n",
              "      <td>-3.4720</td>\n",
              "      <td>-6.2670</td>\n",
              "      <td>-6.3980</td>\n",
              "      <td>-8.6300</td>\n",
              "      <td>-8.1490</td>\n",
              "      <td>-6.2900</td>\n",
              "      <td>-8.0970</td>\n",
              "      <td>-8.7330</td>\n",
              "      <td>-2.3780</td>\n",
              "      <td>-8.4480</td>\n",
              "      <td>-4.4550</td>\n",
              "      <td>-5.7930</td>\n",
              "      <td>-3.7000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23805</th>\n",
              "      <td>id_fff6df1c5</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>5628cb3ee</td>\n",
              "      <td>1.7380</td>\n",
              "      <td>-1.2900</td>\n",
              "      <td>-0.4533</td>\n",
              "      <td>-1.1640</td>\n",
              "      <td>-0.4841</td>\n",
              "      <td>-0.2392</td>\n",
              "      <td>-0.1774</td>\n",
              "      <td>-1.3980</td>\n",
              "      <td>-0.4059</td>\n",
              "      <td>0.1553</td>\n",
              "      <td>0.1083</td>\n",
              "      <td>-0.8020</td>\n",
              "      <td>-0.5039</td>\n",
              "      <td>-0.7167</td>\n",
              "      <td>-0.5016</td>\n",
              "      <td>-0.9369</td>\n",
              "      <td>-0.5864</td>\n",
              "      <td>-0.1009</td>\n",
              "      <td>0.8987</td>\n",
              "      <td>0.3389</td>\n",
              "      <td>-1.3460</td>\n",
              "      <td>-0.5087</td>\n",
              "      <td>-0.0892</td>\n",
              "      <td>-0.6559</td>\n",
              "      <td>0.0864</td>\n",
              "      <td>-0.6251</td>\n",
              "      <td>0.2471</td>\n",
              "      <td>-0.4523</td>\n",
              "      <td>-0.0389</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>0.0796</td>\n",
              "      <td>-0.2560</td>\n",
              "      <td>-0.7851</td>\n",
              "      <td>-0.1687</td>\n",
              "      <td>-1.2890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.2866</td>\n",
              "      <td>0.3854</td>\n",
              "      <td>-0.4986</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.5843</td>\n",
              "      <td>0.0907</td>\n",
              "      <td>-0.9303</td>\n",
              "      <td>0.1981</td>\n",
              "      <td>0.6515</td>\n",
              "      <td>0.2877</td>\n",
              "      <td>0.4389</td>\n",
              "      <td>-0.3859</td>\n",
              "      <td>0.5203</td>\n",
              "      <td>-1.1070</td>\n",
              "      <td>2.3870</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-0.6434</td>\n",
              "      <td>-0.9722</td>\n",
              "      <td>-0.4200</td>\n",
              "      <td>-0.5693</td>\n",
              "      <td>1.0700</td>\n",
              "      <td>1.1110</td>\n",
              "      <td>-0.5117</td>\n",
              "      <td>-1.2130</td>\n",
              "      <td>0.3769</td>\n",
              "      <td>0.5296</td>\n",
              "      <td>1.0400</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>1.0150</td>\n",
              "      <td>-0.7669</td>\n",
              "      <td>0.2865</td>\n",
              "      <td>0.5974</td>\n",
              "      <td>-0.2727</td>\n",
              "      <td>0.1188</td>\n",
              "      <td>1.0770</td>\n",
              "      <td>-1.0250</td>\n",
              "      <td>0.1516</td>\n",
              "      <td>0.4503</td>\n",
              "      <td>-0.6312</td>\n",
              "      <td>-0.8302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3235 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n",
              "16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n",
              "25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n",
              "38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n",
              "40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n",
              "23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n",
              "23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "\n",
              "[3235 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        },
        "id": "T65e69uHGVNq",
        "outputId": "fb65766e-a845-433a-cd6d-65ad37244e1a"
      },
      "source": [
        "contagem_top_compostos = top_compostos['composto'].value_counts().to_frame()\n",
        "contagem_top_compostos"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>composto</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>cacb2b860</th>\n",
              "      <td>1866</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>87d714366</th>\n",
              "      <td>718</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9f80f3f77</th>\n",
              "      <td>246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8b87a7a83</th>\n",
              "      <td>203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5628cb3ee</th>\n",
              "      <td>202</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           composto\n",
              "cacb2b860      1866\n",
              "87d714366       718\n",
              "9f80f3f77       246\n",
              "8b87a7a83       203\n",
              "5628cb3ee       202"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 523
        },
        "id": "asJVRq8pGp4F",
        "outputId": "8462a18b-0ba3-4e2b-9482-6f600bab7f19"
      },
      "source": [
        "plt.figure(figsize=(10, 8))\n",
        "ax = sns.countplot(x = 'composto', data=top_compostos, order = contagem_top_compostos.index)\n",
        "ax.set_title('Top 5 compostos', fontsize = 18)\n",
        "ax.set_xlabel('Id do Composto', fontsize = 14)\n",
        "ax.set_ylabel('Frequência', fontsize = 14)\n",
        "plt.show()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aRdNRT3u6Rda"
      },
      "source": [
        "## **Desafio 02: Melhorar a visualização alterando tamanho da fonte...**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "WL8FxZ3MEL7k",
        "outputId": "f4004965-4174-4064-b6bd-85c066c26bdd"
      },
      "source": [
        "plt.figure(figsize=(10, 8))\n",
        "ax = sns.countplot(x = 'composto',\n",
        "                   data=dados.query('composto in @cod_compostos'),\n",
        "                   order = contagem_top_compostos.index,\n",
        "                   palette=\"flare\")\n",
        "for p in ax.patches:\n",
        "  height = p.get_height()\n",
        "  ax.text(p.get_x() + p.get_width()/2.,\n",
        "          height + 10, '{:1.2f}'.format(height),\n",
        "          ha = 'center')\n",
        "ax.set_title('Top 5 compostos', fontsize = 22)\n",
        "ax.set_xlabel('Id do Composto', fontsize = 14)\n",
        "ax.set_ylabel('Frequência', fontsize = 14)\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nXefaxUi6ROc"
      },
      "source": [
        "## **Desafio 03: Plotar os histogramas com seaborn**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "cOViDLJQXiw1",
        "outputId": "8f388ede-5850-4ca4-e5ae-788c3ffbccb8"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Plot do Gene 'g-0':\n",
        "ax1 = sns.histplot(data = dados['g-0'], ax = axs[0])\n",
        "ax1.set_title('Distribuição de Frequência da Expressão do Gene \"g-0\"', fontsize = 18)\n",
        "ax1.set_xlabel('Id do Composto', fontsize = 14)\n",
        "ax1.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "#Plot do Gene 'g-19':\n",
        "ax2 = sns.histplot(data = dados['g-19'], ax = axs[1])\n",
        "ax2.set_title('Distribuição de Frequência da Expressão do Gene \"g-19\"', fontsize = 18)\n",
        "ax2.set_xlabel('Id do Composto', fontsize = 14)\n",
        "ax2.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "k9dbAMmldgSq",
        "outputId": "8a5ef4f3-e348-4f9d-a8a3-c90a80996ab8"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Plot das Médias:\n",
        "ax1 = sns.histplot(data = dados.loc[:,'g-0':'g-771'].describe().T['mean'], ax = axs[0])\n",
        "ax1.set_title('Distribuição de Frequências dos Valores Médios de Expressividade', fontsize = 18)\n",
        "ax1.set_xlabel('Valores Médios', fontsize = 14)\n",
        "ax1.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "#Plot dos Desvios Padrões:\n",
        "ax2 = sns.histplot(data = dados.loc[:,'g-0':'g-771'].describe().T['std'], ax = axs[1])\n",
        "ax2.set_title('Distribuição de Frequências dos Desvios Padrões de Expressividade', fontsize = 18)\n",
        "ax2.set_xlabel('Valores de Desvio Padrão', fontsize = 14)\n",
        "ax2.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "y9ocknbWfABH",
        "outputId": "ed251cd8-8e5f-41fd-cfd6-d419b614240e"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Plot dos Valores Mínimos:\n",
        "ax1 = sns.histplot(data = dados.loc[:,'g-0':'g-771'].describe().T['min'], ax = axs[0])\n",
        "ax1.set_title('Distribuição de Frequências dos Valores Mínimos de Expressividade', fontsize = 18)\n",
        "ax1.set_xlabel('Valores Mínimos de Expressividade', fontsize = 14)\n",
        "ax1.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "#Plot dos Valores Máximos:\n",
        "ax2 = sns.histplot(data = dados.loc[:,'g-0':'g-771'].describe().T['max'], ax = axs[1])\n",
        "ax2.set_title('Distribuição de Frequências dos Valores Máximos de Expressividade', fontsize = 18)\n",
        "ax2.set_xlabel('Valores Máximos de Expressividade', fontsize = 14)\n",
        "ax2.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "x6bWhEnKgfwP",
        "outputId": "09272cc3-6668-46cd-c2ca-3141f3bdb6b3"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Plot das Médias:\n",
        "ax1 = sns.histplot(data = dados.loc[:,'c-0':'c-99'].describe().T['mean'], ax = axs[0])\n",
        "ax1.set_title('Distribuição de Frequências dos Valores Médios de \"c\"', fontsize = 18)\n",
        "ax1.set_xlabel('Valores Médios', fontsize = 14)\n",
        "ax1.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "#Plot dos Desvios Padrões:\n",
        "ax2 = sns.histplot(data = dados.loc[:,'c-0':'c-99'].describe().T['std'], ax = axs[1])\n",
        "ax2.set_title('Distribuição de Frequências dos Desvios Padrões de \"c\"', fontsize = 18)\n",
        "ax2.set_xlabel('Valores de Desvio Padrão', fontsize = 14)\n",
        "ax2.set_ylabel('Frequência', fontsize = 14)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iYMajXha6RDF"
      },
      "source": [
        "## **Desafio 04: Estudar sobre as estatíticas retornadas no .describe()**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xdsCamz5hfuf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "outputId": "6b957106-e733-4f58-ff9d-9bafd4dfecff"
      },
      "source": [
        "dados.describe()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tempo</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "      <td>23814.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.020156</td>\n",
              "      <td>0.248366</td>\n",
              "      <td>-0.095684</td>\n",
              "      <td>0.152253</td>\n",
              "      <td>0.081971</td>\n",
              "      <td>0.057347</td>\n",
              "      <td>-0.138836</td>\n",
              "      <td>0.035961</td>\n",
              "      <td>-0.202651</td>\n",
              "      <td>-0.190083</td>\n",
              "      <td>0.119905</td>\n",
              "      <td>-0.123321</td>\n",
              "      <td>0.182307</td>\n",
              "      <td>0.143203</td>\n",
              "      <td>0.209402</td>\n",
              "      <td>-0.173884</td>\n",
              "      <td>-0.024432</td>\n",
              "      <td>0.126823</td>\n",
              "      <td>-0.146663</td>\n",
              "      <td>0.087687</td>\n",
              "      <td>-0.082982</td>\n",
              "      <td>-0.111908</td>\n",
              "      <td>-0.087379</td>\n",
              "      <td>0.047548</td>\n",
              "      <td>-0.117474</td>\n",
              "      <td>-0.113212</td>\n",
              "      <td>-0.052746</td>\n",
              "      <td>-0.091055</td>\n",
              "      <td>0.112176</td>\n",
              "      <td>-0.046458</td>\n",
              "      <td>-0.076239</td>\n",
              "      <td>-0.197699</td>\n",
              "      <td>0.382177</td>\n",
              "      <td>-0.189432</td>\n",
              "      <td>0.078791</td>\n",
              "      <td>-0.093312</td>\n",
              "      <td>0.135729</td>\n",
              "      <td>-0.188616</td>\n",
              "      <td>-0.606710</td>\n",
              "      <td>0.534425</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.517397</td>\n",
              "      <td>-0.360770</td>\n",
              "      <td>-0.435752</td>\n",
              "      <td>-0.613591</td>\n",
              "      <td>-0.402083</td>\n",
              "      <td>-0.619682</td>\n",
              "      <td>-0.452265</td>\n",
              "      <td>-0.497164</td>\n",
              "      <td>-0.413836</td>\n",
              "      <td>-0.277029</td>\n",
              "      <td>-0.547845</td>\n",
              "      <td>-0.358611</td>\n",
              "      <td>-0.442906</td>\n",
              "      <td>-0.475194</td>\n",
              "      <td>-0.010404</td>\n",
              "      <td>-0.467001</td>\n",
              "      <td>-0.276963</td>\n",
              "      <td>-0.455848</td>\n",
              "      <td>-0.412918</td>\n",
              "      <td>-0.456404</td>\n",
              "      <td>-0.472514</td>\n",
              "      <td>-0.505481</td>\n",
              "      <td>-0.492735</td>\n",
              "      <td>-0.446836</td>\n",
              "      <td>-0.463029</td>\n",
              "      <td>-0.409310</td>\n",
              "      <td>-0.333124</td>\n",
              "      <td>-0.295009</td>\n",
              "      <td>-0.328342</td>\n",
              "      <td>-0.401615</td>\n",
              "      <td>-0.469244</td>\n",
              "      <td>-0.461411</td>\n",
              "      <td>-0.513256</td>\n",
              "      <td>-0.500142</td>\n",
              "      <td>-0.507093</td>\n",
              "      <td>-0.353726</td>\n",
              "      <td>-0.463485</td>\n",
              "      <td>-0.378241</td>\n",
              "      <td>-0.470252</td>\n",
              "      <td>-0.301505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>19.402807</td>\n",
              "      <td>1.393399</td>\n",
              "      <td>0.812363</td>\n",
              "      <td>1.035731</td>\n",
              "      <td>0.950012</td>\n",
              "      <td>1.032091</td>\n",
              "      <td>1.179388</td>\n",
              "      <td>0.882395</td>\n",
              "      <td>1.125494</td>\n",
              "      <td>1.749885</td>\n",
              "      <td>1.087180</td>\n",
              "      <td>1.291501</td>\n",
              "      <td>1.253604</td>\n",
              "      <td>1.234590</td>\n",
              "      <td>1.273068</td>\n",
              "      <td>1.247178</td>\n",
              "      <td>0.659839</td>\n",
              "      <td>1.418997</td>\n",
              "      <td>1.179688</td>\n",
              "      <td>0.743301</td>\n",
              "      <td>0.844796</td>\n",
              "      <td>1.219529</td>\n",
              "      <td>0.824401</td>\n",
              "      <td>0.924838</td>\n",
              "      <td>0.760159</td>\n",
              "      <td>1.203186</td>\n",
              "      <td>0.866977</td>\n",
              "      <td>1.103765</td>\n",
              "      <td>1.001687</td>\n",
              "      <td>1.027758</td>\n",
              "      <td>1.279399</td>\n",
              "      <td>1.302567</td>\n",
              "      <td>1.559174</td>\n",
              "      <td>0.933514</td>\n",
              "      <td>1.172270</td>\n",
              "      <td>1.174325</td>\n",
              "      <td>1.061719</td>\n",
              "      <td>1.397677</td>\n",
              "      <td>2.200277</td>\n",
              "      <td>2.003317</td>\n",
              "      <td>...</td>\n",
              "      <td>2.122318</td>\n",
              "      <td>1.710725</td>\n",
              "      <td>1.898871</td>\n",
              "      <td>2.307820</td>\n",
              "      <td>1.785055</td>\n",
              "      <td>2.225596</td>\n",
              "      <td>1.991021</td>\n",
              "      <td>2.063896</td>\n",
              "      <td>1.887001</td>\n",
              "      <td>1.459639</td>\n",
              "      <td>2.187835</td>\n",
              "      <td>1.730634</td>\n",
              "      <td>1.924716</td>\n",
              "      <td>2.021927</td>\n",
              "      <td>1.029820</td>\n",
              "      <td>2.004317</td>\n",
              "      <td>1.429340</td>\n",
              "      <td>1.924263</td>\n",
              "      <td>1.888788</td>\n",
              "      <td>1.832863</td>\n",
              "      <td>2.011396</td>\n",
              "      <td>2.091353</td>\n",
              "      <td>2.055624</td>\n",
              "      <td>1.987476</td>\n",
              "      <td>2.014045</td>\n",
              "      <td>1.883974</td>\n",
              "      <td>1.647241</td>\n",
              "      <td>1.634073</td>\n",
              "      <td>1.663170</td>\n",
              "      <td>1.832794</td>\n",
              "      <td>2.000488</td>\n",
              "      <td>2.042475</td>\n",
              "      <td>2.001714</td>\n",
              "      <td>2.107105</td>\n",
              "      <td>2.159589</td>\n",
              "      <td>1.629291</td>\n",
              "      <td>2.059725</td>\n",
              "      <td>1.703615</td>\n",
              "      <td>1.834828</td>\n",
              "      <td>1.407918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-5.513000</td>\n",
              "      <td>-5.737000</td>\n",
              "      <td>-9.104000</td>\n",
              "      <td>-5.998000</td>\n",
              "      <td>-6.369000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.337000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.870000</td>\n",
              "      <td>-8.587000</td>\n",
              "      <td>-5.018000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-4.226000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-5.700000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-8.272000</td>\n",
              "      <td>-8.184000</td>\n",
              "      <td>-4.835000</td>\n",
              "      <td>-7.913000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-2.956000</td>\n",
              "      <td>-8.356000</td>\n",
              "      <td>-7.182000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.261000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.839000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-6.452000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-9.938000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "      <td>-10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>24.000000</td>\n",
              "      <td>-0.473075</td>\n",
              "      <td>-0.562200</td>\n",
              "      <td>-0.437750</td>\n",
              "      <td>-0.429575</td>\n",
              "      <td>-0.470925</td>\n",
              "      <td>-0.602225</td>\n",
              "      <td>-0.493900</td>\n",
              "      <td>-0.525175</td>\n",
              "      <td>-0.511675</td>\n",
              "      <td>-0.360200</td>\n",
              "      <td>-0.511475</td>\n",
              "      <td>-0.489675</td>\n",
              "      <td>-0.447500</td>\n",
              "      <td>-0.481200</td>\n",
              "      <td>-0.607975</td>\n",
              "      <td>-0.404150</td>\n",
              "      <td>-0.391950</td>\n",
              "      <td>-0.513775</td>\n",
              "      <td>-0.272200</td>\n",
              "      <td>-0.488675</td>\n",
              "      <td>-0.524600</td>\n",
              "      <td>-0.538900</td>\n",
              "      <td>-0.440375</td>\n",
              "      <td>-0.508900</td>\n",
              "      <td>-0.533900</td>\n",
              "      <td>-0.497700</td>\n",
              "      <td>-0.512875</td>\n",
              "      <td>-0.467800</td>\n",
              "      <td>-0.378300</td>\n",
              "      <td>-0.505750</td>\n",
              "      <td>-0.457975</td>\n",
              "      <td>-0.328200</td>\n",
              "      <td>-0.600500</td>\n",
              "      <td>-0.478700</td>\n",
              "      <td>-0.570525</td>\n",
              "      <td>-0.481800</td>\n",
              "      <td>-0.541950</td>\n",
              "      <td>-0.604100</td>\n",
              "      <td>-0.470250</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.588075</td>\n",
              "      <td>-0.564025</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.583250</td>\n",
              "      <td>-0.566500</td>\n",
              "      <td>-0.603200</td>\n",
              "      <td>-0.541575</td>\n",
              "      <td>-0.560825</td>\n",
              "      <td>-0.555200</td>\n",
              "      <td>-0.534500</td>\n",
              "      <td>-0.569100</td>\n",
              "      <td>-0.558300</td>\n",
              "      <td>-0.573350</td>\n",
              "      <td>-0.594275</td>\n",
              "      <td>-0.389925</td>\n",
              "      <td>-0.551200</td>\n",
              "      <td>-0.544150</td>\n",
              "      <td>-0.575075</td>\n",
              "      <td>-0.568275</td>\n",
              "      <td>-0.582650</td>\n",
              "      <td>-0.558575</td>\n",
              "      <td>-0.562375</td>\n",
              "      <td>-0.572800</td>\n",
              "      <td>-0.561225</td>\n",
              "      <td>-0.560675</td>\n",
              "      <td>-0.560100</td>\n",
              "      <td>-0.533700</td>\n",
              "      <td>-0.504575</td>\n",
              "      <td>-0.544275</td>\n",
              "      <td>-0.569150</td>\n",
              "      <td>-0.566175</td>\n",
              "      <td>-0.565975</td>\n",
              "      <td>-0.589975</td>\n",
              "      <td>-0.568700</td>\n",
              "      <td>-0.563775</td>\n",
              "      <td>-0.567975</td>\n",
              "      <td>-0.552575</td>\n",
              "      <td>-0.561000</td>\n",
              "      <td>-0.592600</td>\n",
              "      <td>-0.562900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>-0.008850</td>\n",
              "      <td>-0.046600</td>\n",
              "      <td>0.075200</td>\n",
              "      <td>0.008050</td>\n",
              "      <td>-0.026900</td>\n",
              "      <td>-0.015650</td>\n",
              "      <td>-0.000650</td>\n",
              "      <td>-0.017900</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.160450</td>\n",
              "      <td>0.038550</td>\n",
              "      <td>0.013800</td>\n",
              "      <td>0.060250</td>\n",
              "      <td>0.009800</td>\n",
              "      <td>-0.030100</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149400</td>\n",
              "      <td>-0.002200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.027800</td>\n",
              "      <td>-0.002800</td>\n",
              "      <td>-0.069350</td>\n",
              "      <td>-0.011800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.018300</td>\n",
              "      <td>-0.011650</td>\n",
              "      <td>0.016100</td>\n",
              "      <td>0.037600</td>\n",
              "      <td>0.003750</td>\n",
              "      <td>0.021750</td>\n",
              "      <td>0.027000</td>\n",
              "      <td>0.019100</td>\n",
              "      <td>-0.054000</td>\n",
              "      <td>0.023350</td>\n",
              "      <td>0.003350</td>\n",
              "      <td>-0.000600</td>\n",
              "      <td>0.015350</td>\n",
              "      <td>-0.000700</td>\n",
              "      <td>0.005800</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.017650</td>\n",
              "      <td>-0.041550</td>\n",
              "      <td>-0.002950</td>\n",
              "      <td>-0.012650</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>0.007650</td>\n",
              "      <td>0.004950</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.023800</td>\n",
              "      <td>-0.011450</td>\n",
              "      <td>-0.007100</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.019500</td>\n",
              "      <td>-0.009300</td>\n",
              "      <td>0.081550</td>\n",
              "      <td>-0.006900</td>\n",
              "      <td>0.018400</td>\n",
              "      <td>-0.014650</td>\n",
              "      <td>-0.014350</td>\n",
              "      <td>0.005300</td>\n",
              "      <td>-0.005300</td>\n",
              "      <td>-0.004050</td>\n",
              "      <td>0.003300</td>\n",
              "      <td>-0.007900</td>\n",
              "      <td>-0.004600</td>\n",
              "      <td>-0.002400</td>\n",
              "      <td>0.007850</td>\n",
              "      <td>-0.005600</td>\n",
              "      <td>-0.020600</td>\n",
              "      <td>-0.030000</td>\n",
              "      <td>-0.009900</td>\n",
              "      <td>0.003250</td>\n",
              "      <td>-0.009100</td>\n",
              "      <td>-0.013750</td>\n",
              "      <td>-0.003300</td>\n",
              "      <td>-0.010250</td>\n",
              "      <td>-0.001250</td>\n",
              "      <td>-0.006800</td>\n",
              "      <td>0.014000</td>\n",
              "      <td>-0.019500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>0.525700</td>\n",
              "      <td>0.403075</td>\n",
              "      <td>0.663925</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.465375</td>\n",
              "      <td>0.510425</td>\n",
              "      <td>0.528725</td>\n",
              "      <td>0.411900</td>\n",
              "      <td>0.549225</td>\n",
              "      <td>0.697775</td>\n",
              "      <td>0.525400</td>\n",
              "      <td>0.575275</td>\n",
              "      <td>0.604450</td>\n",
              "      <td>0.575825</td>\n",
              "      <td>0.457975</td>\n",
              "      <td>0.382475</td>\n",
              "      <td>0.829500</td>\n",
              "      <td>0.494775</td>\n",
              "      <td>0.327800</td>\n",
              "      <td>0.400600</td>\n",
              "      <td>0.492400</td>\n",
              "      <td>0.414875</td>\n",
              "      <td>0.433400</td>\n",
              "      <td>0.329250</td>\n",
              "      <td>0.527700</td>\n",
              "      <td>0.461650</td>\n",
              "      <td>0.508425</td>\n",
              "      <td>0.586450</td>\n",
              "      <td>0.431275</td>\n",
              "      <td>0.507600</td>\n",
              "      <td>0.458075</td>\n",
              "      <td>0.471075</td>\n",
              "      <td>0.391950</td>\n",
              "      <td>0.551300</td>\n",
              "      <td>0.503725</td>\n",
              "      <td>0.564875</td>\n",
              "      <td>0.517025</td>\n",
              "      <td>0.460500</td>\n",
              "      <td>0.642300</td>\n",
              "      <td>...</td>\n",
              "      <td>0.452675</td>\n",
              "      <td>0.427675</td>\n",
              "      <td>0.462175</td>\n",
              "      <td>0.447975</td>\n",
              "      <td>0.447150</td>\n",
              "      <td>0.441250</td>\n",
              "      <td>0.470600</td>\n",
              "      <td>0.458550</td>\n",
              "      <td>0.441000</td>\n",
              "      <td>0.460075</td>\n",
              "      <td>0.460950</td>\n",
              "      <td>0.449975</td>\n",
              "      <td>0.445200</td>\n",
              "      <td>0.473200</td>\n",
              "      <td>0.563575</td>\n",
              "      <td>0.456350</td>\n",
              "      <td>0.493400</td>\n",
              "      <td>0.448375</td>\n",
              "      <td>0.451975</td>\n",
              "      <td>0.463075</td>\n",
              "      <td>0.447675</td>\n",
              "      <td>0.462000</td>\n",
              "      <td>0.468900</td>\n",
              "      <td>0.452375</td>\n",
              "      <td>0.460475</td>\n",
              "      <td>0.461675</td>\n",
              "      <td>0.465950</td>\n",
              "      <td>0.463400</td>\n",
              "      <td>0.450075</td>\n",
              "      <td>0.430875</td>\n",
              "      <td>0.457750</td>\n",
              "      <td>0.461500</td>\n",
              "      <td>0.445675</td>\n",
              "      <td>0.452900</td>\n",
              "      <td>0.470900</td>\n",
              "      <td>0.444750</td>\n",
              "      <td>0.465225</td>\n",
              "      <td>0.446400</td>\n",
              "      <td>0.461275</td>\n",
              "      <td>0.438650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.039000</td>\n",
              "      <td>8.257000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>7.282000</td>\n",
              "      <td>7.333000</td>\n",
              "      <td>5.473000</td>\n",
              "      <td>8.887000</td>\n",
              "      <td>6.433000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>4.134000</td>\n",
              "      <td>6.418000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>8.872000</td>\n",
              "      <td>4.081000</td>\n",
              "      <td>9.842000</td>\n",
              "      <td>5.248000</td>\n",
              "      <td>5.942000</td>\n",
              "      <td>5.201000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>8.494000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.416000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>6.796000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>5.834000</td>\n",
              "      <td>5.602000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>3.888000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>4.857000</td>\n",
              "      <td>3.549000</td>\n",
              "      <td>3.382000</td>\n",
              "      <td>3.328000</td>\n",
              "      <td>4.157000</td>\n",
              "      <td>3.736000</td>\n",
              "      <td>3.582000</td>\n",
              "      <td>3.119000</td>\n",
              "      <td>3.323000</td>\n",
              "      <td>5.014000</td>\n",
              "      <td>2.898000</td>\n",
              "      <td>4.185000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>3.276000</td>\n",
              "      <td>4.992000</td>\n",
              "      <td>3.770000</td>\n",
              "      <td>2.851000</td>\n",
              "      <td>3.211000</td>\n",
              "      <td>4.534000</td>\n",
              "      <td>3.890000</td>\n",
              "      <td>3.994000</td>\n",
              "      <td>4.321000</td>\n",
              "      <td>4.020000</td>\n",
              "      <td>3.738000</td>\n",
              "      <td>3.252000</td>\n",
              "      <td>5.406000</td>\n",
              "      <td>3.110000</td>\n",
              "      <td>3.320000</td>\n",
              "      <td>4.069000</td>\n",
              "      <td>3.960000</td>\n",
              "      <td>3.927000</td>\n",
              "      <td>3.596000</td>\n",
              "      <td>3.747000</td>\n",
              "      <td>2.814000</td>\n",
              "      <td>3.505000</td>\n",
              "      <td>2.924000</td>\n",
              "      <td>3.111000</td>\n",
              "      <td>3.805000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 873 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              tempo           g-0  ...          c-98          c-99\n",
              "count  23814.000000  23814.000000  ...  23814.000000  23814.000000\n",
              "mean      48.020156      0.248366  ...     -0.470252     -0.301505\n",
              "std       19.402807      1.393399  ...      1.834828      1.407918\n",
              "min       24.000000     -5.513000  ...    -10.000000    -10.000000\n",
              "25%       24.000000     -0.473075  ...     -0.592600     -0.562900\n",
              "50%       48.000000     -0.008850  ...      0.014000     -0.019500\n",
              "75%       72.000000      0.525700  ...      0.461275      0.438650\n",
              "max       72.000000     10.000000  ...      3.111000      3.805000\n",
              "\n",
              "[8 rows x 873 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2ZabuXjzi5Cn"
      },
      "source": [
        "A função ``` .describe() ``` fornecida pelo Pandas permite a análise dos seguintes parâmetros estatísticos: **Valor total**, **Média**, **Mediana**, **Desvio Padrão**, **Valor Mínimo**, **Valor Máximo** e os **Quartis**. Ou seja a função permite a análise de **Variáveis de Tendência Central**, como também a análise de **Medidas Separatrizes** e **Medidas de Dispersão**.\n",
        "***\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uAE67jFKrf__"
      },
      "source": [
        "### **Medidas de Tendência Central:**\n",
        "***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BRzOShqOpQDF"
      },
      "source": [
        "#### <font color=green>**Média**</font>\n",
        "https://pt.wikipedia.org/wiki/M%C3%A9dia#Defini%C3%A7%C3%A3o_formal\n",
        "\n",
        "É representada por $\\mu$ quando se refere à população e por $\\bar{X}$ quando se refere à amostra\n",
        "\n",
        "#$$\\mu = \\frac 1n\\sum_{i=1}^{n}X_i$$\n",
        "\n",
        "onde \n",
        "\n",
        "$n$ = número de observações (registros)\n",
        "\n",
        "$X_i$ = valor da i-ésima observação (registro)\n",
        "\n",
        "***\n",
        "\n",
        "#### <font color=green>**Médiana**</font>\n",
        "https://pt.wikipedia.org/wiki/Mediana_(estat%C3%ADstica)\n",
        "\n",
        "Para obtermos a mediana de uma conjunto de dados devemos proceder da seguinte maneira:\n",
        "1. Ordenar o conjunto de dados;\n",
        "2. Identificar o número de observações (registros) do conjunto de dados ($n$);\n",
        "3. Identicar o elemento mediano:\n",
        "\n",
        "> Quando $n$ for ímpar, a posição do elemento mediano será obtida da seguinte forma:\n",
        "\n",
        "\n",
        "# $$Elemento_{Md} = \\frac{n+1}2$$\n",
        "\n",
        "> Quando $n$ for par, a posição do elemento mediano será obtida da seguinte forma:\n",
        "\n",
        "\n",
        "# $$Elemento_{Md} = \\frac{n}2$$\n",
        "\n",
        "4. Obter a mediana:\n",
        "\n",
        "> Quando $n$ for ímpar:\n",
        "\n",
        "\n",
        "# $$Md = X_{Elemento_{Md}}$$\n",
        "\n",
        "> Quando $n$ for par:\n",
        "\n",
        "\n",
        "# $$Md = \\frac{X_{Elemento_{Md}} + X_{Elemento_{Md}+1}}2$$\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GQ63XNLbpPRF"
      },
      "source": [
        "### **Medidas Separatrizes:**\n",
        "***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d9qcPQ29rqjA"
      },
      "source": [
        "Há uma série de medidas de posição semelhantes na sua concepção à mediana, embora não sejam medidas de tendência central. Como se sabe, a mediana divide a distribuição em duas partes iguais quanto ao número de elementos de cada parte. Já os quartis permitem dividir a distribuição em quatro partes iguais quanto ao número de elementos de cada uma; os decis em dez partes e os centis em cem partes iguais."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "diyw7oPcr_Et"
      },
      "source": [
        "#### <font color=green>**Quartis**</font>\n",
        "\n",
        "https://pt.wikipedia.org/wiki/Quartil\n",
        "\n",
        "Assim, no caso duma amostra ordenada:\n",
        "\n",
        "*   primeiro quartil (designado por Q1/4) = quartil inferior = é o valor aos 25% da amostra ordenada = 25º percentil\n",
        "*   segundo quartil (designado por Q2/4) = mediana = é o valor até ao qual se encontra 50% da amostra ordenada = 50º percentil, ou 5º decil.\n",
        "*   terceiro quartil (designado por Q3/4) = quartil superior = valor a partir do qual se encontram 25% dos valores mais elevados = valor aos 75% da amostra ordenada = 75º percentil\n",
        "<p><strong>À diferença entre os quartis superior e inferior chama-se amplitude inter-quartil.</strong></p>\n",
        "<img = alt=\"Colaboratory logo\" src=\"https://s3.amazonaws.com/caelum-online-public/856-introducao-python-pandas/09/compressed_box-plot.png\">\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_QLiWQJStmax"
      },
      "source": [
        "### **Medidas de Dispersão**\n",
        "***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jQKTc_octuj2"
      },
      "source": [
        "Embora as medidas de posição forneçam uma sumarização bastante importante dos dados, elas podem não ser suficientes para caracterizar conjuntos distintos, especialmente quando as observações de determinada distribuição apresentarem dados muito dispersos."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pLVa5Jcht_km"
      },
      "source": [
        "#### <font color=green>**Desvio Padrão**</font>\n",
        "\n",
        "https://pt.wikipedia.org/wiki/Desvio_padr%C3%A3o\n",
        "\n",
        "<p>Em probabilidade, o desvio padrão ou desvio padrão populacional (comumente representado pela letra grega sigma) é uma medida de dispersão em torno da média populacional de uma variável aleatória.</p> \n",
        "\n",
        "# $$\\sigma = \\sqrt{\\frac 1n\\sum_{i=1}^{n}(X_i-\\mu)^2} \\Longrightarrow \\sigma = \\sqrt{\\sigma^2}$$\n",
        "\n",
        "<p>O termo possui também uma acepção específica no campo da estatística, na qual também é chamado de desvio padrão amostral (comumente representado pela letra latina s) e indica uma medida de dispersão dos dados em torno de média amostral. Um baixo desvio padrão indica que os pontos dos dados tendem a estar próximos da média ou do valor esperado.Um alto desvio padrão indica que os pontos dos dados estão espalhados por uma ampla gama de valores.</p> \n",
        "\n",
        "# $$S = \\sqrt{\\frac 1{n-1}\\sum_{i=1}^{n}(X_i-\\bar{X})^2} \\Longrightarrow S = \\sqrt{S^2}$$\n",
        "\n",
        "<p>O desvio padrão populacional ou amostral é a raiz quadrada da variância populacional ou amostral correspondente, de modo a ser uma medida de dispersão que seja um número não negativo e que use a mesma unidade de medida dos dados fornecidos.</p>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xL9MuXiw6Q2J"
      },
      "source": [
        "## **Desafio 05: Refletir sobre a manipulação do tamanho das visualizações**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g15E_26wzOS8"
      },
      "source": [
        "### 'Por que ocorreu a distorção?', 'O gráfico estava realmente distorcido?', 'O que realmente significa um gráfico distorcido?'\n",
        "***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5ZPZLjU848qI"
      },
      "source": [
        "<p>A 'distorção' mencionada ocorre principalmente pela grande amplitude dos dados, principalmente aqueles distantes das medidas de tendência central (<em>outliers</em>). Ou seja análisar essa base de dados, com uma grande amplitude torna necessária uma grande área para a melhor visualização desses dados.</p>\n",
        "<p>Isso entretanto não classificaria necessáriamente uma distorção. Um gráfico distorcido na realidade, como aponta a autora do livro <strong>'<em>Storytelling</em> with data' - Cole Nussbaumer Knaflic</strong>, é um gráfico que sugere uma interpretação diferente do que os dados realmente indicam, o que induz a pessoa ao erro ou a uma interpretação equivocada como indicado no exemplo abaixo. No qual a escala dos eixos foi alterada para gerar uma impressão errada ao telespectador.</p>\n",
        "<img src = 'https://flowingdata.com/wp-content/uploads/2012/08/Bush-cuts.png'>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rzPl_cdA6Qg8"
      },
      "source": [
        "## **Desafio 06: Fazer outras análises com o boxplot e até com o histograma** "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "bzikiRUv65vD",
        "outputId": "4cea895d-dce4-4fff-8069-940a2cb30bb6"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Box Plot aplicado ao banco de dados Gerais:\n",
        "ax1 = sns.boxplot(y='g-0', x='tratamento' , data=dados, ax = axs[0])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação ao tratamento (Banco de Dados Geral)', fontsize = 18)\n",
        "\n",
        "#Box Plot aplicado aos cinco principais compostos:\n",
        "ax1 = sns.boxplot(y='g-0', x='tratamento' , data=top_compostos, ax = axs[1])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação ao tratamento (5 Principais Compostos)', fontsize = 18)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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DQ1x44YWxbNmy6NatW/Tr1y8uv/zy2H333XP+XAAAQGGwNRcA0FEHHjigzdY8Bx74jymmgfzr0Mr9QYMG5TpHlJWVxTe/+c14+OGHo66uLvbZZ5+YMmVKzp8HAAAoHJ0xtwAAuoZXX130nvHClJJAOrZ55f7Pf/7z1p8POeSQ1nG3bt2ib9++ccwxx0Tv3r07HKS6ujqOPvro1vHAgQPjjjvu6PDjkY45c/4Qs2c/mXaMgjN58sS0I6SmtnZ4DB06LO0YAEAB6ey5BQDQNdiWh65um8v91157LR599NE47LDDYs8994yVK1fG888/HyNGjIjHH388Lrvssrjmmmti2LAdL/Gy2WzccccdMWLEiB1+LAAoJD4E/WBd9UNQH4DSVeVzbgEAlK5Nmza2O4ZSt83lfjabjauvvjo+97nPtV72X//1X3H//ffHXXfdFTNmzIif/exnOXkDPnHixOjRo0ecccYZ23W/mpqeO/zc7JhTTjkxTjnlxLRjpGrUqFHvu2zKlKtSSAIUot122zkqK60mea+u+jfZbbedY489dk07BuRdPucWAABQqra53J89e3ZMnTq1zWXHHXdcXHjhhRERMXr06Jg4ccdX3U2ePDmWLl0aN9xwQ2Qy23dKgPr6pshmnZCLdA0YcGi8/PILreNDD/1UrFmzPsVEQCE59NCj4tBDj0o7Rqr+4z/+Tzz//LOt40996vD4wQ8uSDFRurxGpC+TKbNIJM/yNbcAAEpbdXWvaGxsaB336rV7imkg/7a5Pd93333ftwf+nXfeGfvuu29ERDQ0NMTOO++8Q2GmTp0aL774Ylx33XXRrVu3HXosSMsFF/ywzfj88y9KKQlAYfrGN775nvG3UkoCpCUfcwsAoPStW9fYZvzuoh+6gm1euf+Tn/wkvv/978dNN90Uffr0idWrV0d5eXlce+21ERGxZMmS+MEPftDhIIsWLYpf/epXsd9++8W4ceMiImLvvfeO6667rsOPCWnp3r17bN68OQ499FNpRwEoONXVvWLnnXvEpk0b41OfOjyqqqrTjgTkWWfPLQCAriFJknbHUOq2udw/+OCD4+GHH47nnnsu3njjjdhjjz1i4MCBUVlZGRERRx11VBx1VMe3GTjggANiwYIFHb4/FJJ+/T4REVbtA3yYvfbaK1aseN2qfeiiOntuEbF19f+FF14Yy5Yti27dukW/fv3i8ssvj91393V9AABKwzaX+xERlZWVMWjQoM7KAgB0ERUVlbHvvvtZtQ9dWGfPLcrKyuKb3/xmHH300RGx9dxeU6ZMiSuuuKLTnhMAAPJp+85YCwAAUASqq6tbi/2IiIEDB8aKFStSTAQAALm1XSv3AQAAik02m4077rgjRowYsc33qanp2YmJ2ldZWZ7acwOFr7KyPPbYY9e0Y1AAZs2aFY8++mjaMQrO1Kld91t6n/vc57br/Q7FT7kPAACUtIkTJ0aPHj3ijDPO2Ob71Nc3RTabzkn5tmxpSeV5geKwZUtLrFmzPu0YFIC//W2T14wP0JX/Jn/72ybHhwKQyZTlbaGIch8AAChZkydPjqVLl8YNN9wQmYxdSQEoHUOHDouhQ4elHSNV11//83jmmadbx4MGHR3f+c4PUkwE+eXdLQAAUJKmTp0aL774Ylx33XXRrVu3tOMAADl2+ulfbzP+6lf/OaUkkA4r9wEAgJKzaNGi+NWvfhX77bdfjBs3LiIi9t5777juuutSTgYA5Ep1da/YZZeesWFDUwwadHRUVVWnHQnySrkPAACUnAMOOCAWLFiQdgwAoJP17ds3Vqx43ap9uiTb8gAAAAAARamiojL23Xc/q/bpkpT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZJT7AAAAAABQZCrSDlAqbr/9/8by5UvTjkGBWLZs67+FyZMnppyEQrHPPv3i9NO/nnYMAAAAAEqEcj9Hli9fGgsWvRrl3avTjkIByLaUR0TEq8vfTDkJhaBlc2PaEQAAAAAoMcr9HCrvXh09+h2fdgygwGxc+ljaEQAAAAAoMcp9APLC9mW8m+3LeDdblwEAAGw/5T4AebF8+dJ47dVXom9PLz1E9IhsRERsXvVqyklI26qm5rQjAAAAFCUNCwB507dnRfzLYbunHQMoINOeX5t2BAAAgKKUSTsAAAAAAACwfazcBwAAKDAtmxtj49LH0o5BAcg2b46IiExF95STUAhaNjdGRO+0YwBQIJT7AAAABWSfffqlHYEC8s5J6PfdR6FLRERvxwgAWhVUub9kyZIYP358NDY2RnV1dUyePDn222+/tGMBAADkzemnfz3tCBSQyZMnRkTERRf9e8pJAIBCU1B77l9yySVx+umnx8MPPxynn356TJgwIe1IAAAAAABQcAqm3K+vr4+XXnopTjrppIiIOOmkk+Kll16KtWvXppwMAAAAAAAKS8Fsy7Ny5cro06dPlJeXR0REeXl5fOxjH4uVK1fG7rvvnnK6j7ZuXaOTXgEfqGVzY6xbVzCHWwAAgKJ2++3/N5YvX5p2DArEO+cmeWcbM9hnn35dZpvDkmqbamp6pvbc5eUF8yUIoACVl2dijz12TTtGqiory2Nz2iGAglRZWd7lj5EAwLZbvnxpvPbqK9G3Z0nVWnRQj8hGRMTmVa+mnIRCsKqpOe0IeVUwR8E999wzVq9eHS0tLVFeXh4tLS3xxhtvxJ577rnNj1Ff3xTZbNKJKT9cz567RXn3t6NHv+NTeX6gcG1c+lj07LlbrFmzPu0oqdqypSXtCECB2rKlJdVjZCZTluoiEQBg+/XtWRH/cljh7/QA5Ne057vWFu8FU+7X1NTEgAED4v7774+TTz457r///hgwYEBRbMkDwEdbt64xGpqau9wLLdC+VU3N0WtdY9oxAAAAik7BlPsREZdeemmMHz8+rr/++thtt91i8uTJaUcCAAAAAICCU1Dl/v777x9333132jEA6ARVVdWx06Y3fXUWaGPa82uje1V12jEAAACKjrPAAgAAAABAkVHuAwAAJWnJkiXx5S9/OT7/+c/Hl7/85XjttdfSjgQAADmj3AcAAErSJZdcEqeffno8/PDDcfrpp8eECRPSjgQAADmj3AcAAEpOfX19vPTSS3HSSSdFRMRJJ50UL730UqxduzblZAAAkBsFdULdYteyuTE2Ln0s7RgUgGzz5oiIyFR0TzkJhaBlc2NE9E47BgB0KStXrow+ffpEeXl5RESUl5fHxz72sVi5cmXsvruTuwMAUPyU+zmyzz790o5AAVm2bGlEROy7j0KXiIjejhEAUGRqanqmHQEiIqKycusHVHvssWvKSaBwVFaWx+a0QwAFq7KyvMu8bir3c+T007+edgQKyOTJEyMi4qKL/j3lJAAAXdOee+4Zq1evjpaWligvL4+WlpZ44403Ys8999ym+9fXN0U2m3RySvhoW7a0RETEmjXrU04CheOd/xcAH2TLlpZUXzczmbK8LRRR7gMAACWnpqYmBgwYEPfff3+cfPLJcf/998eAAQNsyQNQAtata4yGpuaY9rzzqABtrWpqjl7rGtOOkTfKfQDyZpU34Pxd09vZiIjo2S2TchLStqqpOfZLOwQl69JLL43x48fH9ddfH7vttltMnjw57UgAAJAzyn0A8sJ5B3i3N/5+bpLeff276Or2C8cHOs/+++8fd999d9oxAMixqqrq2GnTm/Evh/k2FtDWtOfXRveq6rRj5I1yH4C8cG4S3s25SQAAAGDH+C48AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUGeU+AAAAAAAUmYq0AwAAAADA9ljV1BzTnl+bdgwKQNPb2YiI6NnNGma2Hhv2SztEHin3AQAAACga++zTL+0IFJA3li2NiIjeff27IGK/6FrHCOU+AAAAAEXj9NO/nnYECsjkyRMjIuKii/495SSQf76vAgAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5D51g9epVsWDByzFjxl1pRwEAAAAASlBBlPuXXXZZnHDCCTF69OgYN25cvPDCC2lHgh3S2NgQERF1dfelnAQAAAAAKEUFUe4PGzYs6urqYubMmXHOOefE+eefn3Yk6LC7776zzdjqfQAAAAAg1yrSDhARcdxxx7X+PHDgwFi1alVks9nIZAriswe2w5w5f4jZs59MO0aqFix4uc24ru6+WLhwQUpp0ldbOzyGDh2WdgwAAAAAKCkF157fdtttceyxxyr2AQAAAADgQ+Rl5f6YMWNixYoVH3jd3Llzo7y8PCIiHnjggairq4vbbrutQ89TU9OzwxnJjVNOOTFOOeXEtGOkatSoUe+7bMqUq1JIAlC4Kiu3vvbvsceuKScBAACA4pSXcn/GjBkfeZtHH300rr766rj55pujd+/eHXqe+vqmyGaTDt0XOtOaNevTjgBQULZsaYkIx0cKQyZTZpEIAABQdApiz/3HH388rrzyypg2bVrsvffeaccBgE7j3CRbLVu2NCIiJk+emHKSdDkvCQAAAB1VEOX+D3/4w6isrIzzzjuv9bKbb745evXqlWIqAKCzVFVVpR0BAAAAilpBlPvz589POwIA5MXQocOs1I6IxsaGuOGGa+Pb3/5+VFVVpx0HAAAAik4m7QAAQNdTVzcjFi1aEDNn3pt2FAAAAChKyn0AIK8aGxviqaeejCRJYvbsJ2Pdusa0IwEAAEDRUe4DAHlVVzcjWlqaIyKiubnZ6n0AAADoAOU+AJBXc+fOjiRJIiIiSZKYO3d2yomAUnPZZZfFCSecEKNHj45x48bFCy+8kHYkAADIOeU+AJBXNTU17Y4BdtSwYcOirq4uZs6cGeecc06cf/75aUcCAICcq0g7AADQtdTX17c7BthRxx13XOvPAwcOjFWrVkU2m41MxtomAABKh3e3AEBeDRlSGxFlfx+V/X0M0Dluu+22OPbYYxX7AACUHCv3AYC8GjVqTDz11BPR3NwcFRUVMXr0qWlHAorMmDFjYsWKFR943dy5c6O8vDwiIh544IGoq6uL2267bbufo6am5w5lhFyprNz673mPPXZNOQlAYXKcpCtT7gMAeVVd3SuOOebYeOKJx+KYY4ZHVVV12pGAIjNjxoyPvM2jjz4aV199ddx8883Ru3fv7X6O+vqmyGaTjsSDnNqypSUiItasWZ9yEoDC5DhJoclkyvK2UES5DwDk3ahRY+L11/9q1T7QKR5//PG48sorY9q0abH33nunHQcAOsWcOX+I2bOfTDtG6pYtWxoREZMnT0w5Sfpqa4fH0KHD0o5BHin3Icf22ONjsWbNG23GALRVXd0rxo+fkHYMoET98Ic/jMrKyjjvvPNaL7v55pujV69eKaYCADpDVVVV2hEgNcp9yLE99/x4m3L/4x//eIppAAC6nvnz56cdAQA63dChw6zSjojGxoa44YZr49vf/r4tP+lyMmkHgFLz4ovPtRk///xzH3JLAAAAAHZEXd2MWLRoQcyceW/aUSDvlPuQY9lstt0xAAAAADuusbEhnnrqyUiSJGbPfjLWrWtMOxLklXIfAAAAACg6dXUzoqWlOSIimpubrd6ny1HuQ46VlZW1OwYAAABgx82dOzuSJImIiCRJYu7c2SkngvxS7kOOvfOi8mFjAAAAAHZcTU1Nu2Modcp9yLGysky7YwAAAAB2XH19fbtjKHVaR8ixnXbaqd0xAAAAADtuyJDaiHhnO+Syv4+h61DuQ45t3ryp3TEAEY2NDTFp0uWxbl1j2lEAAIAiNWrUmKioKI+IiIqKihg9+tSUE0F+KfcBgLybPv3OWLjwlbj77jvSjgIAABSp6upeccwxx0ZZWVkcc8zwqKqqTjsS5FVF2gEAgK6lsbEh5s2bHRER8+bNidNO+4o34QC8z5w5f4jZs59MO0bqli1bGhERkydPTDlJ+mprh8fQocPSjgEUmFGjxsTrr//Vqn26JCv3Icf69Nmz3TFAVzd9+p2RJElERCRJ1up9AGhHVVVVVFVVpR0DoGBVV/eK8eMnWDBEl1SWvDO7LgH19U2RzZbMr0ORWrbstbj00h+1ji+77MrYZ59+KSYCKCzf+tbXoqWlpXVcXl4eN910S4qJ6OoymbKoqemZdgwKjLkFAAAdkc/5hZX7kGO77VbV7hgAAAAAYEcp9yHH6upmRCaz9b9WJpOJmTPvTTkRQGE5+ughbcaf+czQlJIAAABA8VLuQ47NmzcnstlsRERks9mYN29OyokACsvYsePafAg6duy4lBMBAABA8VHuQ44NHjw0MpnyiIjIZMpj8GArUgHerbq6V+tq/cGDa534CgAAADpAuQ85NmrUmEiSrSv3kySJ0aNPTTkRQOEZO3Zc9O9/kFX7AAAA0EEVaQeAUlRWVhZJkkRZWdpJAApTdXWvGD9+QtoxAAAAoGhZuQ85Vlc3I8r+3uqXlZU5oS4AAAAAkHPKfcixefPmREtLS0REtLS0OKEuAAAAAJBzyn3IscGDh0Z5+dYdr8rLK5xQFwAAAKCTNDY2xKRJl8e6dY1pR4G8U+5Djo0aNSYyma3b8mQyGSfUBQAAAOgk06ffGQsXvhJ3331H2lEg75T7kGPV1b2itnZ4lJWVRW3tsKiqqk47EgAAAEDJaWxsiHnzZkfE1m2Srd6nq1HuQycYPnxEdO/ePY499vi0owAAAACUpOnT74wkSSIiIkmyVu/T5RRUuf/000/HgAED4tZbb007CuyQRx75fWzatCkeeeT3aUcBAAAAKElPPz233TGUuoIp95uammLKlCkxbNiwtKPADtn6lbA5ERExb95sXwkDAAAAAHKuYMr9SZMmxVlnnRW9evVKOwrskK1fCctGREQ2m43p0+9MOREAAABA6Tn66CFtxp/5zNCUkkA6KtIOEBHx5JNPxvr16+OEE06IJ554osOPU1PTM3ehoIPe+xWw+fPnxPjxF6SUBgAAAKA0jR07LubPnxPZbDYymUyMHTsu7UiQV3kp98eMGRMrVqz4wOseeuih+NnPfhbTpk3b4eepr2+KbDbZ4ceBHdHS0vK+8Zo161NKAwB8lEymzCIRAIAiVF3dKz7zmaExd+5TMXhwbVRVVacdCfIqL+X+jBkzPvS6Z555JtasWROnnXZaREQ0NDTE448/Ho2NjfG9730vH/EgpzKZTGSz2TZjAAAAAHJv7Nhx8eaba6zap0sqS5KkoJa6jx8/Pg455JA444wztvu+Vu5TCH7961/G3LlPtY6HDDkmvvnNc1NMBAC0x8p9Poi5BQAAHZHP+YUlxZBj7/2k+LTTvpJSEgAAAACgVBXECXXfbdKkSWlHAAAAAACAgmblPuRYXV3bc0zMnHlvSkkAAAAAgFKl3Iccmzt3drtjAAAAAIAdpdyHHKupqWl3DAAAAACwo5T7kGP19fXtjgEAAAAAdpRyH3Ls0EM/1WZ82GGf+pBbAgDQmZ5++ukYMGBA3HrrrWlHAQCAnFPuQ4699tqSNuMlS5Z8yC0BAOgsTU1NMWXKlBg2bFjaUQAAoFMo9yHH3nzzjXbHAAB0vkmTJsVZZ50VvXr1SjsKAAB0CuU+AABQUp588slYv359nHDCCWlHAQCATlORdgAoNWVlmUiSbJsxAAC5M2bMmFixYsUHXvfQQw/Fz372s5g2bdoOPUdNTc8duj8AAHQ25T7k2ODBQ2Pu3KfajAEAyJ29KTR0AAAS20lEQVQZM2Z86HXPPPNMrFmzJk477bSIiGhoaIjHH388Ghsb43vf+942P0d9fVNks8kOZwUAoGvJZMrytlCkLEmSknnH6g04haCxsSH+9V+/2zq++urro6qqOsVEAIWnsbEhbrjh2jj33PMcI0ldPt98k3/jx4+PQw45JM4444ztup+5BQAAHZHP+YX9QiDHqqt7RZ8+e0ZERJ8+eyqtAD5AXd2MWLRoQcyceW/aUQAAAKAoKfchxxobG6K+/s2IiFi79s1Yt64x5UQAhaWxsSFmz34ykiSJ2bP/4DgJdKpJkyZt96p9AAAoBsp9yLG6uhmtJ9TNZrNWpQK8R13djNatLhwnAQAAoGOU+5Bj8+bNiZaWloiIaGlpiXnz5qScCKCwbD1ONkdEREtLs+MkAAAAdIByH3LsiCMGtRkfeeRRKSUBKEyDBw+N8vKKiIgoL6+IwYOHppwIAAAAio9yHzpZkiRpRwAoKKNGjYlMpiwiIjKZTIwefWrKiQAAAKD4KPchx/70p2faHQN0ddXVvaK2dniUlZVFbe2wqKqqTjsSAAAAFB3lPuTYe7eXsN0EwPuNGjUmDjjgQKv2AQAAoIOU+5Bjw4ePaDM+9tjjU0oCULiqq3vF+PETrNoHAACADlLuQ47df//v3jO+L6UkAAAAAECpUu5Djv3xj/+vzfiZZ/7fh9wSAAAAAKBjlPuQY0mStDsGAAAAANhRyn3IsT59+rY7BgAAAADYUcp9yLEzzvhGm/HXvnZmOkEAAAAASlxjY0NMmnR5rFvXmHYUyDvlPuTYn/70TJvxe/fgBwAAACA36upmxKJFC2LmzHvTjgJ5p9yHHJs7d3a7YwAAAAB2XGNjQ8ye/WQkSRKzZ//B6n26HOU+5FhNTU27YwAAAAB2XF3djMhmk4iIyGazVu/T5Sj3Icfq6+vbHQMAAACw4+bNmxMtLc0REdHS0hzz5s1JORHkl3IfcmzIkNqIKPv7qOzvYwAAAAByafDgoVFeXhEREeXlFTF48NCUE0F+Kfchx0aNGhMVFeUREVFRURGjR5+aciIAAACA0jNq1JjIZLYusMxkMjoYuhzlPuRYdXWvOOaYY6OsrCyOOWZ4VFVVpx0JAAAAoORUV/eK2trhUVZWFrW1w3QwdDkVaQeAUjRq1Jh4/fW/+sQYAAAAoBPpYOjKypIkSdIOkSv19U2tZ8gGAIBtkcmURU1Nz7RjUGDMLQAA6Ih8zi9sywMAAAAAAEWmYLblueWWW+K2226LysrKyGQy8bvf/S7tSAAAAAAAUJAKotx/5JFH4qGHHorp06dHz549480330w7EgAAAAAAFKyC2Jbnt7/9bXzve9+Lnj237kXUu3fvlBMBAAAAAEDhKohyf/HixfHcc8/FuHHj4tRTT4277ror7UgAAAAAAFCw8rItz5gxY2LFihUfeN3cuXOjpaUlVq5cGbfffns0NDTEV77ylfjEJz4RRx111HY9T77OQgwAAAAAAGnKS7k/Y8aMdq/fa6+94qSTTopMJhM1NTUxZMiQeP7557e73K+vb4psNtmRqAAAdDGZTJlFIgAAQNEpiG15TjrppHjqqaciImLjxo3xxz/+MQ466KCUUwEAAAAAQGEqiHL/G9/4RqxcuTJOPPHEOO2002LUqFExdOjQtGMBAAAAAEBBKkuSpGT2sbEtDwAA28u2PHwQcwsAADoin/OLvOy5ny+ZTFnaEQAAKDLeQ/JB/LsAAKAj8vk+sqRW7gMAAAAAQFdQEHvuAwAAAAAA2065DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5DwAAAAAARUa5D3kwYsSIWLhwYdoxAIratddeG2+//XaH7zt58uQcJwKA/DO3ANhx5haUCuU+pKi5uTntCABF4xe/+EVs2bLlA69zPAWgq/NaCLDtzC0oFRVpB4B8ePbZZ+Oqq66KDRs2RETEhRdeGLvttlv89Kc/jY0bN0aPHj3ixz/+cRx22GHx17/+Nb74xS/Gl770pXjqqadi8+bNMWXKlLjzzjvjueeei+7du8f1118fe+yxx4c+3zPPPBOXXXZZREQcddRRkSRJ63UjRoyIkSNHxvz586N///7x4x//OH7yk5/ECy+8EBERJ598cnzrW9+KiIhXX301fvjDH8amTZvioIMOimXLlsW5554bxx13XPz2t7+NBx54IFpaWmKnnXaKSy+9NAYMGNBZf0KgBOT7WLh48eL46U9/GmvWrImIiDPPPDPGjBkTS5cujQkTJsTatWujoqIizj///Bg2bFhERBx44IFx/vnnx6OPPhqNjY1x4YUXxuc///nWY+q4ceMik8nELbfcEldccUWUl5fHkiVLYsOGDfG73/0ubrzxxpg5c2ZERBx66KFx8cUXxy677PK+bDfeeGM88sgj0dLSEn369ImJEye2+7sAwDvMLQDMLd7N3IJUJVDiGhoakiFDhiR//OMfkyRJkubm5mTNmjXJ8OHDk7lz5yZJkiRz5sxJhg8fnrz11lvJ8uXLk/79+yePP/54kiRJctNNNyVHHnlk8tJLLyVJkiSXXHJJMnXq1A99vrfeeiupra1N5s+fnyRJkjzwwANJ//79kwULFiRJkiTHHXdccskll7Te/qqrrkouvPDCJJvNJuvXr09GjhyZPPHEE0mSJMmYMWOS++67L0mSJHn++eeTgw46KJk1a1aSJElSX1/f+hhz5sxJTjvttB39UwElLN/Hwi1btiT/9E//lDz44IOtl61duzZJkiQZO3ZsctdddyVJkiSLFi1KPv3pT7ce0/r375/ccsstSZIkyTPPPJPU1ta23r9///5JU1NT6/iiiy5KxowZk2zYsCFJkiR54oknkhNPPDFZv359ks1mkwsuuCC56qqrkiRJkmuuuSaZNGlSkiRJct999yUXX3xx0tLSkiRJktx2223Jv/7rv2733xSArsfcAsDcwtyCQmJbHkren//859h///3jiCOOiIiI8vLyqK+vj8rKyhg8eHBERAwZMiQqKytjyZIlERHRo0ePOPbYYyMi4uCDD46+ffu2rlw5+OCDY9myZR/6fP/zP/8TO++8cxx99NERETFy5MjYdddd29zmlFNOaf153rx5cdppp0VZWVn07NkzTjzxxJg3b140NTXFwoULY9SoURGx9VPiAw88sPV+L774Ynz1q1+Nk046Ka688sp4+eWXd+TPBJS4fB8LlyxZEs3NzfGFL3yh9bJevXpFU1NTvPzyy/HFL34xIiI++clPxoABA+LPf/5z6+1GjhwZEREDBw6MN954I956660PfZ4TTjghevToERFbj6cjR46Mnj17RllZWXzpS1+KefPmve8+s2bNirlz58aYMWPi5JNPjttvvz1ef/319v+AABDmFgAR5hbvZm5B2mzLAx+gW7durT9nMpk24/Ly8mhpadmuxysrK2szfufFoiP3jYh4++234wc/+EHceuutcfDBB8fq1atbv3YGkCu5PhZuq5122qn1OSK27nn5zmXvtT3H03ckSRLnnntujB07tuMhAWAbmVsAmFtAZ7Fyn5I3cODAWLx4cTz77LMREdHS0hI1NTWxZcuWmD9/fkRs/US2ubk5PvGJT+zw8/3DP/xDbN68OZ555pmIiHjooYfib3/724fefvDgwXHPPfdEkiTR1NQUDz74YAwZMiR69uwZBxxwQNx///0REfGXv/wlFi5cGBFb34A3NzfHnnvuGRERt99++w7nBkpbvo+Fn/jEJ6KioiJ+//vft17W0NAQPXv2jAEDBsSMGTMiYuvema+88koMHDjwIx9zl112iaampg+9fvDgwfH73/8+mpqaIkmSmD59egwZMuR9txsxYkTcfvvtsW7duojYekx95ZVXtvdXBKALMrcAMLd4N3ML0mblPiWvuro6rr322pg0aVJs3LgxMplMXHTRRXHNNde0OdHLz3/+8zafHHdUt27dYurUqW1OerXXXnt96O2/853vxMSJE1u/Ijt69OjWlTKTJ0+OH/3oR3HjjTdG//79o3///rHrrrtGz54947zzzouxY8dGdXV1fP7zn9/h3EBpy/exsKKiIq6//vq4/PLL4/rrr4+ysrI488wz45RTTokpU6bEhAkT4uabb46Kioq46qqrYvfdd//IxzzzzDPj61//enTv3j1uueWW910/fPjwWLBgQYwbNy4iIg455JA499xz33e7U045JRobG+OMM86IiK2rbb7yla/EQQcdtIO/NQClztwCwNzi3cwtSFtZkiRJ2iGAD7Zhw4bo0aNHlJWVxauvvhpf+9rX4qGHHoqqqqq0owEAAEXE3AIASo+V+1DAnn322bjqqqvinc/gJk6c6M03AACw3cwtAKD0WLkPHXT33XfHrbfe+r7LJ02a1HrGd4BS51gIADvO6ymAYyF0hHIfAAAAAACKTCbtAAAAAAAAwPZR7gMAAAAAQJFR7gMAAAAAQJFR7gPkwYgRI2Lu3Lkdvv/48ePj6quvzmGi3CnkbAAAUGrMLQB4h3IfIGXNzc1pRwAAAEqAuQVA16LcB+hkF1xwQaxYsSK+/e1vx+GHHx433XRTHHjggXH33XfHscceG//8z/8cERHnnXdeDB06NI488sj46le/GosWLYqIiP/8z/+Murq6+M1vfhOHH354fPvb346IiBtvvDE++9nPxuGHHx4jR46MRx99tPU577333hg3blxcccUVMWjQoDj++OPjT3/6U9x7770xfPjwGDx4cMyYMaP19m+//XZMnjw5jj322BgyZEhMmDAhNm/eHBERTz/9dAwbNix++9vfxuDBg6O2tjbuueeedrMtXrw4vva1r8WgQYPixBNPjMcee6zz/9AAAFDizC3MLQDaSADodMcdd1wyZ86cJEmSZPny5Un//v2TCy64INmwYUOyadOmJEmS5O67707Wr1+fvPXWW8lPfvKTZPTo0a33v+iii5KpU6e2ecwHH3wwWbVqVdLS0pI88MADyac+9alk9erVSZIkyT333JMMGDAgmT59etLc3JxMnTo1GT58eHLppZcmb731VvLUU08lAwcOTJqampIkSZKf/vSnyTnnnJM0NDQk69evT84555xkypQpSZIkyfz585MBAwYk//Ef/5G8/fbbyRNPPJEcdthhSWNj4wdme/vtt5PPfvazyS9/+cvkrbfeSubOnZsMHDgwWbx4cSf9dQEAoOswtzC3AHiHlfsAKfn+978fPXr0iO7du0dExNixY6Nnz57RrVu3+P73vx+vvPJKrF+//kPv/4UvfCH69OkTmUwmRo4cGf369Yvnn3++9fq99947vvjFL0Z5eXmMHDkyVq5cGd/97nejW7duUVtbG926dYtly5ZFkiRx1113xY9+9KOorq6Onj17xjnnnBMPPPBA62NVVFTEd7/73aisrIzhw4dHjx49YsmSJR+Y67nnnouNGzfG2WefHd26dYvBgwfHcccd1+bxAACA3DG3AOiaKtIOANBV9e3bt/XnlpaWuPrqq+Ohhx6KtWvXRiaz9bPXhoaG2HXXXT/w/vfdd19MmzYtXn/99YiI2LhxYzQ0NLReX1NT0/rzO2/ye/fu3XrZTjvtFBs2bIi1a9fGpk2b4tRTT229LkmSyGazrePq6uqoqPjfl4ydd945Nm7c+IG53njjjejbt2/r7xARsddee8Xq1avb+WsAAAAdZW4B0DUp9wFSUlZW1vpzXV1dPPbYYzFt2rTYe++9Y/369XHUUUdFkiTvu21ExOuvvx4XX3xx3HzzzXH44YdHeXl5nHzyyR3K0atXr+jevXs88MAD0adPnx36PSIiPvaxj8WqVasim822vglfuXJl7Lfffh3KBwAAtM/cAqBrsi0PQB707t07li9f/qHXb9iwIbp16xa9evWKTZs2xdSpU9tcX1NTE3/9619bx5s2bYqysrLYfffdIyLinnvuaT1J1vbKZDJx2mmnxRVXXBH19fUREbF69ep46qmntun+78122GGHRffu3ePXv/51bNmyJZ5++umYNWtWjBw5skP5AACA/2VuYW4B8A7lPkAenH322fHLX/4yBg0aFA8//PD7rj/llFNir732imOOOSZOPPHEGDhwYJvrx44dG6+++moMGjQovvOd78QnP/nJOPPMM2PcuHExZMiQWLhwYRxxxBEdznfBBRdEv3794ktf+lIcccQR8Y1vfOND9718r/dm69atW9xwww3xhz/8IT7zmc/EZZddFldddVXsv//+Hc4HAABsZW5hbgHwjrLkne9lAQAAAAAARcHKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDLKfQAAAAAAKDL/PyVpxa7uP7UdAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "9AgHuGVH7QbR",
        "outputId": "b4c78ba8-f795-4c9a-c726-9d8392a6f89f"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Box Plot aplicado ao banco de dados Gerais:\n",
        "ax1 = sns.boxplot(y='g-0', x='dose' , data=dados, ax = axs[0])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação à dosagem (Banco de Dados Geral)', fontsize = 18)\n",
        "\n",
        "#Box Plot aplicado aos cinco principais compostos:\n",
        "ax1 = sns.boxplot(y='g-0', x='dose' , data=top_compostos, ax = axs[1])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação à dosagem (5 Principais Compostos)', fontsize = 18)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "id": "mQc5feD-7UWT",
        "outputId": "4fcf83b6-67c3-4128-8295-4135ce7ff2b7"
      },
      "source": [
        "# Criação do Canva:\n",
        "fig, axs = plt.subplots(figsize = (26, 7), ncols = 2)\n",
        "\n",
        "#Box Plot aplicado ao banco de dados Gerais:\n",
        "ax1 = sns.boxplot(y='g-0', x='tempo' , data=dados, ax = axs[0])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação ao tempo (Banco de Dados Geral)', fontsize = 18)\n",
        "\n",
        "#Box Plot aplicado aos cinco principais compostos:\n",
        "ax1 = sns.boxplot(y='g-0', x='tempo' , data=top_compostos, ax = axs[1])\n",
        "ax1.set_title('Comportamento do \"g-0\" em relação ao tempo (5 Principais Compostos)', fontsize = 18)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1872x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WqOCaTaL6cKk"
      },
      "source": [
        "## **Desafio 07: Resumo do que você aprendeu com os dados**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fIKDHa0g7rJR"
      },
      "source": [
        "Nessa análise dos dados foi possível desenvolver sobre:\n",
        "\n",
        "*   As impotancias de ter uma boa visualização, e como isso vai além dos efeitos cosméticos.\n",
        "*   Refletir sobre outros conceitos de visualização como distorção de dados e melhora de representatividade.\n",
        "*   Análisar dentro do banco de dados as medidas de tendência central, medidas separatrizes e medidas de dispersão, fornecidas pelo ```.describe()```\n",
        "*   Compreensão maior do que se tratam os 'g's e os 'c's e seu comportamento ao longo da distribuição das amostras."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mWTGrmZ2xKW2"
      },
      "source": [
        "# **Referências**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ia-3cdc3xPDe"
      },
      "source": [
        "*    https://cursos.alura.com.br/course/introducao-python-pandas\n",
        "*    https://cursos.alura.com.br/course/estatistica-distribuicoes-e-medidas\n",
        "*    https://pt.wikipedia.org/wiki/M%C3%A9dia\n",
        "*    https://pt.wikipedia.org/wiki/Mediana_(estat%C3%ADstica)\n",
        "*    https://pt.wikipedia.org/wiki/Quartil\n",
        "*    https://pt.wikipedia.org/wiki/Desvio_padr%C3%A3o"
      ]
    }
  ]
}