Aula_02_Dados_Italo.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Aula_02_Dados_Italo.ipynb","provenance":[{"file_id":"1iy41ZJY2N0K9TvhZKOgjO58WjC7atXHQ","timestamp":1619537154579},{"file_id":"1I0QF_X7fykLHQdVcXPtF8tGa1qTbDLxM","timestamp":1619099732888}],"collapsed_sections":["UIsjjtsF74vf"]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","metadata":{"id":"UIsjjtsF74vf"},"source":["#Aula 01"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"jw4JmFUsNPwq","executionInfo":{"status":"ok","timestamp":1620127784048,"user_tz":180,"elapsed":6744,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"0171b196-66dc-4197-bb44-4288e31ab049"},"source":["import pandas as pd\n","\n","url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n","\n","dados = pd.read_csv(url_dados, compression = 'zip')\n","dados"],"execution_count":1,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>droga</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","  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<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","      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<td>0.3055</td>\n","      <td>-0.4726</td>\n","      <td>0.1269</td>\n","      <td>0.2531</td>\n","      <td>0.1730</td>\n","      <td>-0.4532</td>\n","      <td>-1.0790</td>\n","      <td>0.2474</td>\n","      <td>-0.4550</td>\n","      <td>0.3588</td>\n","      <td>0.1600</td>\n","      <td>-0.7362</td>\n","      <td>-0.1103</td>\n","      <td>0.8550</td>\n","      <td>-0.4139</td>\n","      <td>0.5541</td>\n","      <td>0.2310</td>\n","      <td>-0.5573</td>\n","      <td>-0.4397</td>\n","      <td>-0.9260</td>\n","      <td>-0.2424</td>\n","      <td>-0.6686</td>\n","      <td>0.2326</td>\n","      <td>0.6456</td>\n","      <td>0.0136</td>\n","      <td>-0.5141</td>\n","      <td>-0.6320</td>\n","      <td>0.7166</td>\n","      <td>...</td>\n","      <td>0.0807</td>\n","      <td>0.4024</td>\n","      <td>-0.0895</td>\n","      <td>0.4420</td>\n","      <td>0.9641</td>\n","      <td>-0.1846</td>\n","      <td>-0.0014</td>\n","      <td>0.3154</td>\n","      <td>-0.2071</td>\n","      <td>-0.6158</td>\n","      <td>-0.2977</td>\n","      <td>0.0992</td>\n","      <td>0.6838</td>\n","      <td>0.5259</td>\n","      <td>0.7882</td>\n","      <td>0.3119</td>\n","      <td>-0.7697</td>\n","      <td>0.2203</td>\n","      <td>-1.0710</td>\n","      <td>0.5979</td>\n","      <td>0.0848</td>\n","      <td>-0.2555</td>\n","      <td>0.6293</td>\n","      <td>1.1660</td>\n","      <td>0.3329</td>\n","      <td>0.2754</td>\n","      <td>0.4108</td>\n","      <td>-0.1252</td>\n","      <td>-0.2340</td>\n","      <td>0.2267</td>\n","      <td>0.1969</td>\n","      <td>0.0262</td>\n","      <td>-0.8121</td>\n","      <td>0.3434</td>\n","      <td>0.5372</td>\n","      <td>-0.3246</td>\n","      <td>0.0631</td>\n","      <td>0.9171</td>\n","      <td>0.5258</td>\n","      <td>0.4680</td>\n","    </tr>\n","    <tr>\n","      <th>23810</th>\n","      <td>id_fffb70c0c</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D2</td>\n","      <td>ecf3b6b74</td>\n","      <td>-1.3260</td>\n","      <td>0.3478</td>\n","      <td>-0.3743</td>\n","      <td>0.9905</td>\n","      <td>-0.7178</td>\n","      <td>0.6621</td>\n","      <td>-0.2252</td>\n","      <td>-0.5565</td>\n","      <td>0.5112</td>\n","      <td>0.6727</td>\n","      <td>-0.1851</td>\n","      <td>2.8650</td>\n","      <td>-0.2140</td>\n","      <td>-0.6153</td>\n","      <td>0.8362</td>\n","      <td>0.5584</td>\n","      <td>-0.2589</td>\n","      <td>0.1292</td>\n","      <td>0.0148</td>\n","      <td>0.0949</td>\n","      <td>-0.2182</td>\n","      <td>-0.9235</td>\n","      <td>0.0749</td>\n","      <td>-1.5910</td>\n","      <td>-0.8359</td>\n","      <td>-0.9217</td>\n","      <td>0.3013</td>\n","      <td>0.1716</td>\n","      <td>0.0880</td>\n","      <td>0.1842</td>\n","      <td>0.1835</td>\n","      <td>0.5436</td>\n","      <td>-0.0533</td>\n","      <td>-0.0491</td>\n","      <td>0.9543</td>\n","      <td>...</td>\n","      <td>0.1410</td>\n","      <td>1.2640</td>\n","      <td>-0.8663</td>\n","      <td>0.8129</td>\n","      <td>-0.1514</td>\n","      <td>-0.4652</td>\n","      <td>-0.7390</td>\n","      <td>-1.3270</td>\n","      <td>0.9925</td>\n","      <td>1.0570</td>\n","      <td>-0.3355</td>\n","      <td>-0.2555</td>\n","      <td>0.8219</td>\n","      <td>0.6995</td>\n","      <td>-0.2942</td>\n","      <td>0.2408</td>\n","      <td>-0.7781</td>\n","      <td>-0.0929</td>\n","      <td>-0.0329</td>\n","      <td>0.0781</td>\n","      <td>-1.4440</td>\n","      <td>-0.0921</td>\n","      <td>0.3188</td>\n","      <td>-1.1080</td>\n","      <td>0.4895</td>\n","      <td>-0.2144</td>\n","      <td>1.0960</td>\n","      <td>0.3335</td>\n","      <td>0.4444</td>\n","      <td>-1.1130</td>\n","      <td>0.4286</td>\n","      <td>0.4426</td>\n","      <td>0.0423</td>\n","      <td>-0.3195</td>\n","      <td>-0.8086</td>\n","      <td>-0.9798</td>\n","      <td>-0.2084</td>\n","      <td>-0.1224</td>\n","      <td>-0.2715</td>\n","      <td>0.3689</td>\n","    </tr>\n","    <tr>\n","      <th>23811</th>\n","      <td>id_fffc1c3f4</td>\n","      <td>com_controle</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>cacb2b860</td>\n","      <td>0.3942</td>\n","      <td>0.3756</td>\n","      <td>0.3109</td>\n","      <td>-0.7389</td>\n","      <td>0.5505</td>\n","      <td>-0.0159</td>\n","      <td>-0.2541</td>\n","      <td>0.1745</td>\n","      <td>-0.0340</td>\n","      <td>0.4865</td>\n","      <td>-0.1854</td>\n","      <td>0.0716</td>\n","      <td>0.1729</td>\n","      <td>-0.0434</td>\n","      <td>0.1542</td>\n","      <td>-0.2192</td>\n","      <td>-0.0302</td>\n","      <td>-0.4218</td>\n","      <td>0.4057</td>\n","      <td>-0.5372</td>\n","      <td>0.1521</td>\n","      <td>-0.2651</td>\n","      <td>0.2310</td>\n","      <td>-0.8101</td>\n","      <td>0.4943</td>\n","      <td>0.6905</td>\n","      <td>-0.3720</td>\n","      <td>-1.4110</td>\n","      <td>0.4516</td>\n","      <td>1.2300</td>\n","      <td>-0.1949</td>\n","      <td>-1.3280</td>\n","      <td>-0.4276</td>\n","      <td>-0.0040</td>\n","      <td>-0.3086</td>\n","      <td>...</td>\n","      <td>0.6845</td>\n","      <td>0.7127</td>\n","      <td>0.7294</td>\n","      <td>0.4718</td>\n","      <td>-0.2020</td>\n","      <td>0.2783</td>\n","      <td>0.4934</td>\n","      <td>0.4144</td>\n","      <td>0.5449</td>\n","      <td>1.4690</td>\n","      <td>-0.6142</td>\n","      <td>0.6068</td>\n","      <td>0.3434</td>\n","      <td>0.9880</td>\n","      <td>-0.0468</td>\n","      <td>-0.1882</td>\n","      <td>-0.0087</td>\n","      <td>-0.0356</td>\n","      <td>0.5718</td>\n","      <td>0.4971</td>\n","      <td>0.1057</td>\n","      <td>0.2111</td>\n","      <td>0.6992</td>\n","      <td>0.0708</td>\n","      <td>0.6169</td>\n","      <td>0.2248</td>\n","      <td>0.5994</td>\n","      <td>0.2689</td>\n","      <td>0.0305</td>\n","      <td>1.2320</td>\n","      <td>0.5409</td>\n","      <td>0.3755</td>\n","      <td>0.7343</td>\n","      <td>0.2807</td>\n","      <td>0.4116</td>\n","      <td>0.6422</td>\n","      <td>0.2256</td>\n","      <td>0.7592</td>\n","      <td>0.6656</td>\n","      <td>0.3808</td>\n","    </tr>\n","    <tr>\n","      <th>23812</th>\n","      <td>id_fffcb9e7c</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>8b87a7a83</td>\n","      <td>0.6660</td>\n","      <td>0.2324</td>\n","      <td>0.4392</td>\n","      <td>0.2044</td>\n","      <td>0.8531</td>\n","      <td>-0.0343</td>\n","      <td>0.0323</td>\n","      <td>0.0463</td>\n","      <td>0.4299</td>\n","      <td>-0.7985</td>\n","      <td>0.5742</td>\n","      <td>0.1421</td>\n","      <td>2.2700</td>\n","      <td>0.2046</td>\n","      <td>0.5363</td>\n","      <td>-1.7330</td>\n","      <td>0.1450</td>\n","      <td>0.6097</td>\n","      <td>0.2024</td>\n","      <td>0.9865</td>\n","      <td>-0.7805</td>\n","      <td>0.9608</td>\n","      <td>0.3440</td>\n","      <td>2.7650</td>\n","      <td>0.4925</td>\n","      <td>0.6698</td>\n","      <td>0.2374</td>\n","      <td>-0.3372</td>\n","      <td>0.8771</td>\n","      <td>-2.6560</td>\n","      <td>-0.2000</td>\n","      <td>-0.2043</td>\n","      <td>0.6797</td>\n","      <td>-0.0248</td>\n","      <td>-0.0927</td>\n","      <td>...</td>\n","      <td>0.3360</td>\n","      <td>-0.6136</td>\n","      <td>0.5011</td>\n","      <td>0.9261</td>\n","      <td>0.4419</td>\n","      <td>0.0295</td>\n","      <td>0.4220</td>\n","      <td>0.4677</td>\n","      <td>-0.1184</td>\n","      <td>0.4524</td>\n","      <td>0.4135</td>\n","      <td>0.1356</td>\n","      <td>-0.5801</td>\n","      <td>0.0411</td>\n","      <td>1.0240</td>\n","      <td>1.0340</td>\n","      <td>-0.0270</td>\n","      <td>-0.4194</td>\n","      <td>0.7403</td>\n","      <td>-0.6793</td>\n","      <td>-0.1423</td>\n","      <td>0.7307</td>\n","      <td>0.7946</td>\n","      <td>-0.0650</td>\n","      <td>0.9038</td>\n","      <td>0.2324</td>\n","      <td>0.9676</td>\n","      <td>1.0940</td>\n","      <td>0.4290</td>\n","      <td>0.5187</td>\n","      <td>-0.1105</td>\n","      <td>0.4258</td>\n","      <td>-0.2012</td>\n","      <td>0.1506</td>\n","      <td>1.5230</td>\n","      <td>0.7101</td>\n","      <td>0.1732</td>\n","      <td>0.7015</td>\n","      <td>-0.6290</td>\n","      <td>0.0740</td>\n","    </tr>\n","    <tr>\n","      <th>23813</th>\n","      <td>id_ffffdd77b</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>972f41291</td>\n","      <td>-0.8598</td>\n","      <td>1.0240</td>\n","      <td>-0.1361</td>\n","      <td>0.7952</td>\n","      <td>-0.3611</td>\n","      <td>-3.6750</td>\n","      <td>-1.2420</td>\n","      <td>0.9146</td>\n","      <td>3.0790</td>\n","      <td>1.2460</td>\n","      <td>1.9460</td>\n","      <td>1.4370</td>\n","      <td>2.9780</td>\n","      <td>2.2370</td>\n","      <td>-0.6818</td>\n","      <td>0.6870</td>\n","      <td>-1.1060</td>\n","      <td>0.0182</td>\n","      <td>-0.9247</td>\n","      <td>-0.0738</td>\n","      <td>-0.1919</td>\n","      <td>-0.7722</td>\n","      <td>-1.4050</td>\n","      <td>-1.0050</td>\n","      <td>-1.1170</td>\n","      <td>-0.5293</td>\n","      <td>-1.1720</td>\n","      <td>-0.2885</td>\n","      <td>0.1599</td>\n","      <td>-0.4250</td>\n","      <td>0.3591</td>\n","      <td>-0.1420</td>\n","      <td>-0.9530</td>\n","      <td>-0.2005</td>\n","      <td>-1.8340</td>\n","      <td>...</td>\n","      <td>-6.9170</td>\n","      <td>-1.8640</td>\n","      <td>-2.5090</td>\n","      <td>-4.7130</td>\n","      <td>-1.7250</td>\n","      <td>-3.8650</td>\n","      <td>-3.0800</td>\n","      <td>-4.1530</td>\n","      <td>-1.2030</td>\n","      <td>-1.1690</td>\n","      <td>-4.1460</td>\n","      <td>-1.2670</td>\n","      <td>-1.1300</td>\n","      <td>-2.4390</td>\n","      <td>0.1591</td>\n","      <td>-2.2490</td>\n","      <td>-2.5860</td>\n","      <td>-1.9520</td>\n","      <td>-2.1810</td>\n","      <td>-4.6690</td>\n","      <td>-3.9450</td>\n","      <td>-2.9560</td>\n","      <td>-2.7930</td>\n","      <td>-2.1560</td>\n","      <td>-2.4100</td>\n","      <td>-1.8190</td>\n","      <td>-3.3480</td>\n","      <td>-0.1414</td>\n","      <td>-2.6430</td>\n","      <td>-2.5810</td>\n","      <td>-3.3890</td>\n","      <td>-1.7450</td>\n","      <td>-6.6300</td>\n","      <td>-4.0950</td>\n","      <td>-7.3860</td>\n","      <td>-1.4160</td>\n","      <td>-3.5770</td>\n","      <td>-0.4775</td>\n","      <td>-2.1500</td>\n","      <td>-4.2520</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>23814 rows × 877 columns</p>\n","</div>"],"text/plain":["                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n","1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n","2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n","3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n","4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n","...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n","23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n","23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n","23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n","23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n","23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n","\n","[23814 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":1}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"qBvT4sBNNPws","executionInfo":{"status":"ok","timestamp":1620127784050,"user_tz":180,"elapsed":6655,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"dfeff5f3-17c8-4a23-f8b6-926ab99144a3"},"source":["dados.head()"],"execution_count":2,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>droga</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>...</th>\n","      <th>c-60</th>\n","      <th>c-61</th>\n","      <th>c-62</th>\n","      <th>c-63</th>\n","      <th>c-64</th>\n","      <th>c-65</th>\n","      <th>c-66</th>\n","      <th>c-67</th>\n","      <th>c-68</th>\n","      <th>c-69</th>\n","      <th>c-70</th>\n","      <th>c-71</th>\n","      <th>c-72</th>\n","      <th>c-73</th>\n","      <th>c-74</th>\n","      <th>c-75</th>\n","      <th>c-76</th>\n","      <th>c-77</th>\n","      <th>c-78</th>\n","      <th>c-79</th>\n","      <th>c-80</th>\n","      <th>c-81</th>\n","      <th>c-82</th>\n","      <th>c-83</th>\n","      <th>c-84</th>\n","      <th>c-85</th>\n","      <th>c-86</th>\n","      <th>c-87</th>\n","      <th>c-88</th>\n","      <th>c-89</th>\n","      <th>c-90</th>\n","      <th>c-91</th>\n","      <th>c-92</th>\n","      <th>c-93</th>\n","      <th>c-94</th>\n","      <th>c-95</th>\n","      <th>c-96</th>\n","      <th>c-97</th>\n","      <th>c-98</th>\n","      <th>c-99</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>id_000644bb2</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>b68db1d53</td>\n","      <td>1.0620</td>\n","      <td>0.5577</td>\n","      <td>-0.2479</td>\n","      <td>-0.6208</td>\n","      <td>-0.1944</td>\n","      <td>-1.0120</td>\n","      <td>-1.0220</td>\n","      <td>-0.0326</td>\n","      <td>0.5548</td>\n","      <td>-0.0921</td>\n","      <td>1.1830</td>\n","      <td>0.1530</td>\n","      <td>0.5574</td>\n","      <td>-0.4015</td>\n","      <td>0.1789</td>\n","      <td>-0.6528</td>\n","      <td>-0.7969</td>\n","      <td>0.6342</td>\n","      <td>0.1778</td>\n","      <td>-0.3694</td>\n","      <td>-0.5688</td>\n","      <td>-1.1360</td>\n","      <td>-1.1880</td>\n","      <td>0.6940</td>\n","      <td>0.4393</td>\n","      <td>0.2664</td>\n","      <td>0.1907</td>\n","      <td>0.1628</td>\n","      <td>-0.2853</td>\n","      <td>0.5819</td>\n","      <td>0.2934</td>\n","      <td>-0.5584</td>\n","      <td>-0.0916</td>\n","      <td>-0.3010</td>\n","      <td>-0.1537</td>\n","      <td>...</td>\n","      <td>0.4805</td>\n","      <td>0.4965</td>\n","      <td>0.3680</td>\n","      <td>0.8427</td>\n","      <td>0.1042</td>\n","      <td>0.1403</td>\n","      <td>0.1758</td>\n","      <td>1.2570</td>\n","      <td>-0.5979</td>\n","      <td>1.2250</td>\n","      <td>-0.0553</td>\n","      <td>0.7351</td>\n","      <td>0.5810</td>\n","      <td>0.9590</td>\n","      <td>0.2427</td>\n","      <td>0.0495</td>\n","      <td>0.4141</td>\n","      <td>0.8432</td>\n","      <td>0.6162</td>\n","      <td>-0.7318</td>\n","      <td>1.2120</td>\n","      <td>0.6362</td>\n","      <td>-0.4427</td>\n","      <td>0.1288</td>\n","      <td>1.4840</td>\n","      <td>0.1799</td>\n","      <td>0.5367</td>\n","      <td>-0.1111</td>\n","      <td>-1.0120</td>\n","      <td>0.6685</td>\n","      <td>0.2862</td>\n","      <td>0.2584</td>\n","      <td>0.8076</td>\n","      <td>0.5523</td>\n","      <td>-0.1912</td>\n","      <td>0.6584</td>\n","      <td>-0.3981</td>\n","      <td>0.2139</td>\n","      <td>0.3801</td>\n","      <td>0.4176</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>id_000779bfc</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>df89a8e5a</td>\n","      <td>0.0743</td>\n","      <td>0.4087</td>\n","      <td>0.2991</td>\n","      <td>0.0604</td>\n","      <td>1.0190</td>\n","      <td>0.5207</td>\n","      <td>0.2341</td>\n","      <td>0.3372</td>\n","      <td>-0.4047</td>\n","      <td>0.8507</td>\n","      <td>-1.1520</td>\n","      <td>-0.4201</td>\n","      <td>-0.0958</td>\n","      <td>0.4590</td>\n","      <td>0.0803</td>\n","      <td>0.2250</td>\n","      <td>0.5293</td>\n","      <td>0.2839</td>\n","      <td>-0.3494</td>\n","      <td>0.2883</td>\n","      <td>0.9449</td>\n","      <td>-0.1646</td>\n","      <td>-0.2657</td>\n","      <td>-0.3372</td>\n","      <td>0.3135</td>\n","      <td>-0.4316</td>\n","      <td>0.4773</td>\n","      <td>0.2075</td>\n","      <td>-0.4216</td>\n","      <td>-0.1161</td>\n","      <td>-0.0499</td>\n","      <td>-0.2627</td>\n","      <td>0.9959</td>\n","      <td>-0.2483</td>\n","      <td>0.2655</td>\n","      <td>...</td>\n","      <td>0.4083</td>\n","      <td>0.0319</td>\n","      <td>0.3905</td>\n","      <td>0.7099</td>\n","      <td>0.2912</td>\n","      <td>0.4151</td>\n","      <td>-0.2840</td>\n","      <td>-0.3104</td>\n","      <td>-0.6373</td>\n","      <td>0.2887</td>\n","      <td>-0.0765</td>\n","      <td>0.2539</td>\n","      <td>0.4443</td>\n","      <td>0.5932</td>\n","      <td>0.2031</td>\n","      <td>0.7639</td>\n","      <td>0.5499</td>\n","      <td>-0.3322</td>\n","      <td>-0.0977</td>\n","      <td>0.4329</td>\n","      <td>-0.2782</td>\n","      <td>0.7827</td>\n","      <td>0.5934</td>\n","      <td>0.3402</td>\n","      <td>0.1499</td>\n","      <td>0.4420</td>\n","      <td>0.9366</td>\n","      <td>0.8193</td>\n","      <td>-0.4236</td>\n","      <td>0.3192</td>\n","      <td>-0.4265</td>\n","      <td>0.7543</td>\n","      <td>0.4708</td>\n","      <td>0.0230</td>\n","      <td>0.2957</td>\n","      <td>0.4899</td>\n","      <td>0.1522</td>\n","      <td>0.1241</td>\n","      <td>0.6077</td>\n","      <td>0.7371</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>id_000a6266a</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>18bb41b2c</td>\n","      <td>0.6280</td>\n","      <td>0.5817</td>\n","      <td>1.5540</td>\n","      <td>-0.0764</td>\n","      <td>-0.0323</td>\n","      <td>1.2390</td>\n","      <td>0.1715</td>\n","      <td>0.2155</td>\n","      <td>0.0065</td>\n","      <td>1.2300</td>\n","      <td>-0.4797</td>\n","      <td>-0.5631</td>\n","      <td>-0.0366</td>\n","      <td>-1.8300</td>\n","      <td>0.6057</td>\n","      <td>-0.3278</td>\n","      <td>0.6042</td>\n","      <td>-0.3075</td>\n","      <td>-0.1147</td>\n","      <td>-0.0570</td>\n","      <td>-0.0799</td>\n","      <td>-0.8181</td>\n","      <td>-1.5320</td>\n","      <td>0.2307</td>\n","      <td>0.4901</td>\n","      <td>0.4780</td>\n","      <td>-1.3970</td>\n","      <td>4.6240</td>\n","      <td>-0.0437</td>\n","      <td>1.2870</td>\n","      <td>-1.8530</td>\n","      <td>0.6069</td>\n","      <td>0.4290</td>\n","      <td>0.1783</td>\n","      <td>0.0018</td>\n","      <td>...</td>\n","      <td>-0.5477</td>\n","      <td>-0.7576</td>\n","      <td>-0.0444</td>\n","      <td>0.1894</td>\n","      <td>-0.0014</td>\n","      <td>-2.3640</td>\n","      <td>-0.4682</td>\n","      <td>0.1210</td>\n","      <td>-0.5177</td>\n","      <td>-0.0604</td>\n","      <td>0.1682</td>\n","      <td>-0.4436</td>\n","      <td>0.4963</td>\n","      <td>0.1363</td>\n","      <td>0.3335</td>\n","      <td>0.9760</td>\n","      <td>-0.0427</td>\n","      <td>-0.1235</td>\n","      <td>0.0959</td>\n","      <td>0.0690</td>\n","      <td>-0.9416</td>\n","      <td>-0.7548</td>\n","      <td>-0.1109</td>\n","      <td>-0.6272</td>\n","      <td>0.3019</td>\n","      <td>0.1172</td>\n","      <td>0.1093</td>\n","      <td>-0.3113</td>\n","      <td>0.3019</td>\n","      <td>-0.0873</td>\n","      <td>-0.7250</td>\n","      <td>-0.6297</td>\n","      <td>0.6103</td>\n","      <td>0.0223</td>\n","      <td>-1.3240</td>\n","      <td>-0.3174</td>\n","      <td>-0.6417</td>\n","      <td>-0.2187</td>\n","      <td>-1.4080</td>\n","      <td>0.6931</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>id_0015fd391</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8c7f86626</td>\n","      <td>-0.5138</td>\n","      <td>-0.2491</td>\n","      <td>-0.2656</td>\n","      <td>0.5288</td>\n","      <td>4.0620</td>\n","      <td>-0.8095</td>\n","      <td>-1.9590</td>\n","      <td>0.1792</td>\n","      <td>-0.1321</td>\n","      <td>-1.0600</td>\n","      <td>-0.8269</td>\n","      <td>-0.3584</td>\n","      <td>-0.8511</td>\n","      <td>-0.5844</td>\n","      <td>-2.5690</td>\n","      <td>0.8183</td>\n","      <td>-0.0532</td>\n","      <td>-0.8554</td>\n","      <td>0.1160</td>\n","      <td>-2.3520</td>\n","      <td>2.1200</td>\n","      <td>-1.1580</td>\n","      <td>-0.7191</td>\n","      <td>-0.8004</td>\n","      <td>-1.4670</td>\n","      <td>-0.0107</td>\n","      <td>-0.8995</td>\n","      <td>0.2406</td>\n","      <td>-0.2479</td>\n","      <td>-1.0890</td>\n","      <td>-0.7575</td>\n","      <td>0.0881</td>\n","      <td>-2.7370</td>\n","      <td>0.8745</td>\n","      <td>0.5787</td>\n","      <td>...</td>\n","      <td>-2.1220</td>\n","      <td>-0.3752</td>\n","      <td>-2.3820</td>\n","      <td>-3.7350</td>\n","      <td>-2.9740</td>\n","      <td>-1.4930</td>\n","      <td>-1.6600</td>\n","      <td>-3.1660</td>\n","      <td>0.2816</td>\n","      <td>-0.2990</td>\n","      <td>-1.1870</td>\n","      <td>-0.5044</td>\n","      <td>-1.7750</td>\n","      <td>-1.6120</td>\n","      <td>-0.9215</td>\n","      <td>-1.0810</td>\n","      <td>-3.0520</td>\n","      <td>-3.4470</td>\n","      <td>-2.7740</td>\n","      <td>-1.8460</td>\n","      <td>-0.5568</td>\n","      <td>-3.3960</td>\n","      <td>-2.9510</td>\n","      <td>-1.1550</td>\n","      <td>-3.2620</td>\n","      <td>-1.5390</td>\n","      <td>-2.4600</td>\n","      <td>-0.9417</td>\n","      <td>-1.5550</td>\n","      <td>0.2431</td>\n","      <td>-2.0990</td>\n","      <td>-0.6441</td>\n","      <td>-5.6300</td>\n","      <td>-1.3780</td>\n","      <td>-0.8632</td>\n","      <td>-1.2880</td>\n","      <td>-1.6210</td>\n","      <td>-0.8784</td>\n","      <td>-0.3876</td>\n","      <td>-0.8154</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>id_001626bd3</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D2</td>\n","      <td>7cbed3131</td>\n","      <td>-0.3254</td>\n","      <td>-0.4009</td>\n","      <td>0.9700</td>\n","      <td>0.6919</td>\n","      <td>1.4180</td>\n","      <td>-0.8244</td>\n","      <td>-0.2800</td>\n","      <td>-0.1498</td>\n","      <td>-0.8789</td>\n","      <td>0.8630</td>\n","      <td>-0.2219</td>\n","      <td>-0.5121</td>\n","      <td>-0.9577</td>\n","      <td>1.1750</td>\n","      <td>0.2042</td>\n","      <td>0.1970</td>\n","      <td>0.1244</td>\n","      <td>-1.7090</td>\n","      <td>-0.3543</td>\n","      <td>-0.5160</td>\n","      <td>-0.3330</td>\n","      <td>-0.2685</td>\n","      <td>0.7649</td>\n","      <td>0.2057</td>\n","      <td>1.3720</td>\n","      <td>0.6835</td>\n","      <td>0.8056</td>\n","      <td>-0.3754</td>\n","      <td>-1.2090</td>\n","      <td>0.2965</td>\n","      <td>-0.0712</td>\n","      <td>0.6389</td>\n","      <td>0.6674</td>\n","      <td>-0.0783</td>\n","      <td>1.1740</td>\n","      <td>...</td>\n","      <td>-0.2274</td>\n","      <td>0.3215</td>\n","      <td>0.1535</td>\n","      <td>-0.4640</td>\n","      <td>-0.5943</td>\n","      <td>0.3973</td>\n","      <td>0.1500</td>\n","      <td>0.5178</td>\n","      <td>0.5159</td>\n","      <td>0.6091</td>\n","      <td>0.1813</td>\n","      <td>-0.4249</td>\n","      <td>0.7832</td>\n","      <td>0.6529</td>\n","      <td>0.5648</td>\n","      <td>0.4817</td>\n","      <td>0.0587</td>\n","      <td>0.5303</td>\n","      <td>0.6376</td>\n","      <td>-0.3966</td>\n","      <td>-1.4950</td>\n","      <td>-0.9625</td>\n","      <td>-0.0541</td>\n","      <td>0.6273</td>\n","      <td>0.4563</td>\n","      <td>0.0698</td>\n","      <td>0.8134</td>\n","      <td>0.1924</td>\n","      <td>0.6054</td>\n","      <td>-0.1824</td>\n","      <td>0.0042</td>\n","      <td>0.0048</td>\n","      <td>0.6670</td>\n","      <td>1.0690</td>\n","      <td>0.5523</td>\n","      <td>-0.3031</td>\n","      <td>0.1094</td>\n","      <td>0.2885</td>\n","      <td>-0.3786</td>\n","      <td>0.7125</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 877 columns</p>\n","</div>"],"text/plain":["             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n","1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n","2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n","3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n","4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n","\n","[5 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":2}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fYdow_XdNPws","executionInfo":{"status":"ok","timestamp":1620127784054,"user_tz":180,"elapsed":6646,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"e4da3381-6c85-4460-ce48-03fcec864baf"},"source":["dados.shape"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(23814, 877)"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"zOmQRiUTNPwt","executionInfo":{"status":"ok","timestamp":1620127784055,"user_tz":180,"elapsed":6635,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"fceb7c0e-c1cd-43b1-a0a3-069b6facd0a3"},"source":["dados['tratamento']"],"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0           com_droga\n","1           com_droga\n","2           com_droga\n","3           com_droga\n","4           com_droga\n","             ...     \n","23809       com_droga\n","23810       com_droga\n","23811    com_controle\n","23812       com_droga\n","23813       com_droga\n","Name: tratamento, Length: 23814, dtype: object"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BrCJ2TzSNPwt","executionInfo":{"status":"ok","timestamp":1620127784557,"user_tz":180,"elapsed":7124,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"c3a6c076-d07f-45df-b250-233115872ae0"},"source":["dados['tratamento'].unique()"],"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['com_droga', 'com_controle'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"d-eF7mPaNPwt","executionInfo":{"status":"ok","timestamp":1620127784558,"user_tz":180,"elapsed":7111,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"5a665398-b662-4327-a4d1-60f0f4039a02"},"source":["dados['tempo'].unique()"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([24, 72, 48])"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Zgm1XiOeNPwu","executionInfo":{"status":"ok","timestamp":1620127784559,"user_tz":180,"elapsed":7098,"user":{"displayName":"Italo 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  'b2fe3eca7', 'dd4a96d16'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":8}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hvdM3kYSNPwv","executionInfo":{"status":"ok","timestamp":1620127784560,"user_tz":180,"elapsed":7070,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"e968b149-db55-47e0-9627-9da187b2b31f"},"source":["dados['g-0'].unique()"],"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 1.062 ,  0.0743,  0.628 , ...,  0.3942,  0.666 , -0.8598])"]},"metadata":{"tags":[]},"execution_count":9}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZwjZj1F6NPwv","executionInfo":{"status":"ok","timestamp":1620127784561,"user_tz":180,"elapsed":7056,"user":{"displayName":"Italo 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float64"]},"metadata":{"tags":[]},"execution_count":12}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"owgn4RkDNPww","executionInfo":{"status":"ok","timestamp":1620127784564,"user_tz":180,"elapsed":7006,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"e92171cb-a934-4721-ff60-3bed1ed32cc2"},"source":["dados['dose'].value_counts(normalize = True)"],"execution_count":13,"outputs":[{"output_type":"execute_result","data":{"text/plain":["D1    0.510078\n","D2    0.489922\n","Name: dose, dtype: float64"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"OzMt7-vdNPwx","executionInfo":{"status":"ok","timestamp":1620127784565,"user_tz":180,"elapsed":6986,"user":{"displayName":"Italo 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"wTkLLtMnNPwx","executionInfo":{"status":"ok","timestamp":1620127784565,"user_tz":180,"elapsed":6965,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"510f1890-7cc7-42b7-86d5-4fb83907476d"},"source":["dados['tempo'].value_counts().plot.pie()"],"execution_count":15,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4ec672a990>"]},"metadata":{"tags":[]},"execution_count":15},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"ArVvC7PRNPwx","executionInfo":{"status":"ok","timestamp":1620127784875,"user_tz":180,"elapsed":7257,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"305179bb-637e-48db-f36b-e7ba2abb58c4"},"source":["dados['tempo'].value_counts().plot.bar()"],"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4ec65194d0>"]},"metadata":{"tags":[]},"execution_count":16},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"ngAH-Ir6NPwy","executionInfo":{"status":"ok","timestamp":1620127784876,"user_tz":180,"elapsed":7240,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"b71c0303-c4d3-407d-ce66-d1950ab77efa"},"source":["dados_filtrados = dados[dados['g-0'] > 0]\n","dados_filtrados.head()"],"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>droga</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>...</th>\n","      <th>c-60</th>\n","      <th>c-61</th>\n","      <th>c-62</th>\n","      <th>c-63</th>\n","      <th>c-64</th>\n","      <th>c-65</th>\n","      <th>c-66</th>\n","      <th>c-67</th>\n","      <th>c-68</th>\n","      <th>c-69</th>\n","      <th>c-70</th>\n","      <th>c-71</th>\n","      <th>c-72</th>\n","      <th>c-73</th>\n","      <th>c-74</th>\n","      <th>c-75</th>\n","      <th>c-76</th>\n","      <th>c-77</th>\n","      <th>c-78</th>\n","      <th>c-79</th>\n","      <th>c-80</th>\n","      <th>c-81</th>\n","      <th>c-82</th>\n","      <th>c-83</th>\n","      <th>c-84</th>\n","      <th>c-85</th>\n","      <th>c-86</th>\n","      <th>c-87</th>\n","      <th>c-88</th>\n","      <th>c-89</th>\n","      <th>c-90</th>\n","      <th>c-91</th>\n","      <th>c-92</th>\n","      <th>c-93</th>\n","      <th>c-94</th>\n","      <th>c-95</th>\n","      <th>c-96</th>\n","      <th>c-97</th>\n","      <th>c-98</th>\n","      <th>c-99</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>id_000644bb2</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>b68db1d53</td>\n","      <td>1.0620</td>\n","      <td>0.5577</td>\n","      <td>-0.2479</td>\n","      <td>-0.6208</td>\n","      <td>-0.1944</td>\n","      <td>-1.0120</td>\n","      <td>-1.0220</td>\n","      <td>-0.0326</td>\n","      <td>0.5548</td>\n","      <td>-0.0921</td>\n","      <td>1.1830</td>\n","      <td>0.1530</td>\n","      <td>0.5574</td>\n","      <td>-0.4015</td>\n","      <td>0.1789</td>\n","      <td>-0.6528</td>\n","      <td>-0.7969</td>\n","      <td>0.6342</td>\n","      <td>0.1778</td>\n","      <td>-0.3694</td>\n","      <td>-0.5688</td>\n","      <td>-1.1360</td>\n","      <td>-1.1880</td>\n","      <td>0.6940</td>\n","      <td>0.4393</td>\n","      <td>0.2664</td>\n","      <td>0.1907</td>\n","      <td>0.1628</td>\n","      <td>-0.2853</td>\n","      <td>0.5819</td>\n","      <td>0.2934</td>\n","      <td>-0.5584</td>\n","      <td>-0.0916</td>\n","      <td>-0.3010</td>\n","      <td>-0.1537</td>\n","      <td>...</td>\n","      <td>0.4805</td>\n","      <td>0.4965</td>\n","      <td>0.3680</td>\n","      <td>0.8427</td>\n","      <td>0.1042</td>\n","      <td>0.1403</td>\n","      <td>0.1758</td>\n","      <td>1.2570</td>\n","      <td>-0.5979</td>\n","      <td>1.2250</td>\n","      <td>-0.0553</td>\n","      <td>0.7351</td>\n","      <td>0.5810</td>\n","      <td>0.9590</td>\n","      <td>0.2427</td>\n","      <td>0.0495</td>\n","      <td>0.4141</td>\n","      <td>0.8432</td>\n","      <td>0.6162</td>\n","      <td>-0.7318</td>\n","      <td>1.2120</td>\n","      <td>0.6362</td>\n","      <td>-0.4427</td>\n","      <td>0.1288</td>\n","      <td>1.4840</td>\n","      <td>0.1799</td>\n","      <td>0.5367</td>\n","      <td>-0.1111</td>\n","      <td>-1.0120</td>\n","      <td>0.6685</td>\n","      <td>0.2862</td>\n","      <td>0.2584</td>\n","      <td>0.8076</td>\n","      <td>0.5523</td>\n","      <td>-0.1912</td>\n","      <td>0.6584</td>\n","      <td>-0.3981</td>\n","      <td>0.2139</td>\n","      <td>0.3801</td>\n","      <td>0.4176</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>id_000779bfc</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>df89a8e5a</td>\n","      <td>0.0743</td>\n","      <td>0.4087</td>\n","      <td>0.2991</td>\n","      <td>0.0604</td>\n","      <td>1.0190</td>\n","      <td>0.5207</td>\n","      <td>0.2341</td>\n","      <td>0.3372</td>\n","      <td>-0.4047</td>\n","      <td>0.8507</td>\n","      <td>-1.1520</td>\n","      <td>-0.4201</td>\n","      <td>-0.0958</td>\n","      <td>0.4590</td>\n","      <td>0.0803</td>\n","      <td>0.2250</td>\n","      <td>0.5293</td>\n","      <td>0.2839</td>\n","      <td>-0.3494</td>\n","      <td>0.2883</td>\n","      <td>0.9449</td>\n","      <td>-0.1646</td>\n","      <td>-0.2657</td>\n","      <td>-0.3372</td>\n","      <td>0.3135</td>\n","      <td>-0.4316</td>\n","      <td>0.4773</td>\n","      <td>0.2075</td>\n","      <td>-0.4216</td>\n","      <td>-0.1161</td>\n","      <td>-0.0499</td>\n","      <td>-0.2627</td>\n","      <td>0.9959</td>\n","      <td>-0.2483</td>\n","      <td>0.2655</td>\n","      <td>...</td>\n","      <td>0.4083</td>\n","      <td>0.0319</td>\n","      <td>0.3905</td>\n","      <td>0.7099</td>\n","      <td>0.2912</td>\n","      <td>0.4151</td>\n","      <td>-0.2840</td>\n","      <td>-0.3104</td>\n","      <td>-0.6373</td>\n","      <td>0.2887</td>\n","      <td>-0.0765</td>\n","      <td>0.2539</td>\n","      <td>0.4443</td>\n","      <td>0.5932</td>\n","      <td>0.2031</td>\n","      <td>0.7639</td>\n","      <td>0.5499</td>\n","      <td>-0.3322</td>\n","      <td>-0.0977</td>\n","      <td>0.4329</td>\n","      <td>-0.2782</td>\n","      <td>0.7827</td>\n","      <td>0.5934</td>\n","      <td>0.3402</td>\n","      <td>0.1499</td>\n","      <td>0.4420</td>\n","      <td>0.9366</td>\n","      <td>0.8193</td>\n","      <td>-0.4236</td>\n","      <td>0.3192</td>\n","      <td>-0.4265</td>\n","      <td>0.7543</td>\n","      <td>0.4708</td>\n","      <td>0.0230</td>\n","      <td>0.2957</td>\n","      <td>0.4899</td>\n","      <td>0.1522</td>\n","      <td>0.1241</td>\n","      <td>0.6077</td>\n","      <td>0.7371</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>id_000a6266a</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>18bb41b2c</td>\n","      <td>0.6280</td>\n","      <td>0.5817</td>\n","      <td>1.5540</td>\n","      <td>-0.0764</td>\n","      <td>-0.0323</td>\n","      <td>1.2390</td>\n","      <td>0.1715</td>\n","      <td>0.2155</td>\n","      <td>0.0065</td>\n","      <td>1.2300</td>\n","      <td>-0.4797</td>\n","      <td>-0.5631</td>\n","      <td>-0.0366</td>\n","      <td>-1.8300</td>\n","      <td>0.6057</td>\n","      <td>-0.3278</td>\n","      <td>0.6042</td>\n","      <td>-0.3075</td>\n","      <td>-0.1147</td>\n","      <td>-0.0570</td>\n","      <td>-0.0799</td>\n","      <td>-0.8181</td>\n","      <td>-1.5320</td>\n","      <td>0.2307</td>\n","      <td>0.4901</td>\n","      <td>0.4780</td>\n","      <td>-1.3970</td>\n","      <td>4.6240</td>\n","      <td>-0.0437</td>\n","      <td>1.2870</td>\n","      <td>-1.8530</td>\n","      <td>0.6069</td>\n","      <td>0.4290</td>\n","      <td>0.1783</td>\n","      <td>0.0018</td>\n","      <td>...</td>\n","      <td>-0.5477</td>\n","      <td>-0.7576</td>\n","      <td>-0.0444</td>\n","      <td>0.1894</td>\n","      <td>-0.0014</td>\n","      <td>-2.3640</td>\n","      <td>-0.4682</td>\n","      <td>0.1210</td>\n","      <td>-0.5177</td>\n","      <td>-0.0604</td>\n","      <td>0.1682</td>\n","      <td>-0.4436</td>\n","      <td>0.4963</td>\n","      <td>0.1363</td>\n","      <td>0.3335</td>\n","      <td>0.9760</td>\n","      <td>-0.0427</td>\n","      <td>-0.1235</td>\n","      <td>0.0959</td>\n","      <td>0.0690</td>\n","      <td>-0.9416</td>\n","      <td>-0.7548</td>\n","      <td>-0.1109</td>\n","      <td>-0.6272</td>\n","      <td>0.3019</td>\n","      <td>0.1172</td>\n","      <td>0.1093</td>\n","      <td>-0.3113</td>\n","      <td>0.3019</td>\n","      <td>-0.0873</td>\n","      <td>-0.7250</td>\n","      <td>-0.6297</td>\n","      <td>0.6103</td>\n","      <td>0.0223</td>\n","      <td>-1.3240</td>\n","      <td>-0.3174</td>\n","      <td>-0.6417</td>\n","      <td>-0.2187</td>\n","      <td>-1.4080</td>\n","      <td>0.6931</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>id_001bd861f</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D2</td>\n","      <td>746ca1f5a</td>\n","      <td>2.0440</td>\n","      <td>1.7000</td>\n","      <td>-1.5390</td>\n","      <td>5.9440</td>\n","      <td>-2.1670</td>\n","      <td>-4.0360</td>\n","      <td>3.6950</td>\n","      <td>1.4530</td>\n","      <td>0.9724</td>\n","      <td>-2.4380</td>\n","      <td>5.1340</td>\n","      <td>-4.6600</td>\n","      <td>5.7960</td>\n","      <td>4.9700</td>\n","      <td>1.5540</td>\n","      <td>2.4790</td>\n","      <td>-3.8010</td>\n","      <td>-1.0230</td>\n","      <td>5.3110</td>\n","      <td>-0.5660</td>\n","      <td>-4.4450</td>\n","      <td>1.2210</td>\n","      <td>1.3750</td>\n","      <td>0.3932</td>\n","      <td>0.3392</td>\n","      <td>4.3510</td>\n","      <td>5.7540</td>\n","      <td>-1.6590</td>\n","      <td>5.3000</td>\n","      <td>5.6050</td>\n","      <td>5.5320</td>\n","      <td>3.7860</td>\n","      <td>0.9197</td>\n","      <td>1.9310</td>\n","      <td>2.4870</td>\n","      <td>...</td>\n","      <td>-0.8904</td>\n","      <td>2.0590</td>\n","      <td>0.5052</td>\n","      <td>0.6890</td>\n","      <td>0.5340</td>\n","      <td>0.5135</td>\n","      <td>0.6507</td>\n","      <td>0.9838</td>\n","      <td>0.4532</td>\n","      <td>-0.3212</td>\n","      <td>0.2662</td>\n","      <td>0.6864</td>\n","      <td>1.6300</td>\n","      <td>1.3810</td>\n","      <td>0.0061</td>\n","      <td>0.2908</td>\n","      <td>0.2598</td>\n","      <td>0.1266</td>\n","      <td>-0.3526</td>\n","      <td>1.1750</td>\n","      <td>-1.1030</td>\n","      <td>1.3650</td>\n","      <td>1.0610</td>\n","      <td>0.4034</td>\n","      <td>1.0880</td>\n","      <td>-0.4230</td>\n","      <td>0.4013</td>\n","      <td>0.1726</td>\n","      <td>0.7464</td>\n","      <td>0.9418</td>\n","      <td>0.1855</td>\n","      <td>1.1720</td>\n","      <td>0.8325</td>\n","      <td>0.6486</td>\n","      <td>0.8090</td>\n","      <td>1.5880</td>\n","      <td>2.4670</td>\n","      <td>0.0357</td>\n","      <td>0.1351</td>\n","      <td>-0.3179</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>id_0020d0484</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8b87a7a83</td>\n","      <td>0.2711</td>\n","      <td>0.5133</td>\n","      <td>-0.1327</td>\n","      <td>2.5950</td>\n","      <td>0.6980</td>\n","      <td>0.5846</td>\n","      <td>-0.2633</td>\n","      <td>-2.1490</td>\n","      <td>0.4881</td>\n","      <td>1.4750</td>\n","      <td>-0.0488</td>\n","      <td>-0.0561</td>\n","      <td>0.1641</td>\n","      <td>0.1749</td>\n","      <td>-0.3464</td>\n","      <td>-0.1811</td>\n","      <td>0.5685</td>\n","      <td>1.2970</td>\n","      <td>1.0510</td>\n","      <td>-0.9585</td>\n","      <td>0.7911</td>\n","      <td>-0.2991</td>\n","      <td>2.7420</td>\n","      <td>-0.5979</td>\n","      <td>-1.0240</td>\n","      <td>0.7268</td>\n","      <td>0.1590</td>\n","      <td>-1.9730</td>\n","      <td>1.1340</td>\n","      <td>-2.5720</td>\n","      <td>0.2068</td>\n","      <td>0.9992</td>\n","      <td>-0.1958</td>\n","      <td>0.2262</td>\n","      <td>1.0140</td>\n","      <td>...</td>\n","      <td>-0.2623</td>\n","      <td>-0.5500</td>\n","      <td>-0.0530</td>\n","      <td>0.2077</td>\n","      <td>-0.0825</td>\n","      <td>0.2156</td>\n","      <td>0.8142</td>\n","      <td>1.0990</td>\n","      <td>1.0860</td>\n","      <td>0.4011</td>\n","      <td>-0.1342</td>\n","      <td>0.4653</td>\n","      <td>-0.1104</td>\n","      <td>0.3935</td>\n","      <td>1.2370</td>\n","      <td>-0.5072</td>\n","      <td>0.0351</td>\n","      <td>0.5084</td>\n","      <td>-0.1248</td>\n","      <td>0.4351</td>\n","      <td>0.1389</td>\n","      <td>0.6726</td>\n","      <td>0.6070</td>\n","      <td>0.3431</td>\n","      <td>-0.4116</td>\n","      <td>0.1194</td>\n","      <td>0.3420</td>\n","      <td>0.1331</td>\n","      <td>0.8541</td>\n","      <td>0.6282</td>\n","      <td>0.3230</td>\n","      <td>-0.4140</td>\n","      <td>0.2532</td>\n","      <td>0.0513</td>\n","      <td>0.8600</td>\n","      <td>1.4250</td>\n","      <td>0.6633</td>\n","      <td>0.4562</td>\n","      <td>-0.9622</td>\n","      <td>0.0260</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 877 columns</p>\n","</div>"],"text/plain":["             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n","1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n","2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n","6  id_001bd861f  com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n","7  id_0020d0484  com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n","\n","[5 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":17}]},{"cell_type":"markdown","metadata":{"id":"87yE0HvTNY6u"},"source":["#Aula 02"]},{"cell_type":"markdown","metadata":{"id":"xFXfW7vFvfK-"},"source":["Olá!\n","\n","Seja bem vindo e bem vinda a aula 02!\n","\n","Na aula 01, nós começamos a explorar um conjunto de dados relacionados à industria farmacêutica. Para isso nós utilizamos uma biblioteca muito conhecida no mundo de DataScience: o Pandas.\n","\n","Nós utilizamos o Pandas para abrir o dataset, que estava no formato CSV, e para gerar um dataframe, uma tabela, para então começarmos a analisar e entender o que significava cada coluna. Com a ajuda da Vanessa, especialista na área, identificamos que temos colunas que nos remetem a dados que estão sob tratamento(droga) e com controle. Além disso, temos também diversas colunas que remetem aos genes.\n","\n","Começamos nossa análise olhando para cada coluna de forma separada e também geramos gráficos, para auxiliar nossa análise.\n","\n","E você? Como se saiu na resolução dos desafios?\n","\n","Agora, vamos mergulhar juntos na aula 02!"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"hB3O-zZW9ZYw","executionInfo":{"status":"ok","timestamp":1620128206774,"user_tz":180,"elapsed":985,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"c8204924-f004-4808-91ea-0713263384bf"},"source":["dados"],"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>droga</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>...</th>\n","      <th>c-60</th>\n","      <th>c-61</th>\n","      <th>c-62</th>\n","      <th>c-63</th>\n","      <th>c-64</th>\n","      <th>c-65</th>\n","      <th>c-66</th>\n","      <th>c-67</th>\n","      <th>c-68</th>\n","      <th>c-69</th>\n","      <th>c-70</th>\n","      <th>c-71</th>\n","      <th>c-72</th>\n","      <th>c-73</th>\n","      <th>c-74</th>\n","      <th>c-75</th>\n","      <th>c-76</th>\n","      <th>c-77</th>\n","      <th>c-78</th>\n","      <th>c-79</th>\n","      <th>c-80</th>\n","      <th>c-81</th>\n","      <th>c-82</th>\n","      <th>c-83</th>\n","      <th>c-84</th>\n","      <th>c-85</th>\n","      <th>c-86</th>\n","      <th>c-87</th>\n","      <th>c-88</th>\n","      <th>c-89</th>\n","      <th>c-90</th>\n","      <th>c-91</th>\n","      <th>c-92</th>\n","      <th>c-93</th>\n","      <th>c-94</th>\n","      <th>c-95</th>\n","      <th>c-96</th>\n","      <th>c-97</th>\n","      <th>c-98</th>\n","      <th>c-99</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>id_000644bb2</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>b68db1d53</td>\n","      <td>1.0620</td>\n","      <td>0.5577</td>\n","      <td>-0.2479</td>\n","      <td>-0.6208</td>\n","      <td>-0.1944</td>\n","      <td>-1.0120</td>\n","      <td>-1.0220</td>\n","      <td>-0.0326</td>\n","      <td>0.5548</td>\n","      <td>-0.0921</td>\n","      <td>1.1830</td>\n","      <td>0.1530</td>\n","      <td>0.5574</td>\n","      <td>-0.4015</td>\n","      <td>0.1789</td>\n","      <td>-0.6528</td>\n","      <td>-0.7969</td>\n","      <td>0.6342</td>\n","      <td>0.1778</td>\n","      <td>-0.3694</td>\n","      <td>-0.5688</td>\n","      <td>-1.1360</td>\n","      <td>-1.1880</td>\n","      <td>0.6940</td>\n","      <td>0.4393</td>\n","      <td>0.2664</td>\n","      <td>0.1907</td>\n","      <td>0.1628</td>\n","      <td>-0.2853</td>\n","      <td>0.5819</td>\n","      <td>0.2934</td>\n","      <td>-0.5584</td>\n","      <td>-0.0916</td>\n","      <td>-0.3010</td>\n","      <td>-0.1537</td>\n","      <td>...</td>\n","      <td>0.4805</td>\n","      <td>0.4965</td>\n","      <td>0.3680</td>\n","      <td>0.8427</td>\n","      <td>0.1042</td>\n","      <td>0.1403</td>\n","      <td>0.1758</td>\n","      <td>1.2570</td>\n","      <td>-0.5979</td>\n","      <td>1.2250</td>\n","      <td>-0.0553</td>\n","      <td>0.7351</td>\n","      <td>0.5810</td>\n","      <td>0.9590</td>\n","      <td>0.2427</td>\n","      <td>0.0495</td>\n","      <td>0.4141</td>\n","      <td>0.8432</td>\n","      <td>0.6162</td>\n","      <td>-0.7318</td>\n","      <td>1.2120</td>\n","      <td>0.6362</td>\n","      <td>-0.4427</td>\n","      <td>0.1288</td>\n","      <td>1.4840</td>\n","      <td>0.1799</td>\n","      <td>0.5367</td>\n","      <td>-0.1111</td>\n","      <td>-1.0120</td>\n","      <td>0.6685</td>\n","      <td>0.2862</td>\n","      <td>0.2584</td>\n","      <td>0.8076</td>\n","      <td>0.5523</td>\n","      <td>-0.1912</td>\n","      <td>0.6584</td>\n","      <td>-0.3981</td>\n","      <td>0.2139</td>\n","      <td>0.3801</td>\n","      <td>0.4176</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>id_000779bfc</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>df89a8e5a</td>\n","      <td>0.0743</td>\n","      <td>0.4087</td>\n","      <td>0.2991</td>\n","      <td>0.0604</td>\n","      <td>1.0190</td>\n","      <td>0.5207</td>\n","      <td>0.2341</td>\n","      <td>0.3372</td>\n","      <td>-0.4047</td>\n","      <td>0.8507</td>\n","      <td>-1.1520</td>\n","      <td>-0.4201</td>\n","      <td>-0.0958</td>\n","      <td>0.4590</td>\n","      <td>0.0803</td>\n","      <td>0.2250</td>\n","      <td>0.5293</td>\n","      <td>0.2839</td>\n","      <td>-0.3494</td>\n","      <td>0.2883</td>\n","      <td>0.9449</td>\n","      <td>-0.1646</td>\n","      <td>-0.2657</td>\n","      <td>-0.3372</td>\n","      <td>0.3135</td>\n","      <td>-0.4316</td>\n","      <td>0.4773</td>\n","      <td>0.2075</td>\n","      <td>-0.4216</td>\n","      <td>-0.1161</td>\n","      <td>-0.0499</td>\n","      <td>-0.2627</td>\n","      <td>0.9959</td>\n","      <td>-0.2483</td>\n","      <td>0.2655</td>\n","      <td>...</td>\n","      <td>0.4083</td>\n","      <td>0.0319</td>\n","      <td>0.3905</td>\n","      <td>0.7099</td>\n","      <td>0.2912</td>\n","      <td>0.4151</td>\n","      <td>-0.2840</td>\n","      <td>-0.3104</td>\n","      <td>-0.6373</td>\n","      <td>0.2887</td>\n","      <td>-0.0765</td>\n","      <td>0.2539</td>\n","      <td>0.4443</td>\n","      <td>0.5932</td>\n","      <td>0.2031</td>\n","      <td>0.7639</td>\n","      <td>0.5499</td>\n","      <td>-0.3322</td>\n","      <td>-0.0977</td>\n","      <td>0.4329</td>\n","      <td>-0.2782</td>\n","      <td>0.7827</td>\n","      <td>0.5934</td>\n","      <td>0.3402</td>\n","      <td>0.1499</td>\n","      <td>0.4420</td>\n","      <td>0.9366</td>\n","      <td>0.8193</td>\n","      <td>-0.4236</td>\n","      <td>0.3192</td>\n","      <td>-0.4265</td>\n","      <td>0.7543</td>\n","      <td>0.4708</td>\n","      <td>0.0230</td>\n","      <td>0.2957</td>\n","      <td>0.4899</td>\n","      <td>0.1522</td>\n","      <td>0.1241</td>\n","      <td>0.6077</td>\n","      <td>0.7371</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>id_000a6266a</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>18bb41b2c</td>\n","      <td>0.6280</td>\n","      <td>0.5817</td>\n","      <td>1.5540</td>\n","      <td>-0.0764</td>\n","      <td>-0.0323</td>\n","      <td>1.2390</td>\n","      <td>0.1715</td>\n","      <td>0.2155</td>\n","      <td>0.0065</td>\n","      <td>1.2300</td>\n","      <td>-0.4797</td>\n","      <td>-0.5631</td>\n","      <td>-0.0366</td>\n","      <td>-1.8300</td>\n","      <td>0.6057</td>\n","      <td>-0.3278</td>\n","      <td>0.6042</td>\n","      <td>-0.3075</td>\n","      <td>-0.1147</td>\n","      <td>-0.0570</td>\n","      <td>-0.0799</td>\n","      <td>-0.8181</td>\n","      <td>-1.5320</td>\n","      <td>0.2307</td>\n","      <td>0.4901</td>\n","      <td>0.4780</td>\n","      <td>-1.3970</td>\n","      <td>4.6240</td>\n","      <td>-0.0437</td>\n","      <td>1.2870</td>\n","      <td>-1.8530</td>\n","      <td>0.6069</td>\n","      <td>0.4290</td>\n","      <td>0.1783</td>\n","      <td>0.0018</td>\n","      <td>...</td>\n","      <td>-0.5477</td>\n","      <td>-0.7576</td>\n","      <td>-0.0444</td>\n","      <td>0.1894</td>\n","      <td>-0.0014</td>\n","      <td>-2.3640</td>\n","      <td>-0.4682</td>\n","      <td>0.1210</td>\n","      <td>-0.5177</td>\n","      <td>-0.0604</td>\n","      <td>0.1682</td>\n","      <td>-0.4436</td>\n","      <td>0.4963</td>\n","      <td>0.1363</td>\n","      <td>0.3335</td>\n","      <td>0.9760</td>\n","      <td>-0.0427</td>\n","      <td>-0.1235</td>\n","      <td>0.0959</td>\n","      <td>0.0690</td>\n","      <td>-0.9416</td>\n","      <td>-0.7548</td>\n","      <td>-0.1109</td>\n","      <td>-0.6272</td>\n","      <td>0.3019</td>\n","      <td>0.1172</td>\n","      <td>0.1093</td>\n","      <td>-0.3113</td>\n","      <td>0.3019</td>\n","      <td>-0.0873</td>\n","      <td>-0.7250</td>\n","      <td>-0.6297</td>\n","      <td>0.6103</td>\n","      <td>0.0223</td>\n","      <td>-1.3240</td>\n","      <td>-0.3174</td>\n","      <td>-0.6417</td>\n","      <td>-0.2187</td>\n","      <td>-1.4080</td>\n","      <td>0.6931</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>id_0015fd391</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8c7f86626</td>\n","      <td>-0.5138</td>\n","      <td>-0.2491</td>\n","      <td>-0.2656</td>\n","      <td>0.5288</td>\n","      <td>4.0620</td>\n","      <td>-0.8095</td>\n","      <td>-1.9590</td>\n","      <td>0.1792</td>\n","      <td>-0.1321</td>\n","      <td>-1.0600</td>\n","      <td>-0.8269</td>\n","      <td>-0.3584</td>\n","      <td>-0.8511</td>\n","      <td>-0.5844</td>\n","      <td>-2.5690</td>\n","      <td>0.8183</td>\n","      <td>-0.0532</td>\n","      <td>-0.8554</td>\n","      <td>0.1160</td>\n","      <td>-2.3520</td>\n","      <td>2.1200</td>\n","      <td>-1.1580</td>\n","      <td>-0.7191</td>\n","      <td>-0.8004</td>\n","      <td>-1.4670</td>\n","      <td>-0.0107</td>\n","      <td>-0.8995</td>\n","      <td>0.2406</td>\n","      <td>-0.2479</td>\n","      <td>-1.0890</td>\n","      <td>-0.7575</td>\n","      <td>0.0881</td>\n","      <td>-2.7370</td>\n","      <td>0.8745</td>\n","      <td>0.5787</td>\n","      <td>...</td>\n","      <td>-2.1220</td>\n","      <td>-0.3752</td>\n","      <td>-2.3820</td>\n","      <td>-3.7350</td>\n","      <td>-2.9740</td>\n","      <td>-1.4930</td>\n","      <td>-1.6600</td>\n","      <td>-3.1660</td>\n","      <td>0.2816</td>\n","      <td>-0.2990</td>\n","      <td>-1.1870</td>\n","      <td>-0.5044</td>\n","      <td>-1.7750</td>\n","      <td>-1.6120</td>\n","      <td>-0.9215</td>\n","      <td>-1.0810</td>\n","      <td>-3.0520</td>\n","      <td>-3.4470</td>\n","      <td>-2.7740</td>\n","      <td>-1.8460</td>\n","      <td>-0.5568</td>\n","      <td>-3.3960</td>\n","      <td>-2.9510</td>\n","      <td>-1.1550</td>\n","      <td>-3.2620</td>\n","      <td>-1.5390</td>\n","      <td>-2.4600</td>\n","      <td>-0.9417</td>\n","      <td>-1.5550</td>\n","      <td>0.2431</td>\n","      <td>-2.0990</td>\n","      <td>-0.6441</td>\n","      <td>-5.6300</td>\n","      <td>-1.3780</td>\n","      <td>-0.8632</td>\n","      <td>-1.2880</td>\n","      <td>-1.6210</td>\n","      <td>-0.8784</td>\n","      <td>-0.3876</td>\n","      <td>-0.8154</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>id_001626bd3</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D2</td>\n","      <td>7cbed3131</td>\n","      <td>-0.3254</td>\n","      <td>-0.4009</td>\n","      <td>0.9700</td>\n","      <td>0.6919</td>\n","      <td>1.4180</td>\n","      <td>-0.8244</td>\n","      <td>-0.2800</td>\n","      <td>-0.1498</td>\n","      <td>-0.8789</td>\n","      <td>0.8630</td>\n","      <td>-0.2219</td>\n","      <td>-0.5121</td>\n","      <td>-0.9577</td>\n","      <td>1.1750</td>\n","      <td>0.2042</td>\n","      <td>0.1970</td>\n","      <td>0.1244</td>\n","      <td>-1.7090</td>\n","      <td>-0.3543</td>\n","      <td>-0.5160</td>\n","      <td>-0.3330</td>\n","      <td>-0.2685</td>\n","      <td>0.7649</td>\n","      <td>0.2057</td>\n","      <td>1.3720</td>\n","      <td>0.6835</td>\n","      <td>0.8056</td>\n","      <td>-0.3754</td>\n","      <td>-1.2090</td>\n","      <td>0.2965</td>\n","      <td>-0.0712</td>\n","      <td>0.6389</td>\n","      <td>0.6674</td>\n","      <td>-0.0783</td>\n","      <td>1.1740</td>\n","      <td>...</td>\n","      <td>-0.2274</td>\n","      <td>0.3215</td>\n","      <td>0.1535</td>\n","      <td>-0.4640</td>\n","      <td>-0.5943</td>\n","      <td>0.3973</td>\n","      <td>0.1500</td>\n","      <td>0.5178</td>\n","      <td>0.5159</td>\n","      <td>0.6091</td>\n","      <td>0.1813</td>\n","      <td>-0.4249</td>\n","      <td>0.7832</td>\n","      <td>0.6529</td>\n","      <td>0.5648</td>\n","      <td>0.4817</td>\n","      <td>0.0587</td>\n","      <td>0.5303</td>\n","      <td>0.6376</td>\n","      <td>-0.3966</td>\n","      <td>-1.4950</td>\n","      <td>-0.9625</td>\n","      <td>-0.0541</td>\n","      <td>0.6273</td>\n","      <td>0.4563</td>\n","      <td>0.0698</td>\n","      <td>0.8134</td>\n","      <td>0.1924</td>\n","      <td>0.6054</td>\n","      <td>-0.1824</td>\n","      <td>0.0042</td>\n","      <td>0.0048</td>\n","      <td>0.6670</td>\n","      <td>1.0690</td>\n","      <td>0.5523</td>\n","      <td>-0.3031</td>\n","      <td>0.1094</td>\n","      <td>0.2885</td>\n","      <td>-0.3786</td>\n","      <td>0.7125</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>23809</th>\n","      <td>id_fffb1ceed</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D2</td>\n","      <td>df1d0a5a1</td>\n","      <td>0.1394</td>\n","      <td>-0.0636</td>\n","      <td>-0.1112</td>\n","      <td>-0.5080</td>\n","      <td>-0.4713</td>\n","      <td>0.7201</td>\n","      <td>0.5773</td>\n","      <td>0.3055</td>\n","      <td>-0.4726</td>\n","      <td>0.1269</td>\n","      <td>0.2531</td>\n","      <td>0.1730</td>\n","      <td>-0.4532</td>\n","      <td>-1.0790</td>\n","      <td>0.2474</td>\n","      <td>-0.4550</td>\n","      <td>0.3588</td>\n","      <td>0.1600</td>\n","      <td>-0.7362</td>\n","      <td>-0.1103</td>\n","      <td>0.8550</td>\n","      <td>-0.4139</td>\n","      <td>0.5541</td>\n","      <td>0.2310</td>\n","      <td>-0.5573</td>\n","      <td>-0.4397</td>\n","      <td>-0.9260</td>\n","      <td>-0.2424</td>\n","      <td>-0.6686</td>\n","      <td>0.2326</td>\n","      <td>0.6456</td>\n","      <td>0.0136</td>\n","      <td>-0.5141</td>\n","      <td>-0.6320</td>\n","      <td>0.7166</td>\n","      <td>...</td>\n","      <td>0.0807</td>\n","      <td>0.4024</td>\n","      <td>-0.0895</td>\n","      <td>0.4420</td>\n","      <td>0.9641</td>\n","      <td>-0.1846</td>\n","      <td>-0.0014</td>\n","      <td>0.3154</td>\n","      <td>-0.2071</td>\n","      <td>-0.6158</td>\n","      <td>-0.2977</td>\n","      <td>0.0992</td>\n","      <td>0.6838</td>\n","      <td>0.5259</td>\n","      <td>0.7882</td>\n","      <td>0.3119</td>\n","      <td>-0.7697</td>\n","      <td>0.2203</td>\n","      <td>-1.0710</td>\n","      <td>0.5979</td>\n","      <td>0.0848</td>\n","      <td>-0.2555</td>\n","      <td>0.6293</td>\n","      <td>1.1660</td>\n","      <td>0.3329</td>\n","      <td>0.2754</td>\n","      <td>0.4108</td>\n","      <td>-0.1252</td>\n","      <td>-0.2340</td>\n","      <td>0.2267</td>\n","      <td>0.1969</td>\n","      <td>0.0262</td>\n","      <td>-0.8121</td>\n","      <td>0.3434</td>\n","      <td>0.5372</td>\n","      <td>-0.3246</td>\n","      <td>0.0631</td>\n","      <td>0.9171</td>\n","      <td>0.5258</td>\n","      <td>0.4680</td>\n","    </tr>\n","    <tr>\n","      <th>23810</th>\n","      <td>id_fffb70c0c</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D2</td>\n","      <td>ecf3b6b74</td>\n","      <td>-1.3260</td>\n","      <td>0.3478</td>\n","      <td>-0.3743</td>\n","      <td>0.9905</td>\n","      <td>-0.7178</td>\n","      <td>0.6621</td>\n","      <td>-0.2252</td>\n","      <td>-0.5565</td>\n","      <td>0.5112</td>\n","      <td>0.6727</td>\n","      <td>-0.1851</td>\n","      <td>2.8650</td>\n","      <td>-0.2140</td>\n","      <td>-0.6153</td>\n","      <td>0.8362</td>\n","      <td>0.5584</td>\n","      <td>-0.2589</td>\n","      <td>0.1292</td>\n","      <td>0.0148</td>\n","      <td>0.0949</td>\n","      <td>-0.2182</td>\n","      <td>-0.9235</td>\n","      <td>0.0749</td>\n","      <td>-1.5910</td>\n","      <td>-0.8359</td>\n","      <td>-0.9217</td>\n","      <td>0.3013</td>\n","      <td>0.1716</td>\n","      <td>0.0880</td>\n","      <td>0.1842</td>\n","      <td>0.1835</td>\n","      <td>0.5436</td>\n","      <td>-0.0533</td>\n","      <td>-0.0491</td>\n","      <td>0.9543</td>\n","      <td>...</td>\n","      <td>0.1410</td>\n","      <td>1.2640</td>\n","      <td>-0.8663</td>\n","      <td>0.8129</td>\n","      <td>-0.1514</td>\n","      <td>-0.4652</td>\n","      <td>-0.7390</td>\n","      <td>-1.3270</td>\n","      <td>0.9925</td>\n","      <td>1.0570</td>\n","      <td>-0.3355</td>\n","      <td>-0.2555</td>\n","      <td>0.8219</td>\n","      <td>0.6995</td>\n","      <td>-0.2942</td>\n","      <td>0.2408</td>\n","      <td>-0.7781</td>\n","      <td>-0.0929</td>\n","      <td>-0.0329</td>\n","      <td>0.0781</td>\n","      <td>-1.4440</td>\n","      <td>-0.0921</td>\n","      <td>0.3188</td>\n","      <td>-1.1080</td>\n","      <td>0.4895</td>\n","      <td>-0.2144</td>\n","      <td>1.0960</td>\n","      <td>0.3335</td>\n","      <td>0.4444</td>\n","      <td>-1.1130</td>\n","      <td>0.4286</td>\n","      <td>0.4426</td>\n","      <td>0.0423</td>\n","      <td>-0.3195</td>\n","      <td>-0.8086</td>\n","      <td>-0.9798</td>\n","      <td>-0.2084</td>\n","      <td>-0.1224</td>\n","      <td>-0.2715</td>\n","      <td>0.3689</td>\n","    </tr>\n","    <tr>\n","      <th>23811</th>\n","      <td>id_fffc1c3f4</td>\n","      <td>com_controle</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>cacb2b860</td>\n","      <td>0.3942</td>\n","      <td>0.3756</td>\n","      <td>0.3109</td>\n","      <td>-0.7389</td>\n","      <td>0.5505</td>\n","      <td>-0.0159</td>\n","      <td>-0.2541</td>\n","      <td>0.1745</td>\n","      <td>-0.0340</td>\n","      <td>0.4865</td>\n","      <td>-0.1854</td>\n","      <td>0.0716</td>\n","      <td>0.1729</td>\n","      <td>-0.0434</td>\n","      <td>0.1542</td>\n","      <td>-0.2192</td>\n","      <td>-0.0302</td>\n","      <td>-0.4218</td>\n","      <td>0.4057</td>\n","      <td>-0.5372</td>\n","      <td>0.1521</td>\n","      <td>-0.2651</td>\n","      <td>0.2310</td>\n","      <td>-0.8101</td>\n","      <td>0.4943</td>\n","      <td>0.6905</td>\n","      <td>-0.3720</td>\n","      <td>-1.4110</td>\n","      <td>0.4516</td>\n","      <td>1.2300</td>\n","      <td>-0.1949</td>\n","      <td>-1.3280</td>\n","      <td>-0.4276</td>\n","      <td>-0.0040</td>\n","      <td>-0.3086</td>\n","      <td>...</td>\n","      <td>0.6845</td>\n","      <td>0.7127</td>\n","      <td>0.7294</td>\n","      <td>0.4718</td>\n","      <td>-0.2020</td>\n","      <td>0.2783</td>\n","      <td>0.4934</td>\n","      <td>0.4144</td>\n","      <td>0.5449</td>\n","      <td>1.4690</td>\n","      <td>-0.6142</td>\n","      <td>0.6068</td>\n","      <td>0.3434</td>\n","      <td>0.9880</td>\n","      <td>-0.0468</td>\n","      <td>-0.1882</td>\n","      <td>-0.0087</td>\n","      <td>-0.0356</td>\n","      <td>0.5718</td>\n","      <td>0.4971</td>\n","      <td>0.1057</td>\n","      <td>0.2111</td>\n","      <td>0.6992</td>\n","      <td>0.0708</td>\n","      <td>0.6169</td>\n","      <td>0.2248</td>\n","      <td>0.5994</td>\n","      <td>0.2689</td>\n","      <td>0.0305</td>\n","      <td>1.2320</td>\n","      <td>0.5409</td>\n","      <td>0.3755</td>\n","      <td>0.7343</td>\n","      <td>0.2807</td>\n","      <td>0.4116</td>\n","      <td>0.6422</td>\n","      <td>0.2256</td>\n","      <td>0.7592</td>\n","      <td>0.6656</td>\n","      <td>0.3808</td>\n","    </tr>\n","    <tr>\n","      <th>23812</th>\n","      <td>id_fffcb9e7c</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>8b87a7a83</td>\n","      <td>0.6660</td>\n","      <td>0.2324</td>\n","      <td>0.4392</td>\n","      <td>0.2044</td>\n","      <td>0.8531</td>\n","      <td>-0.0343</td>\n","      <td>0.0323</td>\n","      <td>0.0463</td>\n","      <td>0.4299</td>\n","      <td>-0.7985</td>\n","      <td>0.5742</td>\n","      <td>0.1421</td>\n","      <td>2.2700</td>\n","      <td>0.2046</td>\n","      <td>0.5363</td>\n","      <td>-1.7330</td>\n","      <td>0.1450</td>\n","      <td>0.6097</td>\n","      <td>0.2024</td>\n","      <td>0.9865</td>\n","      <td>-0.7805</td>\n","      <td>0.9608</td>\n","      <td>0.3440</td>\n","      <td>2.7650</td>\n","      <td>0.4925</td>\n","      <td>0.6698</td>\n","      <td>0.2374</td>\n","      <td>-0.3372</td>\n","      <td>0.8771</td>\n","      <td>-2.6560</td>\n","      <td>-0.2000</td>\n","      <td>-0.2043</td>\n","      <td>0.6797</td>\n","      <td>-0.0248</td>\n","      <td>-0.0927</td>\n","      <td>...</td>\n","      <td>0.3360</td>\n","      <td>-0.6136</td>\n","      <td>0.5011</td>\n","      <td>0.9261</td>\n","      <td>0.4419</td>\n","      <td>0.0295</td>\n","      <td>0.4220</td>\n","      <td>0.4677</td>\n","      <td>-0.1184</td>\n","      <td>0.4524</td>\n","      <td>0.4135</td>\n","      <td>0.1356</td>\n","      <td>-0.5801</td>\n","      <td>0.0411</td>\n","      <td>1.0240</td>\n","      <td>1.0340</td>\n","      <td>-0.0270</td>\n","      <td>-0.4194</td>\n","      <td>0.7403</td>\n","      <td>-0.6793</td>\n","      <td>-0.1423</td>\n","      <td>0.7307</td>\n","      <td>0.7946</td>\n","      <td>-0.0650</td>\n","      <td>0.9038</td>\n","      <td>0.2324</td>\n","      <td>0.9676</td>\n","      <td>1.0940</td>\n","      <td>0.4290</td>\n","      <td>0.5187</td>\n","      <td>-0.1105</td>\n","      <td>0.4258</td>\n","      <td>-0.2012</td>\n","      <td>0.1506</td>\n","      <td>1.5230</td>\n","      <td>0.7101</td>\n","      <td>0.1732</td>\n","      <td>0.7015</td>\n","      <td>-0.6290</td>\n","      <td>0.0740</td>\n","    </tr>\n","    <tr>\n","      <th>23813</th>\n","      <td>id_ffffdd77b</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>972f41291</td>\n","      <td>-0.8598</td>\n","      <td>1.0240</td>\n","      <td>-0.1361</td>\n","      <td>0.7952</td>\n","      <td>-0.3611</td>\n","      <td>-3.6750</td>\n","      <td>-1.2420</td>\n","      <td>0.9146</td>\n","      <td>3.0790</td>\n","      <td>1.2460</td>\n","      <td>1.9460</td>\n","      <td>1.4370</td>\n","      <td>2.9780</td>\n","      <td>2.2370</td>\n","      <td>-0.6818</td>\n","      <td>0.6870</td>\n","      <td>-1.1060</td>\n","      <td>0.0182</td>\n","      <td>-0.9247</td>\n","      <td>-0.0738</td>\n","      <td>-0.1919</td>\n","      <td>-0.7722</td>\n","      <td>-1.4050</td>\n","      <td>-1.0050</td>\n","      <td>-1.1170</td>\n","      <td>-0.5293</td>\n","      <td>-1.1720</td>\n","      <td>-0.2885</td>\n","      <td>0.1599</td>\n","      <td>-0.4250</td>\n","      <td>0.3591</td>\n","      <td>-0.1420</td>\n","      <td>-0.9530</td>\n","      <td>-0.2005</td>\n","      <td>-1.8340</td>\n","      <td>...</td>\n","      <td>-6.9170</td>\n","      <td>-1.8640</td>\n","      <td>-2.5090</td>\n","      <td>-4.7130</td>\n","      <td>-1.7250</td>\n","      <td>-3.8650</td>\n","      <td>-3.0800</td>\n","      <td>-4.1530</td>\n","      <td>-1.2030</td>\n","      <td>-1.1690</td>\n","      <td>-4.1460</td>\n","      <td>-1.2670</td>\n","      <td>-1.1300</td>\n","      <td>-2.4390</td>\n","      <td>0.1591</td>\n","      <td>-2.2490</td>\n","      <td>-2.5860</td>\n","      <td>-1.9520</td>\n","      <td>-2.1810</td>\n","      <td>-4.6690</td>\n","      <td>-3.9450</td>\n","      <td>-2.9560</td>\n","      <td>-2.7930</td>\n","      <td>-2.1560</td>\n","      <td>-2.4100</td>\n","      <td>-1.8190</td>\n","      <td>-3.3480</td>\n","      <td>-0.1414</td>\n","      <td>-2.6430</td>\n","      <td>-2.5810</td>\n","      <td>-3.3890</td>\n","      <td>-1.7450</td>\n","      <td>-6.6300</td>\n","      <td>-4.0950</td>\n","      <td>-7.3860</td>\n","      <td>-1.4160</td>\n","      <td>-3.5770</td>\n","      <td>-0.4775</td>\n","      <td>-2.1500</td>\n","      <td>-4.2520</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>23814 rows × 877 columns</p>\n","</div>"],"text/plain":["                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n","1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n","2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n","3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n","4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n","...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n","23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n","23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n","23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n","23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n","23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n","\n","[23814 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":18}]},{"cell_type":"markdown","metadata":{"id":"zGB4Kq8JvmZ5"},"source":["A base de dados que usamos até o momento tem uma variável chamada ```composto```mas entendemos, com a ajuda da Vanessa, que essa não é a melhor nomenclatura para representa-la. \n","Por isso, vamos usar a função ```map``` da biblioteca Pandas para renomear essa coluna.\n","É importante destacar que passamos o parâmetro ```inplace = True```, esse parâmetro faz com que os dados sejam modificados no local e o dataframe será atualizado. \n","Caso esse parâmetro não seja declarado, o default é ```inplace = False``` e o retorno será uma cópia do objeto e caso você queira, precisa salva-lo com um outro nome."]},{"cell_type":"code","metadata":{"id":"CFse2h0Vcrp4","executionInfo":{"status":"ok","timestamp":1620128372255,"user_tz":180,"elapsed":621,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}}},"source":["mapa = {'droga': 'composto'}\n","dados.rename(columns = mapa, inplace = True)"],"execution_count":19,"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","executionInfo":{"status":"ok","timestamp":1620128376052,"user_tz":180,"elapsed":628,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"48f0560e-fec5-4056-a469-c3b17613a5a4"},"source":["dados.head()"],"execution_count":20,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>composto</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>...</th>\n","      <th>c-60</th>\n","      <th>c-61</th>\n","      <th>c-62</th>\n","      <th>c-63</th>\n","      <th>c-64</th>\n","      <th>c-65</th>\n","      <th>c-66</th>\n","      <th>c-67</th>\n","      <th>c-68</th>\n","      <th>c-69</th>\n","      <th>c-70</th>\n","      <th>c-71</th>\n","      <th>c-72</th>\n","      <th>c-73</th>\n","      <th>c-74</th>\n","      <th>c-75</th>\n","      <th>c-76</th>\n","      <th>c-77</th>\n","      <th>c-78</th>\n","      <th>c-79</th>\n","      <th>c-80</th>\n","      <th>c-81</th>\n","      <th>c-82</th>\n","      <th>c-83</th>\n","      <th>c-84</th>\n","      <th>c-85</th>\n","      <th>c-86</th>\n","      <th>c-87</th>\n","      <th>c-88</th>\n","      <th>c-89</th>\n","      <th>c-90</th>\n","      <th>c-91</th>\n","      <th>c-92</th>\n","      <th>c-93</th>\n","      <th>c-94</th>\n","      <th>c-95</th>\n","      <th>c-96</th>\n","      <th>c-97</th>\n","      <th>c-98</th>\n","      <th>c-99</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>id_000644bb2</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>b68db1d53</td>\n","      <td>1.0620</td>\n","      <td>0.5577</td>\n","      <td>-0.2479</td>\n","      <td>-0.6208</td>\n","      <td>-0.1944</td>\n","      <td>-1.0120</td>\n","      <td>-1.0220</td>\n","      <td>-0.0326</td>\n","      <td>0.5548</td>\n","      <td>-0.0921</td>\n","      <td>1.1830</td>\n","      <td>0.1530</td>\n","      <td>0.5574</td>\n","      <td>-0.4015</td>\n","      <td>0.1789</td>\n","      <td>-0.6528</td>\n","      <td>-0.7969</td>\n","      <td>0.6342</td>\n","      <td>0.1778</td>\n","      <td>-0.3694</td>\n","      <td>-0.5688</td>\n","      <td>-1.1360</td>\n","      <td>-1.1880</td>\n","      <td>0.6940</td>\n","      <td>0.4393</td>\n","      <td>0.2664</td>\n","      <td>0.1907</td>\n","      <td>0.1628</td>\n","      <td>-0.2853</td>\n","      <td>0.5819</td>\n","      <td>0.2934</td>\n","      <td>-0.5584</td>\n","      <td>-0.0916</td>\n","      <td>-0.3010</td>\n","      <td>-0.1537</td>\n","      <td>...</td>\n","      <td>0.4805</td>\n","      <td>0.4965</td>\n","      <td>0.3680</td>\n","      <td>0.8427</td>\n","      <td>0.1042</td>\n","      <td>0.1403</td>\n","      <td>0.1758</td>\n","      <td>1.2570</td>\n","      <td>-0.5979</td>\n","      <td>1.2250</td>\n","      <td>-0.0553</td>\n","      <td>0.7351</td>\n","      <td>0.5810</td>\n","      <td>0.9590</td>\n","      <td>0.2427</td>\n","      <td>0.0495</td>\n","      <td>0.4141</td>\n","      <td>0.8432</td>\n","      <td>0.6162</td>\n","      <td>-0.7318</td>\n","      <td>1.2120</td>\n","      <td>0.6362</td>\n","      <td>-0.4427</td>\n","      <td>0.1288</td>\n","      <td>1.4840</td>\n","      <td>0.1799</td>\n","      <td>0.5367</td>\n","      <td>-0.1111</td>\n","      <td>-1.0120</td>\n","      <td>0.6685</td>\n","      <td>0.2862</td>\n","      <td>0.2584</td>\n","      <td>0.8076</td>\n","      <td>0.5523</td>\n","      <td>-0.1912</td>\n","      <td>0.6584</td>\n","      <td>-0.3981</td>\n","      <td>0.2139</td>\n","      <td>0.3801</td>\n","      <td>0.4176</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>id_000779bfc</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>df89a8e5a</td>\n","      <td>0.0743</td>\n","      <td>0.4087</td>\n","      <td>0.2991</td>\n","      <td>0.0604</td>\n","      <td>1.0190</td>\n","      <td>0.5207</td>\n","      <td>0.2341</td>\n","      <td>0.3372</td>\n","      <td>-0.4047</td>\n","      <td>0.8507</td>\n","      <td>-1.1520</td>\n","      <td>-0.4201</td>\n","      <td>-0.0958</td>\n","      <td>0.4590</td>\n","      <td>0.0803</td>\n","      <td>0.2250</td>\n","      <td>0.5293</td>\n","      <td>0.2839</td>\n","      <td>-0.3494</td>\n","      <td>0.2883</td>\n","      <td>0.9449</td>\n","      <td>-0.1646</td>\n","      <td>-0.2657</td>\n","      <td>-0.3372</td>\n","      <td>0.3135</td>\n","      <td>-0.4316</td>\n","      <td>0.4773</td>\n","      <td>0.2075</td>\n","      <td>-0.4216</td>\n","      <td>-0.1161</td>\n","      <td>-0.0499</td>\n","      <td>-0.2627</td>\n","      <td>0.9959</td>\n","      <td>-0.2483</td>\n","      <td>0.2655</td>\n","      <td>...</td>\n","      <td>0.4083</td>\n","      <td>0.0319</td>\n","      <td>0.3905</td>\n","      <td>0.7099</td>\n","      <td>0.2912</td>\n","      <td>0.4151</td>\n","      <td>-0.2840</td>\n","      <td>-0.3104</td>\n","      <td>-0.6373</td>\n","      <td>0.2887</td>\n","      <td>-0.0765</td>\n","      <td>0.2539</td>\n","      <td>0.4443</td>\n","      <td>0.5932</td>\n","      <td>0.2031</td>\n","      <td>0.7639</td>\n","      <td>0.5499</td>\n","      <td>-0.3322</td>\n","      <td>-0.0977</td>\n","      <td>0.4329</td>\n","      <td>-0.2782</td>\n","      <td>0.7827</td>\n","      <td>0.5934</td>\n","      <td>0.3402</td>\n","      <td>0.1499</td>\n","      <td>0.4420</td>\n","      <td>0.9366</td>\n","      <td>0.8193</td>\n","      <td>-0.4236</td>\n","      <td>0.3192</td>\n","      <td>-0.4265</td>\n","      <td>0.7543</td>\n","      <td>0.4708</td>\n","      <td>0.0230</td>\n","      <td>0.2957</td>\n","      <td>0.4899</td>\n","      <td>0.1522</td>\n","      <td>0.1241</td>\n","      <td>0.6077</td>\n","      <td>0.7371</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>id_000a6266a</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>18bb41b2c</td>\n","      <td>0.6280</td>\n","      <td>0.5817</td>\n","      <td>1.5540</td>\n","      <td>-0.0764</td>\n","      <td>-0.0323</td>\n","      <td>1.2390</td>\n","      <td>0.1715</td>\n","      <td>0.2155</td>\n","      <td>0.0065</td>\n","      <td>1.2300</td>\n","      <td>-0.4797</td>\n","      <td>-0.5631</td>\n","      <td>-0.0366</td>\n","      <td>-1.8300</td>\n","      <td>0.6057</td>\n","      <td>-0.3278</td>\n","      <td>0.6042</td>\n","      <td>-0.3075</td>\n","      <td>-0.1147</td>\n","      <td>-0.0570</td>\n","      <td>-0.0799</td>\n","      <td>-0.8181</td>\n","      <td>-1.5320</td>\n","      <td>0.2307</td>\n","      <td>0.4901</td>\n","      <td>0.4780</td>\n","      <td>-1.3970</td>\n","      <td>4.6240</td>\n","      <td>-0.0437</td>\n","      <td>1.2870</td>\n","      <td>-1.8530</td>\n","      <td>0.6069</td>\n","      <td>0.4290</td>\n","      <td>0.1783</td>\n","      <td>0.0018</td>\n","      <td>...</td>\n","      <td>-0.5477</td>\n","      <td>-0.7576</td>\n","      <td>-0.0444</td>\n","      <td>0.1894</td>\n","      <td>-0.0014</td>\n","      <td>-2.3640</td>\n","      <td>-0.4682</td>\n","      <td>0.1210</td>\n","      <td>-0.5177</td>\n","      <td>-0.0604</td>\n","      <td>0.1682</td>\n","      <td>-0.4436</td>\n","      <td>0.4963</td>\n","      <td>0.1363</td>\n","      <td>0.3335</td>\n","      <td>0.9760</td>\n","      <td>-0.0427</td>\n","      <td>-0.1235</td>\n","      <td>0.0959</td>\n","      <td>0.0690</td>\n","      <td>-0.9416</td>\n","      <td>-0.7548</td>\n","      <td>-0.1109</td>\n","      <td>-0.6272</td>\n","      <td>0.3019</td>\n","      <td>0.1172</td>\n","      <td>0.1093</td>\n","      <td>-0.3113</td>\n","      <td>0.3019</td>\n","      <td>-0.0873</td>\n","      <td>-0.7250</td>\n","      <td>-0.6297</td>\n","      <td>0.6103</td>\n","      <td>0.0223</td>\n","      <td>-1.3240</td>\n","      <td>-0.3174</td>\n","      <td>-0.6417</td>\n","      <td>-0.2187</td>\n","      <td>-1.4080</td>\n","      <td>0.6931</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>id_0015fd391</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8c7f86626</td>\n","      <td>-0.5138</td>\n","      <td>-0.2491</td>\n","      <td>-0.2656</td>\n","      <td>0.5288</td>\n","      <td>4.0620</td>\n","      <td>-0.8095</td>\n","      <td>-1.9590</td>\n","      <td>0.1792</td>\n","      <td>-0.1321</td>\n","      <td>-1.0600</td>\n","      <td>-0.8269</td>\n","      <td>-0.3584</td>\n","      <td>-0.8511</td>\n","      <td>-0.5844</td>\n","      <td>-2.5690</td>\n","      <td>0.8183</td>\n","      <td>-0.0532</td>\n","      <td>-0.8554</td>\n","      <td>0.1160</td>\n","      <td>-2.3520</td>\n","      <td>2.1200</td>\n","      <td>-1.1580</td>\n","      <td>-0.7191</td>\n","      <td>-0.8004</td>\n","      <td>-1.4670</td>\n","      <td>-0.0107</td>\n","      <td>-0.8995</td>\n","      <td>0.2406</td>\n","      <td>-0.2479</td>\n","      <td>-1.0890</td>\n","      <td>-0.7575</td>\n","      <td>0.0881</td>\n","      <td>-2.7370</td>\n","      <td>0.8745</td>\n","      <td>0.5787</td>\n","      <td>...</td>\n","      <td>-2.1220</td>\n","      <td>-0.3752</td>\n","      <td>-2.3820</td>\n","      <td>-3.7350</td>\n","      <td>-2.9740</td>\n","      <td>-1.4930</td>\n","      <td>-1.6600</td>\n","      <td>-3.1660</td>\n","      <td>0.2816</td>\n","      <td>-0.2990</td>\n","      <td>-1.1870</td>\n","      <td>-0.5044</td>\n","      <td>-1.7750</td>\n","      <td>-1.6120</td>\n","      <td>-0.9215</td>\n","      <td>-1.0810</td>\n","      <td>-3.0520</td>\n","      <td>-3.4470</td>\n","      <td>-2.7740</td>\n","      <td>-1.8460</td>\n","      <td>-0.5568</td>\n","      <td>-3.3960</td>\n","      <td>-2.9510</td>\n","      <td>-1.1550</td>\n","      <td>-3.2620</td>\n","      <td>-1.5390</td>\n","      <td>-2.4600</td>\n","      <td>-0.9417</td>\n","      <td>-1.5550</td>\n","      <td>0.2431</td>\n","      <td>-2.0990</td>\n","      <td>-0.6441</td>\n","      <td>-5.6300</td>\n","      <td>-1.3780</td>\n","      <td>-0.8632</td>\n","      <td>-1.2880</td>\n","      <td>-1.6210</td>\n","      <td>-0.8784</td>\n","      <td>-0.3876</td>\n","      <td>-0.8154</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>id_001626bd3</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D2</td>\n","      <td>7cbed3131</td>\n","      <td>-0.3254</td>\n","      <td>-0.4009</td>\n","      <td>0.9700</td>\n","      <td>0.6919</td>\n","      <td>1.4180</td>\n","      <td>-0.8244</td>\n","      <td>-0.2800</td>\n","      <td>-0.1498</td>\n","      <td>-0.8789</td>\n","      <td>0.8630</td>\n","      <td>-0.2219</td>\n","      <td>-0.5121</td>\n","      <td>-0.9577</td>\n","      <td>1.1750</td>\n","      <td>0.2042</td>\n","      <td>0.1970</td>\n","      <td>0.1244</td>\n","      <td>-1.7090</td>\n","      <td>-0.3543</td>\n","      <td>-0.5160</td>\n","      <td>-0.3330</td>\n","      <td>-0.2685</td>\n","      <td>0.7649</td>\n","      <td>0.2057</td>\n","      <td>1.3720</td>\n","      <td>0.6835</td>\n","      <td>0.8056</td>\n","      <td>-0.3754</td>\n","      <td>-1.2090</td>\n","      <td>0.2965</td>\n","      <td>-0.0712</td>\n","      <td>0.6389</td>\n","      <td>0.6674</td>\n","      <td>-0.0783</td>\n","      <td>1.1740</td>\n","      <td>...</td>\n","      <td>-0.2274</td>\n","      <td>0.3215</td>\n","      <td>0.1535</td>\n","      <td>-0.4640</td>\n","      <td>-0.5943</td>\n","      <td>0.3973</td>\n","      <td>0.1500</td>\n","      <td>0.5178</td>\n","      <td>0.5159</td>\n","      <td>0.6091</td>\n","      <td>0.1813</td>\n","      <td>-0.4249</td>\n","      <td>0.7832</td>\n","      <td>0.6529</td>\n","      <td>0.5648</td>\n","      <td>0.4817</td>\n","      <td>0.0587</td>\n","      <td>0.5303</td>\n","      <td>0.6376</td>\n","      <td>-0.3966</td>\n","      <td>-1.4950</td>\n","      <td>-0.9625</td>\n","      <td>-0.0541</td>\n","      <td>0.6273</td>\n","      <td>0.4563</td>\n","      <td>0.0698</td>\n","      <td>0.8134</td>\n","      <td>0.1924</td>\n","      <td>0.6054</td>\n","      <td>-0.1824</td>\n","      <td>0.0042</td>\n","      <td>0.0048</td>\n","      <td>0.6670</td>\n","      <td>1.0690</td>\n","      <td>0.5523</td>\n","      <td>-0.3031</td>\n","      <td>0.1094</td>\n","      <td>0.2885</td>\n","      <td>-0.3786</td>\n","      <td>0.7125</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 877 columns</p>\n","</div>"],"text/plain":["             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n","1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n","2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n","3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n","4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n","\n","[5 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":20}]},{"cell_type":"markdown","metadata":{"id":"i7mgnrykiMNb"},"source":["Queremos melhorar a visualização do nosso histograma de compostos e, como existem mais de 3.000 variações na nossa base de dados, decidimos elencar os 5 compostos que mais aparecem.\n","Para isso, vamos usar a função ```value_counts``` (função presente na biblioteca Pandas e que conta a ocorrência dos diferentes valores) e, como queremos saber somente os 5 elementos mais frequentes, também declaramos o ```index[0:5]```. Essa parte final, faz com que o ```value_counts```se atenha à contagem dos maiores valores e apresente como resultado apenas o index do  intervalo [0, 5[, ou seja, o nome dos 5 maiores valores. "]},{"cell_type":"code","metadata":{"id":"D5hK5mcVej_G","executionInfo":{"status":"ok","timestamp":1620128691806,"user_tz":180,"elapsed":658,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}}},"source":["cod_compostos = dados['composto'].value_counts().index[0:5]"],"execution_count":21,"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","executionInfo":{"status":"ok","timestamp":1620128710903,"user_tz":180,"elapsed":635,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"deeb489c-24b9-4dab-8bbe-105d8f046dc8"},"source":["cod_compostos"],"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['cacb2b860', '87d714366', '9f80f3f77', '8b87a7a83', '5628cb3ee'], dtype='object')"]},"metadata":{"tags":[]},"execution_count":22}]},{"cell_type":"markdown","metadata":{"id":"1JANbNGx4wQO"},"source":["Exitem algumas maneiras de filtrar uma base de dados e optamos em usar a função ```query``` do Pandas e, somente a título de curiosidade, essa função é bastante análoga ao SQL (linguagem de programação para bancos de dados).\n","A estrutura dela é bastante simplificada, precisamos apenas definir o dataframe, chamar a função e passar como parâmetro a condição que deve ser \n","filtrada no nosso conjunto de dados.\n","\n","Nesta parte do projeto, queremos realizar um filtro em nossos dados, selecionando apenas as linhas nas quais o composto esteja dentro da nossa lista ```cod_composto``` (lista que representa os 5 compostos mais testados no experimento) e vamos utilizar o método ```query``` para resolver este problema. \n","\n","Como parâmetro da função, passamos uma string contendo a lógica para realização da seleção dos dados. O que queremos é o seguinte: o ```query```precisa retornar para nós todas as linhas contendo os 5 compostos mais utilizados. Logo, a string necessária para isso é: ```composto in @cod_compostos```. \n","\n","Usamos ```composto``` porque essa é a coluna a ser verificada no dataframe e ```cod_compostos``` por ser a lista com os top 5 compostos, o detalhe aqui é que o ```@``` é necessário para informar o ```query``` que ```cod_composto``` é uma variável que já foi definida fora da função."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"id":"_GlSwTMGfpFs","executionInfo":{"status":"ok","timestamp":1620129187492,"user_tz":180,"elapsed":1154,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"f107807a-0d35-494a-f317-a2017f9fb56e"},"source":["dados.query('composto in @cod_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","      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<td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>23793</th>\n","      <td>id_ffd26f361</td>\n","      <td>com_controle</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>cacb2b860</td>\n","      <td>0.6008</td>\n","      <td>0.2781</td>\n","      <td>-0.3319</td>\n","      <td>-0.8782</td>\n","      <td>0.9281</td>\n","      <td>0.7535</td>\n","      <td>0.5971</td>\n","      <td>1.6350</td>\n","      <td>-0.3146</td>\n","      <td>0.4984</td>\n","      <td>-1.1890</td>\n","      <td>0.3772</td>\n","      <td>-0.8196</td>\n","      <td>0.1083</td>\n","      <td>-2.0350</td>\n","      <td>0.4135</td>\n","      <td>0.7586</td>\n","      <td>-0.4024</td>\n","      <td>-0.0449</td>\n","      <td>0.3335</td>\n","      <td>0.2358</td>\n","      <td>0.7919</td>\n","      <td>-0.8775</td>\n","      <td>0.4232</td>\n","      <td>1.8460</td>\n","      <td>-2.0940</td>\n","      <td>0.1438</td>\n","      <td>-0.6604</td>\n","      <td>0.7243</td>\n","      <td>0.0338</td>\n","      <td>-0.0182</td>\n","      <td>-0.2022</td>\n","      <td>0.8827</td>\n","      <td>0.3147</td>\n","      <td>-0.9263</td>\n","      <td>...</td>\n","      <td>0.1934</td>\n","      <td>1.2240</td>\n","      <td>-0.1178</td>\n","      <td>0.1459</td>\n","      <td>-0.1242</td>\n","      <td>0.3106</td>\n","      <td>-0.7959</td>\n","      <td>0.5681</td>\n","      <td>0.3663</td>\n","      <td>0.4874</td>\n","      <td>-0.0548</td>\n","      <td>0.1810</td>\n","      <td>1.3470</td>\n","      <td>1.6210</td>\n","      <td>-0.8260</td>\n","      <td>0.3377</td>\n","      <td>0.3264</td>\n","      <td>0.9241</td>\n","      <td>0.3012</td>\n","      <td>1.2980</td>\n","      <td>-0.2789</td>\n","      <td>0.7019</td>\n","      <td>-0.3528</td>\n","      <td>0.7383</td>\n","      <td>1.0300</td>\n","      <td>0.6527</td>\n","      <td>1.6750</td>\n","      <td>-0.5046</td>\n","      <td>0.2942</td>\n","      <td>0.2950</td>\n","      <td>1.2470</td>\n","      <td>0.9569</td>\n","      <td>-0.2065</td>\n","      <td>-0.4918</td>\n","      <td>0.7863</td>\n","      <td>0.0504</td>\n","      <td>0.8813</td>\n","      <td>0.7757</td>\n","      <td>-0.5272</td>\n","      <td>0.7082</td>\n","    </tr>\n","    <tr>\n","      <th>23802</th>\n","      <td>id_fff3976bd</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>87d714366</td>\n","      <td>3.2890</td>\n","      <td>2.1270</td>\n","      <td>0.9770</td>\n","      <td>2.0490</td>\n","      <td>2.3170</td>\n","      <td>-0.5355</td>\n","      <td>-0.6357</td>\n","      <td>-6.9060</td>\n","      <td>-4.4830</td>\n","      <td>-2.8400</td>\n","      <td>-5.3310</td>\n","      <td>0.6547</td>\n","      <td>-2.2080</td>\n","      <td>3.6030</td>\n","      <td>0.6380</td>\n","      <td>-2.1280</td>\n","      <td>-3.1680</td>\n","      <td>-4.2180</td>\n","      <td>-0.3170</td>\n","      <td>0.2140</td>\n","      <td>-1.7660</td>\n","      <td>-1.9700</td>\n","      <td>-1.4820</td>\n","      <td>-1.3710</td>\n","      <td>-0.2628</td>\n","      <td>-0.5276</td>\n","      <td>-2.4160</td>\n","      <td>-0.4638</td>\n","      <td>-3.8630</td>\n","      <td>-0.8880</td>\n","      <td>-1.9850</td>\n","      <td>2.0530</td>\n","      <td>-1.4700</td>\n","      <td>-3.3220</td>\n","      <td>1.8800</td>\n","      <td>...</td>\n","      <td>-9.9170</td>\n","      <td>-4.0200</td>\n","      <td>-6.7560</td>\n","      <td>-9.9170</td>\n","      <td>-4.1240</td>\n","      <td>-8.5110</td>\n","      <td>-5.7500</td>\n","      <td>-8.4760</td>\n","      <td>-6.9470</td>\n","      <td>-4.7650</td>\n","      <td>-9.7690</td>\n","      <td>-5.7900</td>\n","      <td>-9.9170</td>\n","      <td>-5.7450</td>\n","      <td>-2.3570</td>\n","      <td>-9.1190</td>\n","      <td>-4.5980</td>\n","      <td>-8.7760</td>\n","      <td>-7.7980</td>\n","      <td>-4.1620</td>\n","      <td>-6.1510</td>\n","      <td>-5.7400</td>\n","      <td>-6.8700</td>\n","      <td>-9.1000</td>\n","      <td>-3.3360</td>\n","      <td>-6.6420</td>\n","      <td>-2.2750</td>\n","      <td>-3.4720</td>\n","      <td>-6.2670</td>\n","      <td>-6.3980</td>\n","      <td>-8.6300</td>\n","      <td>-8.1490</td>\n","      <td>-6.2900</td>\n","      <td>-8.0970</td>\n","      <td>-8.7330</td>\n","      <td>-2.3780</td>\n","      <td>-8.4480</td>\n","      <td>-4.4550</td>\n","      <td>-5.7930</td>\n","      <td>-3.7000</td>\n","    </tr>\n","    <tr>\n","      <th>23805</th>\n","      <td>id_fff6df1c5</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>5628cb3ee</td>\n","      <td>1.7380</td>\n","      <td>-1.2900</td>\n","      <td>-0.4533</td>\n","      <td>-1.1640</td>\n","      <td>-0.4841</td>\n","      <td>-0.2392</td>\n","      <td>-0.1774</td>\n","      <td>-1.3980</td>\n","      <td>-0.4059</td>\n","      <td>0.1553</td>\n","      <td>0.1083</td>\n","      <td>-0.8020</td>\n","      <td>-0.5039</td>\n","      <td>-0.7167</td>\n","      <td>-0.5016</td>\n","      <td>-0.9369</td>\n","      <td>-0.5864</td>\n","      <td>-0.1009</td>\n","      <td>0.8987</td>\n","      <td>0.3389</td>\n","      <td>-1.3460</td>\n","      <td>-0.5087</td>\n","      <td>-0.0892</td>\n","      <td>-0.6559</td>\n","      <td>0.0864</td>\n","      <td>-0.6251</td>\n","      <td>0.2471</td>\n","      <td>-0.4523</td>\n","      <td>-0.0389</td>\n","      <td>1.0340</td>\n","      <td>0.0796</td>\n","      <td>-0.2560</td>\n","      <td>-0.7851</td>\n","      <td>-0.1687</td>\n","      <td>-1.2890</td>\n","      <td>...</td>\n","      <td>0.2866</td>\n","      <td>0.3854</td>\n","      <td>-0.4986</td>\n","      <td>0.2883</td>\n","      <td>0.5843</td>\n","      <td>0.0907</td>\n","      <td>-0.9303</td>\n","      <td>0.1981</td>\n","      <td>0.6515</td>\n","      <td>0.2877</td>\n","      <td>0.4389</td>\n","      <td>-0.3859</td>\n","      <td>0.5203</td>\n","      <td>-1.1070</td>\n","      <td>2.3870</td>\n","      <td>0.1820</td>\n","      <td>-0.6434</td>\n","      <td>-0.9722</td>\n","      <td>-0.4200</td>\n","      <td>-0.5693</td>\n","      <td>1.0700</td>\n","      <td>1.1110</td>\n","      <td>-0.5117</td>\n","      <td>-1.2130</td>\n","      <td>0.3769</td>\n","      <td>0.5296</td>\n","      <td>1.0400</td>\n","      <td>0.0587</td>\n","      <td>1.0150</td>\n","      <td>-0.7669</td>\n","      <td>0.2865</td>\n","      <td>0.5974</td>\n","      <td>-0.2727</td>\n","      <td>0.1188</td>\n","      <td>1.0770</td>\n","      <td>-1.0250</td>\n","      <td>0.1516</td>\n","      <td>0.4503</td>\n","      <td>-0.6312</td>\n","      <td>-0.8302</td>\n","    </tr>\n","    <tr>\n","      <th>23811</th>\n","      <td>id_fffc1c3f4</td>\n","      <td>com_controle</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>cacb2b860</td>\n","      <td>0.3942</td>\n","      <td>0.3756</td>\n","      <td>0.3109</td>\n","      <td>-0.7389</td>\n","      <td>0.5505</td>\n","      <td>-0.0159</td>\n","      <td>-0.2541</td>\n","      <td>0.1745</td>\n","      <td>-0.0340</td>\n","      <td>0.4865</td>\n","      <td>-0.1854</td>\n","      <td>0.0716</td>\n","      <td>0.1729</td>\n","      <td>-0.0434</td>\n","      <td>0.1542</td>\n","      <td>-0.2192</td>\n","      <td>-0.0302</td>\n","      <td>-0.4218</td>\n","      <td>0.4057</td>\n","      <td>-0.5372</td>\n","      <td>0.1521</td>\n","      <td>-0.2651</td>\n","      <td>0.2310</td>\n","      <td>-0.8101</td>\n","      <td>0.4943</td>\n","      <td>0.6905</td>\n","      <td>-0.3720</td>\n","      <td>-1.4110</td>\n","      <td>0.4516</td>\n","      <td>1.2300</td>\n","      <td>-0.1949</td>\n","      <td>-1.3280</td>\n","      <td>-0.4276</td>\n","      <td>-0.0040</td>\n","      <td>-0.3086</td>\n","      <td>...</td>\n","      <td>0.6845</td>\n","      <td>0.7127</td>\n","      <td>0.7294</td>\n","      <td>0.4718</td>\n","      <td>-0.2020</td>\n","      <td>0.2783</td>\n","      <td>0.4934</td>\n","      <td>0.4144</td>\n","      <td>0.5449</td>\n","      <td>1.4690</td>\n","      <td>-0.6142</td>\n","      <td>0.6068</td>\n","      <td>0.3434</td>\n","      <td>0.9880</td>\n","      <td>-0.0468</td>\n","      <td>-0.1882</td>\n","      <td>-0.0087</td>\n","      <td>-0.0356</td>\n","      <td>0.5718</td>\n","      <td>0.4971</td>\n","      <td>0.1057</td>\n","      <td>0.2111</td>\n","      <td>0.6992</td>\n","      <td>0.0708</td>\n","      <td>0.6169</td>\n","      <td>0.2248</td>\n","      <td>0.5994</td>\n","      <td>0.2689</td>\n","      <td>0.0305</td>\n","      <td>1.2320</td>\n","      <td>0.5409</td>\n","      <td>0.3755</td>\n","      <td>0.7343</td>\n","      <td>0.2807</td>\n","      <td>0.4116</td>\n","      <td>0.6422</td>\n","      <td>0.2256</td>\n","      <td>0.7592</td>\n","      <td>0.6656</td>\n","      <td>0.3808</td>\n","    </tr>\n","    <tr>\n","      <th>23812</th>\n","      <td>id_fffcb9e7c</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>8b87a7a83</td>\n","      <td>0.6660</td>\n","      <td>0.2324</td>\n","      <td>0.4392</td>\n","      <td>0.2044</td>\n","      <td>0.8531</td>\n","      <td>-0.0343</td>\n","      <td>0.0323</td>\n","      <td>0.0463</td>\n","      <td>0.4299</td>\n","      <td>-0.7985</td>\n","      <td>0.5742</td>\n","      <td>0.1421</td>\n","      <td>2.2700</td>\n","      <td>0.2046</td>\n","      <td>0.5363</td>\n","      <td>-1.7330</td>\n","      <td>0.1450</td>\n","      <td>0.6097</td>\n","      <td>0.2024</td>\n","      <td>0.9865</td>\n","      <td>-0.7805</td>\n","      <td>0.9608</td>\n","      <td>0.3440</td>\n","      <td>2.7650</td>\n","      <td>0.4925</td>\n","      <td>0.6698</td>\n","      <td>0.2374</td>\n","      <td>-0.3372</td>\n","      <td>0.8771</td>\n","      <td>-2.6560</td>\n","      <td>-0.2000</td>\n","      <td>-0.2043</td>\n","      <td>0.6797</td>\n","      <td>-0.0248</td>\n","      <td>-0.0927</td>\n","      <td>...</td>\n","      <td>0.3360</td>\n","      <td>-0.6136</td>\n","      <td>0.5011</td>\n","      <td>0.9261</td>\n","      <td>0.4419</td>\n","      <td>0.0295</td>\n","      <td>0.4220</td>\n","      <td>0.4677</td>\n","      <td>-0.1184</td>\n","      <td>0.4524</td>\n","      <td>0.4135</td>\n","      <td>0.1356</td>\n","      <td>-0.5801</td>\n","      <td>0.0411</td>\n","      <td>1.0240</td>\n","      <td>1.0340</td>\n","      <td>-0.0270</td>\n","      <td>-0.4194</td>\n","      <td>0.7403</td>\n","      <td>-0.6793</td>\n","      <td>-0.1423</td>\n","      <td>0.7307</td>\n","      <td>0.7946</td>\n","      <td>-0.0650</td>\n","      <td>0.9038</td>\n","      <td>0.2324</td>\n","      <td>0.9676</td>\n","      <td>1.0940</td>\n","      <td>0.4290</td>\n","      <td>0.5187</td>\n","      <td>-0.1105</td>\n","      <td>0.4258</td>\n","      <td>-0.2012</td>\n","      <td>0.1506</td>\n","      <td>1.5230</td>\n","      <td>0.7101</td>\n","      <td>0.1732</td>\n","      <td>0.7015</td>\n","      <td>-0.6290</td>\n","      <td>0.0740</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>3235 rows × 877 columns</p>\n","</div>"],"text/plain":["                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n","7      id_0020d0484     com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n","16     id_002fb9c19     com_droga     48   D1  ... -9.9840 -9.9840 -9.9840 -6.7840\n","25     id_0054388ec  com_controle     48   D1  ...  0.8837  0.5534  0.8976  1.0050\n","38     id_0079af0fb  com_controle     24   D1  ...  0.2187  0.0737  0.6498 -1.4820\n","40     id_007bfbb91  com_controle     24   D2  ... -0.5751  0.3362  0.8543  0.9180\n","...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n","23793  id_ffd26f361  com_controle     48   D2  ...  0.8813  0.7757 -0.5272  0.7082\n","23802  id_fff3976bd     com_droga     24   D1  ... -8.4480 -4.4550 -5.7930 -3.7000\n","23805  id_fff6df1c5     com_droga     48   D2  ...  0.1516  0.4503 -0.6312 -0.8302\n","23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n","23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n","\n","[3235 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":23}]},{"cell_type":"markdown","metadata":{"id":"p9FQo1EuFF8M"},"source":["Agora que vimos que a nossa filtragem funcionou e que temos como retorno uma base de dados com 3.235 linhas, podemos usar a função ```query```como parâmetro para o ```countplot```, o nosso gráfico de barras.\n","O ```countplot``` é um gráfico pré-programado da biblioteca ```Seaborn```e, por isso, precisaremos fazer a importação padrão da mesma (```import seaborn as sns```). Adicionalmente, aqui no Google Colaboratory, para que possamos enxergar o gráfico com os padrões de configuração da biblioteca, precisamos rodar ```sns.set()```.\n","Além disso, para refinar a apresentação do gráfico, podemos utilizar algumas funcionalidades da biblioteca ```Matplotlib``` (fazendo, primeiramente, sua importação - ```import matplotlib.pyplt as plt```).\n","Também estamos definindo o tamanho do gráfico através da função ```figure``` e seu parâmetro ```figsize=(x, y))``` e o título através do ```set_title('Título')```.\n","Como comentado na aula, usualmente, armazenamos o nosso gráfico em uma variável ```ax``` e então, definimos as demais configurações (por exemplo, ```ax.set_title('Título')```.\n","E, finalmente, para visualizar o gráfico de barras, usamos o ```plt.show()```."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":412},"id":"IePUr98kdgED","executionInfo":{"status":"ok","timestamp":1620132297045,"user_tz":180,"elapsed":1371,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"bc70aa2e-298f-468c-cc99-f2d566ef584f"},"source":["import seaborn as sns\n","import matplotlib.pyplot as plt\n","sns.set()\n","plt.figure(figsize=(8, 6))\n","ax = sns.countplot(x = 'composto',  data=dados.query('composto in @cod_compostos'), order = dados['composto'].value_counts().index[0:5], palette = 'Blues')\n","ax.set_title('Top 5 compostos', fontsize = 15)\n","plt.show()"],"execution_count":38,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"bA_RUClHM6I8"},"source":["Até o momento analisamos os dados de tempo, dose, compostos e afins. Entretanto, não analisamos os dados de expressões gênicas (G's) e viabilidade celular (C's). Será que podemos criar um gráfico de barras para esses dados?\n","Vamos pensar que a nossa base de dados apresenta mais de 3.000 compostos. Mas quantos desses compostos aparecem na coluna ```g-0```? \n","Para responder essa questão, vamos usar a função ```unique()``` do Pandas que conta os valores únicos presentes na coluna em questão. Como resposta padrão, o retorno será uma lista com arrays (os nomes dos compostos) mas, nosso objetivo é saber o tamanho dessa lista e, por isso, usamos o ```len```, pois assim, ele contará o tamanho desta lista de arrays."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DkQ2wH9Gj-w7","executionInfo":{"status":"ok","timestamp":1620132466536,"user_tz":180,"elapsed":653,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"274e65d9-d089-4bd6-e6c0-47c03aa3faa2"},"source":["len(dados['g-0'].unique())"],"execution_count":39,"outputs":[{"output_type":"execute_result","data":{"text/plain":["14367"]},"metadata":{"tags":[]},"execution_count":39}]},{"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","executionInfo":{"status":"ok","timestamp":1620132551430,"user_tz":180,"elapsed":746,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"deef04f1-1af6-452f-fa31-523bac435f0f"},"source":["dados['g-0'].min()"],"execution_count":40,"outputs":[{"output_type":"execute_result","data":{"text/plain":["-5.513"]},"metadata":{"tags":[]},"execution_count":40}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qzH4Jl0OksuL","executionInfo":{"status":"ok","timestamp":1620132551694,"user_tz":180,"elapsed":576,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"d573c278-0f76-4ad6-a45f-1c04d91dbda0"},"source":["dados['g-0'].max()"],"execution_count":41,"outputs":[{"output_type":"execute_result","data":{"text/plain":["10.0"]},"metadata":{"tags":[]},"execution_count":41}]},{"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","executionInfo":{"status":"ok","timestamp":1620132745798,"user_tz":180,"elapsed":1183,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"b25f989f-9108-462f-bbcf-72771a058efa"},"source":["dados['g-0'].hist(bins = 100)"],"execution_count":42,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb708f250>"]},"metadata":{"tags":[]},"execution_count":42},{"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","executionInfo":{"status":"ok","timestamp":1620133301153,"user_tz":180,"elapsed":1295,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"9ec09c01-7e79-4651-980c-2f4a3cd1b06b"},"source":["dados['g-19'].hist(bins = 100)"],"execution_count":43,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb7078810>"]},"metadata":{"tags":[]},"execution_count":43},{"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","executionInfo":{"status":"ok","timestamp":1620133597259,"user_tz":180,"elapsed":3178,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"44e54152-11f8-466d-f43a-b0d3b01b1538"},"source":["dados.describe()"],"execution_count":44,"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":44}]},{"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","executionInfo":{"status":"ok","timestamp":1620133707134,"user_tz":180,"elapsed":624,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"c06bac44-8f48-4ba0-f96d-cf07ceaec807"},"source":["dados[['g-0', 'g-1']]"],"execution_count":45,"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":45}]},{"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","executionInfo":{"status":"ok","timestamp":1620133861247,"user_tz":180,"elapsed":3095,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"04893fd9-c08a-409b-8504-cce0249e88d5"},"source":["dados.loc[:,'g-0':'g-771'].describe()"],"execution_count":46,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>g-35</th>\n","      <th>g-36</th>\n","      <th>g-37</th>\n","      <th>g-38</th>\n","      <th>g-39</th>\n","      <th>...</th>\n","      <th>g-732</th>\n","      <th>g-733</th>\n","      <th>g-734</th>\n","      <th>g-735</th>\n","      <th>g-736</th>\n","      <th>g-737</th>\n","      <th>g-738</th>\n","      <th>g-739</th>\n","      <th>g-740</th>\n","      <th>g-741</th>\n","      <th>g-742</th>\n","      <th>g-743</th>\n","      <th>g-744</th>\n","      <th>g-745</th>\n","      <th>g-746</th>\n","      <th>g-747</th>\n","      <th>g-748</th>\n","      <th>g-749</th>\n","      <th>g-750</th>\n","      <th>g-751</th>\n","      <th>g-752</th>\n","      <th>g-753</th>\n","      <th>g-754</th>\n","      <th>g-755</th>\n","      <th>g-756</th>\n","      <th>g-757</th>\n","      <th>g-758</th>\n","      <th>g-759</th>\n","      <th>g-760</th>\n","      <th>g-761</th>\n","      <th>g-762</th>\n","      <th>g-763</th>\n","      <th>g-764</th>\n","      <th>g-765</th>\n","      <th>g-766</th>\n","      <th>g-767</th>\n","      <th>g-768</th>\n","      <th>g-769</th>\n","      <th>g-770</th>\n","      <th>g-771</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>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":46}]},{"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","executionInfo":{"status":"ok","timestamp":1620134013142,"user_tz":180,"elapsed":4134,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"7ffa2f71-3d0f-4854-e6c0-18801ac740d8"},"source":["dados.loc[:,'g-0':'g-771'].describe().T['mean'].hist(bins=30)"],"execution_count":47,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb6e6add0>"]},"metadata":{"tags":[]},"execution_count":47},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAXoAAAD7CAYAAABkO19ZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAaxElEQVR4nO3df1CT9+EH8HcSStAJxUTAoK7cuOqyuukJd+5287YTrahB1NrhsHa1s17nrmfXastsm6BWMKi9aivX9rZ1c7q5sZ1wRCetR2/OrlrtyRyLdivF1pYImEgFVMAnn+8ffmU4f+R5Qp6QfPp+3XnXJI/P85Y+ed/DJ598HoMQQoCIiKRlHOoARESkLxY9EZHkWPRERJJj0RMRSY5FT0QkORY9EZHkWPRERJJLGOoAFy50IxjUdyq/1ToCfn+XrseIlHjKCjCvnuIpK8C8ehqY1Wg0YOTIr2j6+0Ne9MGg0L3orx8nXsRTVoB59RRPWQHm1dNgsnLohohIcix6IiLJseiJiCTHoicikhyLnohIcix6IiLJseiJiCQ35PPoiSIhOWUYksyhT+fePiUKaYhiC4uepJBkTkDB0zUht6vdWhiFNESxhUM3RESSY9ETEUlOVdG/8847mD9/PgoLCzFv3jy89dZbAIDm5mYUFRVh1qxZKCoqwpkzZ/TMSkREYQg5Ri+EwDPPPIPdu3dj/PjxOH36NH74wx9ixowZcLlcKC4uRmFhIWpqauB0OrFz585o5CYiIpVUXdEbjUZ0dnYCADo7O5Geno4LFy7A6/XC4XAAABwOB7xeLwKBgH5piYhIs5BX9AaDAS+//DJWrlyJ4cOHo7u7G2+88QZ8Ph8yMjJgMpkAACaTCenp6fD5fLBYLLoHJyIidUIW/dWrV/H666+jsrISOTk5+OCDD/Dkk0+ioqIiIgGs1hER2U8oaWnJUTlOJMRTVoB59RRPWQHm1dNgsoYs+lOnTqGtrQ05OTkAgJycHAwbNgxmsxmtra1QFAUmkwmKoqCtrQ02m01TAL+/S/fF/9PSktHe3qnrMSIlnrICsZNXy5sgFvKqESs/W7WYVz8DsxqNBs0XyCHH6EePHo1z587h448/BgA0NTXB7/fjnnvugd1uh8fjAQB4PB7Y7XYO2xARxZiQV/RpaWkoLS3FqlWrYDAYAABlZWVITU1FaWkpSkpKUFlZiZSUFLjdbt0DExGRNqqWQJg3bx7mzZt30/PZ2dmoqqqKeCgiIoocfjOWiEhyLHoiIsmx6ImIJMeiJyKSHIueiEhyLHoiIsmx6ImIJMeiJyKSHIueiEhyLHoiIsmpWgKBKNKSU4YhyRz69OvpVWBONEUhEZG8WPQ0JJLMCSh4uibkdrVbC1VvR0S3xqEbIiLJseiJiCTHoicikhyLnohIciE/jP3ss8/w05/+tP9xZ2cnurq68P7776O5uRklJSXo6OhAamoq3G43srKy9MxLREQahSz6sWPHoqbmv7MeNm7cCEVRAAAulwvFxcUoLCxETU0NnE4ndu7cqV9aIiLSTNPQTW9vL2pra/HAAw/A7/fD6/XC4XAAABwOB7xeLwKBgC5BiYgoPJqKvr6+HhkZGbjvvvvg8/mQkZEBk+nal1lMJhPS09Ph8/l0CUpEROHR9IWpP//5z3jggQciGsBqHRHR/d1OWlpyVI4TCfGUFWBePcVTVoB59TSYrKqLvrW1FceOHUNFRQUAwGazobW1FYqiwGQyQVEUtLW1wWazaQrg93chGBTaUmuUlpaM9vZOXY8RKfGUFQg/71C+weLl5/tlOReGSjzlHZjVaDRovkBWPXSzd+9efO9738PIkSMBAFarFXa7HR6PBwDg8Xhgt9thsVg0BSAiIn1pKvr/HbYpLS3Frl27MGvWLOzatQvr1q2LeEAiIhoc1UM3dXV1Nz2XnZ2NqqqqiAYiIqLI4jdjiYgkx6InIpIci56ISHIseiIiybHoiYgkx6InIpIci56ISHK8OTh9qfT2KaqWX7jScxWdFy9HIRGR/lj09KWSeJcJBU/XhNyudmsh4mMVFKLQOHRDRCQ5XtET3QKHeEgmLHqiW+AQD8mEQzdERJJj0RMRSY5FT0QkORY9EZHkVH0Y29PTg7KyMrz33nswm82YPHkyNmzYgObmZpSUlKCjowOpqalwu93IysrSOTIREWmhqug3b94Ms9mMuro6GAwGnD9/HgDgcrlQXFyMwsJC1NTUwOl0YufOnboGJiIibUIO3XR3d6O6uhqrVq2CwWAAAIwaNQp+vx9erxcOhwMA4HA44PV6EQgE9E1MRESahLyiP3v2LFJTU/Hqq6/i6NGj+MpXvoJVq1YhKSkJGRkZMJlMAACTyYT09HT4fD5YLBbdgxMRkTohi15RFJw9exbf+MY38Oyzz+If//gHHn/8cWzbti0iAazWERHZTyhqvuUYK+IpKxB/eSNNz39/vP1smVc/g8kasuhtNhsSEhL6h2gmTZqEkSNHIikpCa2trVAUBSaTCYqioK2tDTabTVMAv78LwaAIL71KaWnJaG+Pj+8vxlNWIPy88fQGC0Wv/19flnNhqMRT3oFZjUaD5gvkkGP0FosFU6dOxbvvvgsAaG5uht/vR1ZWFux2OzweDwDA4/HAbrdz2IaIKMaomnWzbt06rF27Fm63GwkJCaioqEBKSgpKS0tRUlKCyspKpKSkwO12652XiIg0UlX048aNw29/+9ubns/OzkZVVVXEQxERUeTwm7FERJJj0RMRSY5FT0QkORY9EZHkWPRERJJj0RMRSY5FT0QkOd4cnGgQevsUVcs5XOm5is6Ll6OQiOhmLHqiQUi8y4SCp2tCble7tRDxsaoKyYhDN0REkmPRExFJjkVPRCQ5Fj0RkeRY9EREkmPRExFJjtMriaJA7Xx7AOjpVWBONAG48y0XOTef1FJV9NOnT0diYiLMZjMAYPXq1Zg2bRoaGhrgdDrR09ODMWPGYPPmzbBarboGJopHaufbA9fm3HNuPkWS6iv67du3Y/z48f2Pg8Eg1qxZg/LycuTm5qKyshJbtmxBeXm5LkGJiCg8YY/RNzY2wmw2Izc3FwCwePFiHDhwIGLBiIgoMlRf0a9evRpCCOTk5OCpp56Cz+dDZmZm/+sWiwXBYBAdHR1ITU3VJSwREWmnquh3794Nm82G3t5ebNy4EevXr8fMmTMjEsBqHRGR/YSi9oOwWBBPWYH4yyuTWPvZx1qeUOIp72Cyqip6m80GAEhMTERxcTF+8pOf4OGHH0ZLS0v/NoFAAEajUfPVvN/fhWBQaPo7WqWlJaO9PT4+toqnrED4eePpDRbLYulc+bKcu0NhYFaj0aD5AjnkGP2lS5fQ2XntAEII7N+/H3a7HRMnTsSVK1dw/PhxAMCePXuQn5+vNT8REeks5BW93+/HE088AUVREAwGkZ2dDZfLBaPRiIqKCrhcrhumVxIRUWwJWfTjxo1DdXX1LV+bMmUKamtrIx6KiIgih0sgEBFJjkVPRCQ5Fj0RkeRY9EREkmPRExFJjkVPRCQ5Fj0RkeRY9EREkmPRExFJjkVPRCQ5Fj0RkeRY9EREklN9hymiUJJThiHJzFOKKNbwXUkRk2ROQMHTNaq2rd1aqHMaIrqOQzdERJLjFT2FFGpIhrcFJIptmor+1VdfxSuvvILa2lqMHz8eDQ0NcDqdN9xhymq16pWVhojaIRkOxxDFJtVDN//617/Q0NCAMWPGAACCwSDWrFkDp9OJuro65ObmYsuWLboFJaIb9fYpSEtLDvknOWXYUEelIabqir63txfr16/H1q1b8fDDDwMAGhsbYTabkZubCwBYvHgx8vLyUF5erl9aIuqXeJdJ9W9anVHIQ7FLVdFv27YN8+bNw9ixY/uf8/l8yMzM7H9ssVgQDAbR0dGB1NRU1QGs1hEa4oYvnsaR4ykrxYdonVPxdu7GU97BZA1Z9CdOnEBjYyNWr14d9kHuxO/vQjAodNn3dWlpyWhvj49rmljMGk9vBrq1aJxTsXju3kk85R2Y1Wg0aL5ADln0x44dQ1NTE/Ly8gAA586dw49//GMsXboULS0t/dsFAgEYjUZNV/NERKS/kB/GrlixAocPH0Z9fT3q6+sxevRo/PKXv8Ty5ctx5coVHD9+HACwZ88e5Ofn6x6YiIi0CXsevdFoREVFBVwu1w3TK4mIKLZoLvr6+vr+/54yZQpqa2sjGoiIiCKLSyAQEUmORU9EJDkWPRGR5Fj0RESSY9ETEUmORU9EJDkWPRGR5Fj0RESSY9ETEUmORU9EJDkWPRGR5Fj0RESSY9ETEUmORU9EJDkWPRGR5Fj0RESSU3XjkZUrV+Kzzz6D0WjE8OHD8cILL8But6O5uRklJSXo6OhAamoq3G43srKydI5MRERaqCp6t9uN5ORkAMDBgwexdu1a7N27Fy6XC8XFxSgsLERNTQ2cTid27typa2AiItJG1dDN9ZIHgK6uLhgMBvj9fni9XjgcDgCAw+GA1+tFIBDQJykREYVF9T1jn3vuObz77rsQQuAXv/gFfD4fMjIyYDKZAAAmkwnp6enw+XywWCyqA1itI7SnDkNaWnLojWJEPGWl+BCtcyrezt14yjuYrKqLfuPGjQCA6upqVFRUYNWqVWEfdCC/vwvBoIjIvm4nLS0Z7e2duh4jUmIxazy9GejWonFOxeK5eyfxlHdgVqPRoPkCWfOsm/nz5+Po0aMYPXo0WltboSgKAEBRFLS1tcFms2ndJRER6Shk0Xd3d8Pn8/U/rq+vx9133w2r1Qq73Q6PxwMA8Hg8sNvtmoZtiIhIfyGHbi5fvoxVq1bh8uXLMBqNuPvuu/Haa6/BYDCgtLQUJSUlqKysREpKCtxudzQyExGRBiGLftSoUfjjH/94y9eys7NRVVUV8VBERBQ5/GYsEZHkWPRERJJj0RMRSY5FT0QkORY9EZHkWPRERJJj0RMRSU71Wjckn+SUYUgy8xSQXW+fomq9ois9V9F58XIUElG08V3+JZZkTkDB0zUht6vdWhiFNKSXxLtMqv8/x8cSX6QVh26IiCTHoicikhyLnohIcix6IiLJseiJiCTHoicikhyLnohIciHn0V+4cAHPPPMMPv30UyQmJuKee+7B+vXrYbFY0NDQAKfTiZ6eHowZMwabN2+G1WqNRm4iIlIp5BW9wWDA8uXLUVdXh9raWowbNw5btmxBMBjEmjVr4HQ6UVdXh9zcXGzZsiUamYmISIOQRZ+amoqpU6f2P548eTJaWlrQ2NgIs9mM3NxcAMDixYtx4MAB/ZISEVFYNC2BEAwG8fvf/x7Tp0+Hz+dDZmZm/2sWiwXBYBAdHR1ITU1VvU+rdYSWCGFTs9ZHrIinrCSXwZ578XbuxlPewWTVVPQbNmzA8OHD8dBDD+Htt98O+6AD+f1dCAZFRPZ1O2lpyWhvj49VPKKZNZ5OcoqOwZx78fQ+A+Ir78CsRqNB8wWy6qJ3u9345JNP8Nprr8FoNMJms6GlpaX/9UAgAKPRqOlqnoiI9KdqeuVLL72ExsZG7NixA4mJiQCAiRMn4sqVKzh+/DgAYM+ePcjPz9cvKRERhSXkFf1//vMfvP7668jKysLixYsBAGPHjsWOHTtQUVEBl8t1w/RKIiKKLSGL/t5778WHH354y9emTJmC2traiIciIqLI4TdjiYgkx6InIpIci56ISHIseiIiybHoiYgkx6InIpIci56ISHIseiIiybHoiYgkx6InIpIci56ISHIseiIiyWm68QgRyau3T1F1M5orPVfRefFyFBJRpLDoiQgAkHiXCQVP14TcrnZrIeLjvkx0HYduiIgkx6InIpJcyKJ3u92YPn06JkyYgH//+9/9zzc3N6OoqAizZs1CUVERzpw5o2dOIiIKU8iiz8vLw+7duzFmzJgbnne5XCguLkZdXR2Ki4vhdDp1C0lEROELWfS5ubmw2Ww3POf3++H1euFwOAAADocDXq8XgUBAn5RERBS2sGbd+Hw+ZGRkwGQyAQBMJhPS09Ph8/lgsVg07ctqHRFOBM3UTBuLpN4+BYl3mcLa9nZZ1e5Ty7GJwnG7czTa77PBiqe8g8k65NMr/f4uBINC12OkpSWjvT26E8LS0pJVTVUDrk1Xu57vTlnV7nPg/kJlJArHrc6voXifDUY85R2Y1Wg0aL5ADmvWjc1mQ2trKxRFAQAoioK2trabhniIiGjohVX0VqsVdrsdHo8HAODxeGC32zUP2xARkf5CDt28+OKLeOutt3D+/HksW7YMqamp2LdvH0pLS1FSUoLKykqkpKTA7XZHIy8REWkUsuiff/55PP/88zc9n52djaqqKl1CxbLklGFIMg/5RxtEQ+ZOa+IMfJ5r4sQONpZGSeYE1R+IEsmIa+LEHy6BQEQkOV7Rx4D//VV4sNMe1S43S0RfDiz6GKDlV+Gh2B8RxTcO3RARSY5FT0QkORY9EZHkWPRERJJj0RMRSY6zbohIF2qn+Wr5Bq3ab6bzW7k3YtETkS70+Aatlm+m81u5/8WhGyIiycXtFb2WX+GIiL7M4rboubgYEZE6HLohIpIci56ISHKDLvrm5mYUFRVh1qxZKCoqwpkzZyIQi4iIImXQY/QulwvFxcUoLCxETU0NnE4ndu7cGYlsEdHbpyDxLlPI+bycd0s0NGRaVjtW5/kPquj9fj+8Xi/efPNNAIDD4cCGDRsQCARU3yjcaDSEffz0kcNCbpN4lwk/fvGtkNv98vn70a0yi5rjatlOj33G+nZDeexY324ojz0U26l9jwLX3qdqj62mWwbTP7eSZE6IeN9cdz1rOJkNQgih+W/9v8bGRjz77LPYt29f/3Nz5szB5s2bcd9994W7WyIiiiB+GEtEJLlBFb3NZkNraysURQEAKIqCtrY22Gy2iIQjIqLBG1TRW61W2O12eDweAIDH44Hdblc9Pk9ERPob1Bg9ADQ1NaGkpAQXL15ESkoK3G43vva1r0UqHxERDdKgi56IiGIbP4wlIpIci56ISHIseiIiybHoiYgkJ13RX758GU8++SRmzpyJ/Px8vPPOO7fd9tSpU1iyZAnmzJmDOXPm4K9//WsUk16jJS8A9PT0YO7cuVi4cGGUEt5Ibd6DBw9i4cKFcDgcmDt3Ln71q19FLaOahfYURcG6deswY8YMzJw5E1VVVVHLN5CarDt27MDcuXNRUFCAhQsX4m9/+1v0g/4/LYsYfvzxx5g0aRLcbnf0Av4PtXn379+PgoICOBwOFBQU4Pz589ENCnVZ/X4/VqxYgYKCAsyePRulpaW4elXFzZWEZF555RXx3HPPCSGEaG5uFt/5zndEV1fXTdt1d3eL6dOnixMnTgghhOjr6xOBQCCqWYVQn/e68vJy8fOf/1wsWLAgWhFvoDZvQ0ODOHfunBBCiIsXL4oZM2aIY8eORSXj0qVLRXV1tRBCiOrqarF06dKbttm7d6949NFHhaIowu/3i2nTpomzZ89GJd9AarIeOnRIXLp0SQghxKlTp0ROTo64fPlyVHNepyavEEJcvXpVPPTQQ+Kpp54SmzZtimbEG6jJe/LkSTF79mzR1tYmhLh2vl65ciWqOYVQl/XFF1/s/3n29vaKRYsWiX379oXct3RX9H/5y19QVFQEAMjKysLEiRNx6NChm7bzeDzIycnB5MmTAQAJCQkYOXJkVLMC6vMCwPHjx3HmzBkUFg7dXbPU5p00aRIyMjIAAMnJycjOzsbnn3+ue77rC+05HA4A1xba83q9CAQCN2y3f/9+PPjggzAajbBYLJgxYwYOHDige75wsk6bNg3Dhl1byGvChAkQQqCjoyOqWbXkBYA33ngD3//+95GVlRXllP+lNu+vf/1rPProo0hLSwNw7Xw1m80xmdVgMKC7uxvBYBC9vb3o6+vrf5/diXRF39LSgjFjxvQ/ttlsOHfu3E3bffTRR0hISMBjjz2GwsJCrF27Fl988UU0owJQn/fSpUsoKyvDunXrohnvJmrzDtTU1ISGhgZ8+9vf1jsefD4fMjIyYDKZAAAmkwnp6enw+Xw3bZeZmdn/WM2/Y6iyDlRdXY2vfvWrGD16dLRi9lOb9/Tp0zh8+DAeeeSRqGccSG3epqYmnD17FkuWLMGCBQtQWVkJEeWvF6nNunLlSjQ3N+O73/1u/5+cnJyQ+4+7e8YuWLAALS0tt3zt73//u+r9BINBHDlyBHv27MGoUaNQXl6OTZs2oby8PFJRAUQub0VFBYqLi5GRkaHrzV0ilfe6trY2rFy5Ei6XS9WVB93e+++/j23btkX18w6t+vr68MILL6C8vLy/tGKdoij48MMP8eabb6K3txfLly9HZmYm5s+fP9TRbnLgwAFMmDABv/nNb9Dd3Y3HHnsMBw4cQH5+/h3/XtwV/d69e+/4emZmJj7//PP+9XZ8Ph+mTp1603Y2mw1Tp05Feno6AKCgoABr166N2bwffPABDh06hMrKSvT09OCLL75AQUEBamtrYzIvcO3X0WXLlmH58uWYPXt2RHPezsCF9kwm020X2rPZbGhpacG3vvUtADdf4cdSVgA4ceIE1qxZg8rKyiFbYkRN3vb2dnz66adYsWIFAODixYsQQqCrqwsbNmyIubzAtXM6Pz8fiYmJSExMRF5eHk6ePBnVolebddeuXSgrK4PRaERycjKmT5+Oo0ePhix66YZu8vPz8Yc//AEAcObMGfzzn//EtGnTbtpu9uzZOHnyJLq6ugAAhw4dwoQJE6KaFVCft7a2FvX19aivr8dLL72E8ePHR7zk1VCb98KFC1i2bBmWLFmCBx98MGr51C60l5+fj6qqKgSDQQQCARw8eBCzZs2KWk4tWU+ePImf/exn2L59+5De50FN3szMTBw9erT/XP3Rj36EH/zgB1EvebV5gWvj4YcPH4YQAn19fThy5Ai+/vWvx2TWsWPH9n8m1tvbi/feew/33ntv6ANE7jPj2NDd3S2eeOIJMWPGDHH//feLt99+u/+1l19+Wfzud7/rf7x3714xd+5c4XA4xOOPPy7a29tjOu91R44cGbJZN2rzbtq0SXzzm98U8+bN6//zpz/9KSoZP/roI7Fo0SJx//33i0WLFommpiYhhBDLly8XJ0+eFEJcmxXidDpFXl6eyMvLE3v27IlKtnCyLly4UEydOvWGn+Xp06djNu9A27dvH9JZN2ryKooiysrKRH5+vpgzZ44oKysTiqLEZNZPPvlEPPLII8LhcIjZs2eL0tJS0dfXF3LfXNSMiEhy0g3dEBHRjVj0RESSY9ETEUmORU9EJDkWPRGR5Fj0RESSY9ETEUmORU9EJLn/A7Almer5zTrAAAAAAElFTkSuQmCC\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","executionInfo":{"status":"ok","timestamp":1620134017745,"user_tz":180,"elapsed":3748,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"bc53a2b9-1bba-44c8-c39c-dad4a4047c40"},"source":["dados.loc[:,'g-0':'g-771'].describe().T['min'].hist(bins=30)"],"execution_count":48,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb7760890>"]},"metadata":{"tags":[]},"execution_count":48},{"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","executionInfo":{"status":"ok","timestamp":1620134034088,"user_tz":180,"elapsed":3922,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"fc15c5e6-d3cc-4ce9-b7e9-3aa5c0a01c77"},"source":["dados.loc[:,'g-0':'g-771'].describe().T['max'].hist(bins=30)"],"execution_count":49,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb6e533d0>"]},"metadata":{"tags":[]},"execution_count":49},{"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","executionInfo":{"status":"ok","timestamp":1620134569261,"user_tz":180,"elapsed":1354,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"f9d3e37e-7fd6-4769-cdd6-54a980a53c8b"},"source":["dados.loc[:,'c-0':'c-99'].describe().T['mean'].hist(bins=50)"],"execution_count":50,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb6c92fd0>"]},"metadata":{"tags":[]},"execution_count":50},{"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","executionInfo":{"status":"ok","timestamp":1620134992371,"user_tz":180,"elapsed":1426,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"12a6a5e5-f6ed-4287-bbcc-dc4acd83717c"},"source":["sns.boxplot(x='g-0' , data=dados)"],"execution_count":51,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb72e1e50>"]},"metadata":{"tags":[]},"execution_count":51},{"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","executionInfo":{"status":"ok","timestamp":1620135762530,"user_tz":180,"elapsed":679,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"a494e910-5f46-47ee-aa84-040e5eb37841"},"source":["plt.figure(figsize=(10,8))\n","sns.boxplot(y='g-0', x='tratamento' , data=dados)"],"execution_count":52,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb6bfb610>"]},"metadata":{"tags":[]},"execution_count":52},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x576 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"KbXSuyvbqdTE"},"source":["#Desafios"]},{"cell_type":"markdown","metadata":{"id":"X_Lg2XTu20ND"},"source":["###Desafio 01: Investigar por que a classe tratamento é tão desbalanceada?\n","\n","###DEsafio 02: Plotar as 5 últimas linhas da tabela\n","\n","###Desafio 03: Proporção das classes tratamento.\n","\n","###Desafio 04: Quantas tipos de drogas foram investigados.\n","\n","###Desafio 05: Procurar na documentação o método query(pandas). \n","\n","###Desafio 06: Renomear as colunas tirando o hífen. \n","\n","###Desafio 07: Deixar os gráficos bonitões. (Matplotlib.pyplot)\n","\n","###Desafio 08: Resumo do que você aprendeu com os dados\n","\n","\n","##Aula2\n","\n","###Desafio 01: Ordenar o gráfico countplot\n","\n","###Desafio 02: Melhorar a visualização alterando tamanho da fonte...\n","\n","###Desafio 03: Plotar os histogramas com seaborn\n","\n","###Desafio 04: Estudar sobre as estatíticas retornadas no .describe()\n","\n","###Desafio 05: Refletir sobre a manipulação do tamanho das visualizações. \n","\n","###Desafio 06: Fazer outras análises com o boxplot e até com o histograma. \n","\n","###Desafio 07: Resumo do que você aprendeu com os dados"]},{"cell_type":"markdown","metadata":{"id":"p3eSP6fWpXyv"},"source":["# Desafio 1:"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":412},"id":"cylkF_AApbBZ","executionInfo":{"status":"ok","timestamp":1620136310642,"user_tz":180,"elapsed":1056,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"dd5d7b4b-91ea-4b90-9bd5-68c5b9095a1c"},"source":["plt.figure(figsize=(8, 6))\n","ax = sns.countplot(x = 'composto',  data=dados.query('composto in @cod_compostos'), order = dados['composto'].value_counts().index[0:5], palette = 'Blues')\n","ax.set_title('Top 5 compostos', fontsize = 15)\n","plt.show()"],"execution_count":53,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"JHsoJ8NFprGS"},"source":["# Desafio 2:"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":417},"id":"XnETOn0_ps-e","executionInfo":{"status":"ok","timestamp":1620138980678,"user_tz":180,"elapsed":1357,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"4a7f639f-de82-4db3-ec02-e96b74f1868e"},"source":["plt.figure(figsize=(8, 6))\n","cod_compostos_dec = []\n","total = len(cod_compostos)\n","i = 0\n","while (total-i) > 0:\n","  i+=1\n","  cod_compostos_dec.append(cod_compostos[total-i])\n","ax = sns.countplot(x = 'composto',  data=dados.query('composto in @cod_compostos'), order = cod_compostos_dec, palette = 'Blues')\n","ax.set_title('Top 5 compostos', fontsize = 15)\n","plt.ylabel('Frequência', fontsize = 18)\n","plt.xlabel('Compostos', fontsize = 18)\n","plt.show()"],"execution_count":83,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"WpkCw-gipxYK"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"f3RsMLoIz0rw"},"source":["# Desafio 3:"]},{"cell_type":"markdown","metadata":{"id":"wHqm5rRCz6eg"},"source":["Temos 4 histogramas feitos na aula e eles foram plotados pelo pandas. Vamos repedir esses histogramas porem plotando pelo seaborn usado só o primeiro como exemplos.\n","Pagina de referência: https://seaborn.pydata.org/generated/seaborn.histplot.html\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":309},"id":"53IdoI_qz2LH","executionInfo":{"status":"ok","timestamp":1620140531889,"user_tz":180,"elapsed":6205,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"58f777f8-1970-4bed-8963-8b1bcdd8f034"},"source":["dados.loc[:,'g-0':'g-771'].describe().T['mean'].hist(bins=30)\n","\n","bx = sns.histplot( data = dados.loc[:,'g-0':'g-771'].describe().T['mean'], bins = 100, kde = True, element='step', fill=False )\n","bx.set_title('Histograma das médias dos genes G', fontsize = 15)\n","plt.ylabel('Frequência', fontsize = 18)\n","plt.xlabel('Média ', fontsize = 18)\n","plt.show()"],"execution_count":92,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"XHTPoNUl1-8B"},"source":["# Desafio 4:"]},{"cell_type":"markdown","metadata":{"id":"bMAOHqII2Mrw"},"source":["Estudo feito em: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.describe.html"]},{"cell_type":"markdown","metadata":{"id":"A7EI4qkO2XaK"},"source":["Esas função vai retornar o valore da frequencia, media, desvio padrão, minimo, primeiro quartil, mediana, terceiro quartil e maximo."]},{"cell_type":"markdown","metadata":{"id":"b4pBJs3t2-nl"},"source":["# Desafio 6:\n"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":390},"id":"NYpyroN33HMg","executionInfo":{"status":"ok","timestamp":1620139951744,"user_tz":180,"elapsed":723,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"8e1f7857-3d93-41a4-866d-0cb9a2159097"},"source":["dados.head(10)"],"execution_count":89,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>id</th>\n","      <th>tratamento</th>\n","      <th>tempo</th>\n","      <th>dose</th>\n","      <th>composto</th>\n","      <th>g-0</th>\n","      <th>g-1</th>\n","      <th>g-2</th>\n","      <th>g-3</th>\n","      <th>g-4</th>\n","      <th>g-5</th>\n","      <th>g-6</th>\n","      <th>g-7</th>\n","      <th>g-8</th>\n","      <th>g-9</th>\n","      <th>g-10</th>\n","      <th>g-11</th>\n","      <th>g-12</th>\n","      <th>g-13</th>\n","      <th>g-14</th>\n","      <th>g-15</th>\n","      <th>g-16</th>\n","      <th>g-17</th>\n","      <th>g-18</th>\n","      <th>g-19</th>\n","      <th>g-20</th>\n","      <th>g-21</th>\n","      <th>g-22</th>\n","      <th>g-23</th>\n","      <th>g-24</th>\n","      <th>g-25</th>\n","      <th>g-26</th>\n","      <th>g-27</th>\n","      <th>g-28</th>\n","      <th>g-29</th>\n","      <th>g-30</th>\n","      <th>g-31</th>\n","      <th>g-32</th>\n","      <th>g-33</th>\n","      <th>g-34</th>\n","      <th>...</th>\n","      <th>c-60</th>\n","      <th>c-61</th>\n","      <th>c-62</th>\n","      <th>c-63</th>\n","      <th>c-64</th>\n","      <th>c-65</th>\n","      <th>c-66</th>\n","      <th>c-67</th>\n","      <th>c-68</th>\n","      <th>c-69</th>\n","      <th>c-70</th>\n","      <th>c-71</th>\n","      <th>c-72</th>\n","      <th>c-73</th>\n","      <th>c-74</th>\n","      <th>c-75</th>\n","      <th>c-76</th>\n","      <th>c-77</th>\n","      <th>c-78</th>\n","      <th>c-79</th>\n","      <th>c-80</th>\n","      <th>c-81</th>\n","      <th>c-82</th>\n","      <th>c-83</th>\n","      <th>c-84</th>\n","      <th>c-85</th>\n","      <th>c-86</th>\n","      <th>c-87</th>\n","      <th>c-88</th>\n","      <th>c-89</th>\n","      <th>c-90</th>\n","      <th>c-91</th>\n","      <th>c-92</th>\n","      <th>c-93</th>\n","      <th>c-94</th>\n","      <th>c-95</th>\n","      <th>c-96</th>\n","      <th>c-97</th>\n","      <th>c-98</th>\n","      <th>c-99</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>id_000644bb2</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>b68db1d53</td>\n","      <td>1.0620</td>\n","      <td>0.5577</td>\n","      <td>-0.2479</td>\n","      <td>-0.6208</td>\n","      <td>-0.1944</td>\n","      <td>-1.0120</td>\n","      <td>-1.0220</td>\n","      <td>-0.0326</td>\n","      <td>0.5548</td>\n","      <td>-0.0921</td>\n","      <td>1.1830</td>\n","      <td>0.1530</td>\n","      <td>0.5574</td>\n","      <td>-0.4015</td>\n","      <td>0.1789</td>\n","      <td>-0.6528</td>\n","      <td>-0.7969</td>\n","      <td>0.6342</td>\n","      <td>0.1778</td>\n","      <td>-0.3694</td>\n","      <td>-0.5688</td>\n","      <td>-1.1360</td>\n","      <td>-1.1880</td>\n","      <td>0.6940</td>\n","      <td>0.4393</td>\n","      <td>0.2664</td>\n","      <td>0.1907</td>\n","      <td>0.1628</td>\n","      <td>-0.2853</td>\n","      <td>0.5819</td>\n","      <td>0.2934</td>\n","      <td>-0.5584</td>\n","      <td>-0.0916</td>\n","      <td>-0.3010</td>\n","      <td>-0.1537</td>\n","      <td>...</td>\n","      <td>0.4805</td>\n","      <td>0.4965</td>\n","      <td>0.3680</td>\n","      <td>0.8427</td>\n","      <td>0.1042</td>\n","      <td>0.1403</td>\n","      <td>0.1758</td>\n","      <td>1.2570</td>\n","      <td>-0.5979</td>\n","      <td>1.2250</td>\n","      <td>-0.0553</td>\n","      <td>0.7351</td>\n","      <td>0.5810</td>\n","      <td>0.9590</td>\n","      <td>0.2427</td>\n","      <td>0.0495</td>\n","      <td>0.4141</td>\n","      <td>0.8432</td>\n","      <td>0.6162</td>\n","      <td>-0.7318</td>\n","      <td>1.2120</td>\n","      <td>0.6362</td>\n","      <td>-0.4427</td>\n","      <td>0.1288</td>\n","      <td>1.4840</td>\n","      <td>0.1799</td>\n","      <td>0.5367</td>\n","      <td>-0.1111</td>\n","      <td>-1.0120</td>\n","      <td>0.6685</td>\n","      <td>0.2862</td>\n","      <td>0.2584</td>\n","      <td>0.8076</td>\n","      <td>0.5523</td>\n","      <td>-0.1912</td>\n","      <td>0.6584</td>\n","      <td>-0.3981</td>\n","      <td>0.2139</td>\n","      <td>0.3801</td>\n","      <td>0.4176</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>id_000779bfc</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D1</td>\n","      <td>df89a8e5a</td>\n","      <td>0.0743</td>\n","      <td>0.4087</td>\n","      <td>0.2991</td>\n","      <td>0.0604</td>\n","      <td>1.0190</td>\n","      <td>0.5207</td>\n","      <td>0.2341</td>\n","      <td>0.3372</td>\n","      <td>-0.4047</td>\n","      <td>0.8507</td>\n","      <td>-1.1520</td>\n","      <td>-0.4201</td>\n","      <td>-0.0958</td>\n","      <td>0.4590</td>\n","      <td>0.0803</td>\n","      <td>0.2250</td>\n","      <td>0.5293</td>\n","      <td>0.2839</td>\n","      <td>-0.3494</td>\n","      <td>0.2883</td>\n","      <td>0.9449</td>\n","      <td>-0.1646</td>\n","      <td>-0.2657</td>\n","      <td>-0.3372</td>\n","      <td>0.3135</td>\n","      <td>-0.4316</td>\n","      <td>0.4773</td>\n","      <td>0.2075</td>\n","      <td>-0.4216</td>\n","      <td>-0.1161</td>\n","      <td>-0.0499</td>\n","      <td>-0.2627</td>\n","      <td>0.9959</td>\n","      <td>-0.2483</td>\n","      <td>0.2655</td>\n","      <td>...</td>\n","      <td>0.4083</td>\n","      <td>0.0319</td>\n","      <td>0.3905</td>\n","      <td>0.7099</td>\n","      <td>0.2912</td>\n","      <td>0.4151</td>\n","      <td>-0.2840</td>\n","      <td>-0.3104</td>\n","      <td>-0.6373</td>\n","      <td>0.2887</td>\n","      <td>-0.0765</td>\n","      <td>0.2539</td>\n","      <td>0.4443</td>\n","      <td>0.5932</td>\n","      <td>0.2031</td>\n","      <td>0.7639</td>\n","      <td>0.5499</td>\n","      <td>-0.3322</td>\n","      <td>-0.0977</td>\n","      <td>0.4329</td>\n","      <td>-0.2782</td>\n","      <td>0.7827</td>\n","      <td>0.5934</td>\n","      <td>0.3402</td>\n","      <td>0.1499</td>\n","      <td>0.4420</td>\n","      <td>0.9366</td>\n","      <td>0.8193</td>\n","      <td>-0.4236</td>\n","      <td>0.3192</td>\n","      <td>-0.4265</td>\n","      <td>0.7543</td>\n","      <td>0.4708</td>\n","      <td>0.0230</td>\n","      <td>0.2957</td>\n","      <td>0.4899</td>\n","      <td>0.1522</td>\n","      <td>0.1241</td>\n","      <td>0.6077</td>\n","      <td>0.7371</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>id_000a6266a</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>18bb41b2c</td>\n","      <td>0.6280</td>\n","      <td>0.5817</td>\n","      <td>1.5540</td>\n","      <td>-0.0764</td>\n","      <td>-0.0323</td>\n","      <td>1.2390</td>\n","      <td>0.1715</td>\n","      <td>0.2155</td>\n","      <td>0.0065</td>\n","      <td>1.2300</td>\n","      <td>-0.4797</td>\n","      <td>-0.5631</td>\n","      <td>-0.0366</td>\n","      <td>-1.8300</td>\n","      <td>0.6057</td>\n","      <td>-0.3278</td>\n","      <td>0.6042</td>\n","      <td>-0.3075</td>\n","      <td>-0.1147</td>\n","      <td>-0.0570</td>\n","      <td>-0.0799</td>\n","      <td>-0.8181</td>\n","      <td>-1.5320</td>\n","      <td>0.2307</td>\n","      <td>0.4901</td>\n","      <td>0.4780</td>\n","      <td>-1.3970</td>\n","      <td>4.6240</td>\n","      <td>-0.0437</td>\n","      <td>1.2870</td>\n","      <td>-1.8530</td>\n","      <td>0.6069</td>\n","      <td>0.4290</td>\n","      <td>0.1783</td>\n","      <td>0.0018</td>\n","      <td>...</td>\n","      <td>-0.5477</td>\n","      <td>-0.7576</td>\n","      <td>-0.0444</td>\n","      <td>0.1894</td>\n","      <td>-0.0014</td>\n","      <td>-2.3640</td>\n","      <td>-0.4682</td>\n","      <td>0.1210</td>\n","      <td>-0.5177</td>\n","      <td>-0.0604</td>\n","      <td>0.1682</td>\n","      <td>-0.4436</td>\n","      <td>0.4963</td>\n","      <td>0.1363</td>\n","      <td>0.3335</td>\n","      <td>0.9760</td>\n","      <td>-0.0427</td>\n","      <td>-0.1235</td>\n","      <td>0.0959</td>\n","      <td>0.0690</td>\n","      <td>-0.9416</td>\n","      <td>-0.7548</td>\n","      <td>-0.1109</td>\n","      <td>-0.6272</td>\n","      <td>0.3019</td>\n","      <td>0.1172</td>\n","      <td>0.1093</td>\n","      <td>-0.3113</td>\n","      <td>0.3019</td>\n","      <td>-0.0873</td>\n","      <td>-0.7250</td>\n","      <td>-0.6297</td>\n","      <td>0.6103</td>\n","      <td>0.0223</td>\n","      <td>-1.3240</td>\n","      <td>-0.3174</td>\n","      <td>-0.6417</td>\n","      <td>-0.2187</td>\n","      <td>-1.4080</td>\n","      <td>0.6931</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>id_0015fd391</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8c7f86626</td>\n","      <td>-0.5138</td>\n","      <td>-0.2491</td>\n","      <td>-0.2656</td>\n","      <td>0.5288</td>\n","      <td>4.0620</td>\n","      <td>-0.8095</td>\n","      <td>-1.9590</td>\n","      <td>0.1792</td>\n","      <td>-0.1321</td>\n","      <td>-1.0600</td>\n","      <td>-0.8269</td>\n","      <td>-0.3584</td>\n","      <td>-0.8511</td>\n","      <td>-0.5844</td>\n","      <td>-2.5690</td>\n","      <td>0.8183</td>\n","      <td>-0.0532</td>\n","      <td>-0.8554</td>\n","      <td>0.1160</td>\n","      <td>-2.3520</td>\n","      <td>2.1200</td>\n","      <td>-1.1580</td>\n","      <td>-0.7191</td>\n","      <td>-0.8004</td>\n","      <td>-1.4670</td>\n","      <td>-0.0107</td>\n","      <td>-0.8995</td>\n","      <td>0.2406</td>\n","      <td>-0.2479</td>\n","      <td>-1.0890</td>\n","      <td>-0.7575</td>\n","      <td>0.0881</td>\n","      <td>-2.7370</td>\n","      <td>0.8745</td>\n","      <td>0.5787</td>\n","      <td>...</td>\n","      <td>-2.1220</td>\n","      <td>-0.3752</td>\n","      <td>-2.3820</td>\n","      <td>-3.7350</td>\n","      <td>-2.9740</td>\n","      <td>-1.4930</td>\n","      <td>-1.6600</td>\n","      <td>-3.1660</td>\n","      <td>0.2816</td>\n","      <td>-0.2990</td>\n","      <td>-1.1870</td>\n","      <td>-0.5044</td>\n","      <td>-1.7750</td>\n","      <td>-1.6120</td>\n","      <td>-0.9215</td>\n","      <td>-1.0810</td>\n","      <td>-3.0520</td>\n","      <td>-3.4470</td>\n","      <td>-2.7740</td>\n","      <td>-1.8460</td>\n","      <td>-0.5568</td>\n","      <td>-3.3960</td>\n","      <td>-2.9510</td>\n","      <td>-1.1550</td>\n","      <td>-3.2620</td>\n","      <td>-1.5390</td>\n","      <td>-2.4600</td>\n","      <td>-0.9417</td>\n","      <td>-1.5550</td>\n","      <td>0.2431</td>\n","      <td>-2.0990</td>\n","      <td>-0.6441</td>\n","      <td>-5.6300</td>\n","      <td>-1.3780</td>\n","      <td>-0.8632</td>\n","      <td>-1.2880</td>\n","      <td>-1.6210</td>\n","      <td>-0.8784</td>\n","      <td>-0.3876</td>\n","      <td>-0.8154</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>id_001626bd3</td>\n","      <td>com_droga</td>\n","      <td>72</td>\n","      <td>D2</td>\n","      <td>7cbed3131</td>\n","      <td>-0.3254</td>\n","      <td>-0.4009</td>\n","      <td>0.9700</td>\n","      <td>0.6919</td>\n","      <td>1.4180</td>\n","      <td>-0.8244</td>\n","      <td>-0.2800</td>\n","      <td>-0.1498</td>\n","      <td>-0.8789</td>\n","      <td>0.8630</td>\n","      <td>-0.2219</td>\n","      <td>-0.5121</td>\n","      <td>-0.9577</td>\n","      <td>1.1750</td>\n","      <td>0.2042</td>\n","      <td>0.1970</td>\n","      <td>0.1244</td>\n","      <td>-1.7090</td>\n","      <td>-0.3543</td>\n","      <td>-0.5160</td>\n","      <td>-0.3330</td>\n","      <td>-0.2685</td>\n","      <td>0.7649</td>\n","      <td>0.2057</td>\n","      <td>1.3720</td>\n","      <td>0.6835</td>\n","      <td>0.8056</td>\n","      <td>-0.3754</td>\n","      <td>-1.2090</td>\n","      <td>0.2965</td>\n","      <td>-0.0712</td>\n","      <td>0.6389</td>\n","      <td>0.6674</td>\n","      <td>-0.0783</td>\n","      <td>1.1740</td>\n","      <td>...</td>\n","      <td>-0.2274</td>\n","      <td>0.3215</td>\n","      <td>0.1535</td>\n","      <td>-0.4640</td>\n","      <td>-0.5943</td>\n","      <td>0.3973</td>\n","      <td>0.1500</td>\n","      <td>0.5178</td>\n","      <td>0.5159</td>\n","      <td>0.6091</td>\n","      <td>0.1813</td>\n","      <td>-0.4249</td>\n","      <td>0.7832</td>\n","      <td>0.6529</td>\n","      <td>0.5648</td>\n","      <td>0.4817</td>\n","      <td>0.0587</td>\n","      <td>0.5303</td>\n","      <td>0.6376</td>\n","      <td>-0.3966</td>\n","      <td>-1.4950</td>\n","      <td>-0.9625</td>\n","      <td>-0.0541</td>\n","      <td>0.6273</td>\n","      <td>0.4563</td>\n","      <td>0.0698</td>\n","      <td>0.8134</td>\n","      <td>0.1924</td>\n","      <td>0.6054</td>\n","      <td>-0.1824</td>\n","      <td>0.0042</td>\n","      <td>0.0048</td>\n","      <td>0.6670</td>\n","      <td>1.0690</td>\n","      <td>0.5523</td>\n","      <td>-0.3031</td>\n","      <td>0.1094</td>\n","      <td>0.2885</td>\n","      <td>-0.3786</td>\n","      <td>0.7125</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>id_001762a82</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D1</td>\n","      <td>e06749542</td>\n","      <td>-0.6111</td>\n","      <td>0.2941</td>\n","      <td>-0.9901</td>\n","      <td>0.2277</td>\n","      <td>1.2810</td>\n","      <td>0.5203</td>\n","      <td>0.0543</td>\n","      <td>-0.2225</td>\n","      <td>-0.1586</td>\n","      <td>0.4289</td>\n","      <td>0.0361</td>\n","      <td>0.3543</td>\n","      <td>0.8310</td>\n","      <td>-0.9129</td>\n","      <td>0.7677</td>\n","      <td>-0.2512</td>\n","      <td>0.7087</td>\n","      <td>0.0481</td>\n","      <td>-0.4486</td>\n","      <td>1.2570</td>\n","      <td>1.2550</td>\n","      <td>0.3359</td>\n","      <td>-0.5103</td>\n","      <td>-0.2993</td>\n","      <td>-1.1950</td>\n","      <td>-0.3208</td>\n","      <td>-0.1187</td>\n","      <td>1.0030</td>\n","      <td>0.9133</td>\n","      <td>0.0376</td>\n","      <td>0.3015</td>\n","      <td>-0.9578</td>\n","      <td>0.5354</td>\n","      <td>1.1360</td>\n","      <td>1.1310</td>\n","      <td>...</td>\n","      <td>0.6701</td>\n","      <td>2.0780</td>\n","      <td>1.3350</td>\n","      <td>0.9889</td>\n","      <td>0.5017</td>\n","      <td>2.0020</td>\n","      <td>0.8918</td>\n","      <td>0.4290</td>\n","      <td>0.0716</td>\n","      <td>0.8465</td>\n","      <td>0.6596</td>\n","      <td>1.3710</td>\n","      <td>1.0580</td>\n","      <td>1.7570</td>\n","      <td>1.0030</td>\n","      <td>0.2152</td>\n","      <td>1.6920</td>\n","      <td>-0.2930</td>\n","      <td>1.4590</td>\n","      <td>1.0950</td>\n","      <td>0.5854</td>\n","      <td>1.7270</td>\n","      <td>0.5580</td>\n","      <td>1.3090</td>\n","      <td>1.0100</td>\n","      <td>0.6980</td>\n","      <td>0.5455</td>\n","      <td>1.0170</td>\n","      <td>1.2910</td>\n","      <td>1.5430</td>\n","      <td>1.8390</td>\n","      <td>1.1570</td>\n","      <td>-1.0120</td>\n","      <td>1.9010</td>\n","      <td>1.4270</td>\n","      <td>0.4519</td>\n","      <td>1.2120</td>\n","      <td>0.3765</td>\n","      <td>0.7848</td>\n","      <td>1.3990</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>id_001bd861f</td>\n","      <td>com_droga</td>\n","      <td>24</td>\n","      <td>D2</td>\n","      <td>746ca1f5a</td>\n","      <td>2.0440</td>\n","      <td>1.7000</td>\n","      <td>-1.5390</td>\n","      <td>5.9440</td>\n","      <td>-2.1670</td>\n","      <td>-4.0360</td>\n","      <td>3.6950</td>\n","      <td>1.4530</td>\n","      <td>0.9724</td>\n","      <td>-2.4380</td>\n","      <td>5.1340</td>\n","      <td>-4.6600</td>\n","      <td>5.7960</td>\n","      <td>4.9700</td>\n","      <td>1.5540</td>\n","      <td>2.4790</td>\n","      <td>-3.8010</td>\n","      <td>-1.0230</td>\n","      <td>5.3110</td>\n","      <td>-0.5660</td>\n","      <td>-4.4450</td>\n","      <td>1.2210</td>\n","      <td>1.3750</td>\n","      <td>0.3932</td>\n","      <td>0.3392</td>\n","      <td>4.3510</td>\n","      <td>5.7540</td>\n","      <td>-1.6590</td>\n","      <td>5.3000</td>\n","      <td>5.6050</td>\n","      <td>5.5320</td>\n","      <td>3.7860</td>\n","      <td>0.9197</td>\n","      <td>1.9310</td>\n","      <td>2.4870</td>\n","      <td>...</td>\n","      <td>-0.8904</td>\n","      <td>2.0590</td>\n","      <td>0.5052</td>\n","      <td>0.6890</td>\n","      <td>0.5340</td>\n","      <td>0.5135</td>\n","      <td>0.6507</td>\n","      <td>0.9838</td>\n","      <td>0.4532</td>\n","      <td>-0.3212</td>\n","      <td>0.2662</td>\n","      <td>0.6864</td>\n","      <td>1.6300</td>\n","      <td>1.3810</td>\n","      <td>0.0061</td>\n","      <td>0.2908</td>\n","      <td>0.2598</td>\n","      <td>0.1266</td>\n","      <td>-0.3526</td>\n","      <td>1.1750</td>\n","      <td>-1.1030</td>\n","      <td>1.3650</td>\n","      <td>1.0610</td>\n","      <td>0.4034</td>\n","      <td>1.0880</td>\n","      <td>-0.4230</td>\n","      <td>0.4013</td>\n","      <td>0.1726</td>\n","      <td>0.7464</td>\n","      <td>0.9418</td>\n","      <td>0.1855</td>\n","      <td>1.1720</td>\n","      <td>0.8325</td>\n","      <td>0.6486</td>\n","      <td>0.8090</td>\n","      <td>1.5880</td>\n","      <td>2.4670</td>\n","      <td>0.0357</td>\n","      <td>0.1351</td>\n","      <td>-0.3179</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>id_0020d0484</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>8b87a7a83</td>\n","      <td>0.2711</td>\n","      <td>0.5133</td>\n","      <td>-0.1327</td>\n","      <td>2.5950</td>\n","      <td>0.6980</td>\n","      <td>0.5846</td>\n","      <td>-0.2633</td>\n","      <td>-2.1490</td>\n","      <td>0.4881</td>\n","      <td>1.4750</td>\n","      <td>-0.0488</td>\n","      <td>-0.0561</td>\n","      <td>0.1641</td>\n","      <td>0.1749</td>\n","      <td>-0.3464</td>\n","      <td>-0.1811</td>\n","      <td>0.5685</td>\n","      <td>1.2970</td>\n","      <td>1.0510</td>\n","      <td>-0.9585</td>\n","      <td>0.7911</td>\n","      <td>-0.2991</td>\n","      <td>2.7420</td>\n","      <td>-0.5979</td>\n","      <td>-1.0240</td>\n","      <td>0.7268</td>\n","      <td>0.1590</td>\n","      <td>-1.9730</td>\n","      <td>1.1340</td>\n","      <td>-2.5720</td>\n","      <td>0.2068</td>\n","      <td>0.9992</td>\n","      <td>-0.1958</td>\n","      <td>0.2262</td>\n","      <td>1.0140</td>\n","      <td>...</td>\n","      <td>-0.2623</td>\n","      <td>-0.5500</td>\n","      <td>-0.0530</td>\n","      <td>0.2077</td>\n","      <td>-0.0825</td>\n","      <td>0.2156</td>\n","      <td>0.8142</td>\n","      <td>1.0990</td>\n","      <td>1.0860</td>\n","      <td>0.4011</td>\n","      <td>-0.1342</td>\n","      <td>0.4653</td>\n","      <td>-0.1104</td>\n","      <td>0.3935</td>\n","      <td>1.2370</td>\n","      <td>-0.5072</td>\n","      <td>0.0351</td>\n","      <td>0.5084</td>\n","      <td>-0.1248</td>\n","      <td>0.4351</td>\n","      <td>0.1389</td>\n","      <td>0.6726</td>\n","      <td>0.6070</td>\n","      <td>0.3431</td>\n","      <td>-0.4116</td>\n","      <td>0.1194</td>\n","      <td>0.3420</td>\n","      <td>0.1331</td>\n","      <td>0.8541</td>\n","      <td>0.6282</td>\n","      <td>0.3230</td>\n","      <td>-0.4140</td>\n","      <td>0.2532</td>\n","      <td>0.0513</td>\n","      <td>0.8600</td>\n","      <td>1.4250</td>\n","      <td>0.6633</td>\n","      <td>0.4562</td>\n","      <td>-0.9622</td>\n","      <td>0.0260</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>id_00224bf20</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D1</td>\n","      <td>952b76dfc</td>\n","      <td>-0.3014</td>\n","      <td>0.5545</td>\n","      <td>-0.2576</td>\n","      <td>-0.1390</td>\n","      <td>-0.6487</td>\n","      <td>-0.6057</td>\n","      <td>-0.7549</td>\n","      <td>0.0896</td>\n","      <td>-0.0946</td>\n","      <td>1.3950</td>\n","      <td>0.5803</td>\n","      <td>0.0350</td>\n","      <td>0.3887</td>\n","      <td>0.8024</td>\n","      <td>-1.2810</td>\n","      <td>0.4403</td>\n","      <td>-0.5125</td>\n","      <td>0.4421</td>\n","      <td>0.0573</td>\n","      <td>-0.3632</td>\n","      <td>-0.7767</td>\n","      <td>0.4234</td>\n","      <td>-0.4403</td>\n","      <td>0.0000</td>\n","      <td>-0.7262</td>\n","      <td>-0.3586</td>\n","      <td>0.6236</td>\n","      <td>0.7060</td>\n","      <td>-0.3461</td>\n","      <td>-0.8389</td>\n","      <td>0.4151</td>\n","      <td>-0.6344</td>\n","      <td>-0.3171</td>\n","      <td>-0.3250</td>\n","      <td>-0.9373</td>\n","      <td>...</td>\n","      <td>-0.4458</td>\n","      <td>-0.0157</td>\n","      <td>-0.7541</td>\n","      <td>-0.0729</td>\n","      <td>-0.2542</td>\n","      <td>-0.4082</td>\n","      <td>0.5141</td>\n","      <td>-0.2704</td>\n","      <td>-1.1490</td>\n","      <td>-0.8242</td>\n","      <td>-0.6872</td>\n","      <td>-1.0260</td>\n","      <td>-0.8389</td>\n","      <td>-0.3815</td>\n","      <td>0.2002</td>\n","      <td>-0.7580</td>\n","      <td>0.0525</td>\n","      <td>-0.8299</td>\n","      <td>0.1164</td>\n","      <td>-0.0231</td>\n","      <td>0.2644</td>\n","      <td>0.0663</td>\n","      <td>-0.3794</td>\n","      <td>-0.3130</td>\n","      <td>-0.3167</td>\n","      <td>-0.0090</td>\n","      <td>-0.5243</td>\n","      <td>-0.7220</td>\n","      <td>-0.7501</td>\n","      <td>0.3808</td>\n","      <td>-1.6470</td>\n","      <td>0.2863</td>\n","      <td>1.1070</td>\n","      <td>-0.7735</td>\n","      <td>-1.0280</td>\n","      <td>-1.3070</td>\n","      <td>-0.1167</td>\n","      <td>-0.1241</td>\n","      <td>-0.6420</td>\n","      <td>0.5543</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>id_0023f063e</td>\n","      <td>com_droga</td>\n","      <td>48</td>\n","      <td>D2</td>\n","      <td>de7583071</td>\n","      <td>-0.0630</td>\n","      <td>0.2564</td>\n","      <td>-0.5279</td>\n","      <td>-0.2541</td>\n","      <td>-0.0182</td>\n","      <td>-1.5370</td>\n","      <td>-0.2180</td>\n","      <td>-0.0430</td>\n","      <td>-0.0116</td>\n","      <td>0.6565</td>\n","      <td>-0.1618</td>\n","      <td>-0.6742</td>\n","      <td>0.7260</td>\n","      <td>-0.8124</td>\n","      <td>0.3477</td>\n","      <td>0.2425</td>\n","      <td>1.2030</td>\n","      <td>-0.4435</td>\n","      <td>0.8795</td>\n","      <td>-0.2243</td>\n","      <td>-0.1423</td>\n","      <td>0.3758</td>\n","      <td>-0.6869</td>\n","      <td>0.2382</td>\n","      <td>-0.8178</td>\n","      <td>-0.7586</td>\n","      <td>1.2330</td>\n","      <td>1.0770</td>\n","      <td>0.3447</td>\n","      <td>-0.3917</td>\n","      <td>0.3276</td>\n","      <td>2.2610</td>\n","      <td>-0.1933</td>\n","      <td>0.2296</td>\n","      <td>-0.1599</td>\n","      <td>...</td>\n","      <td>-0.5233</td>\n","      <td>-0.0834</td>\n","      <td>-0.8118</td>\n","      <td>-0.4018</td>\n","      <td>-1.2540</td>\n","      <td>-0.9295</td>\n","      <td>-0.5881</td>\n","      <td>-0.8408</td>\n","      <td>-0.1703</td>\n","      <td>-0.0097</td>\n","      <td>0.1205</td>\n","      <td>-0.5683</td>\n","      <td>-0.5235</td>\n","      <td>-0.8461</td>\n","      <td>-0.8039</td>\n","      <td>-1.1390</td>\n","      <td>-0.3498</td>\n","      <td>-0.2183</td>\n","      <td>-0.3053</td>\n","      <td>-0.6116</td>\n","      <td>-0.1504</td>\n","      <td>-0.5320</td>\n","      <td>-1.1000</td>\n","      <td>-0.2852</td>\n","      <td>-0.5361</td>\n","      <td>-0.3377</td>\n","      <td>-0.2916</td>\n","      <td>-1.4360</td>\n","      <td>0.3119</td>\n","      <td>-1.0490</td>\n","      <td>0.2201</td>\n","      <td>0.5601</td>\n","      <td>-0.3501</td>\n","      <td>-1.4070</td>\n","      <td>-0.1717</td>\n","      <td>-1.1160</td>\n","      <td>-0.8745</td>\n","      <td>-0.2716</td>\n","      <td>0.0189</td>\n","      <td>-2.0000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>10 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","5  id_001762a82  com_droga     24   D1  ...  1.2120  0.3765  0.7848  1.3990\n","6  id_001bd861f  com_droga     24   D2  ...  2.4670  0.0357  0.1351 -0.3179\n","7  id_0020d0484  com_droga     48   D1  ...  0.6633  0.4562 -0.9622  0.0260\n","8  id_00224bf20  com_droga     48   D1  ... -0.1167 -0.1241 -0.6420  0.5543\n","9  id_0023f063e  com_droga     48   D2  ... -0.8745 -0.2716  0.0189 -2.0000\n","\n","[10 rows x 877 columns]"]},"metadata":{"tags":[]},"execution_count":89}]},{"cell_type":"markdown","metadata":{"id":"tRlXQD_f6AHN"},"source":["Como fizemos o boxplot do g-0 com o tratamento, vou fazer o boxplot com tempo."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":520},"id":"t30JRkyS3cNq","executionInfo":{"status":"ok","timestamp":1620140688991,"user_tz":180,"elapsed":1254,"user":{"displayName":"Italo Alves","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjN_--uX1AHIM2IBNU09Hb4CqzUlfXAHZR60rP7kA=s64","userId":"09696316357588203068"}},"outputId":"762b8d6f-3a90-434e-f9c6-484b72b81b62"},"source":["plt.figure(figsize=(10,8))\n","sns.boxplot(y='g-0', x='tempo' , data=dados)"],"execution_count":93,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f4eb1d1b590>"]},"metadata":{"tags":[]},"execution_count":93},{"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":"an_7Z_w16Xkk"},"source":["Analisando o grafico eu chego na conclusão houve um comportamento muito similar mesmo com a variação do tempo. \n","\n"]},{"cell_type":"markdown","metadata":{"id":"0lHYbwHj8lp8"},"source":["# Desafio 7:\n"]},{"cell_type":"markdown","metadata":{"id":"70OcrsGb8pQO"},"source":["Nessa aula focamos em plot de graficos usando o **seaborn** e o **pandas** tanto em aspectos visuais como analiticos. Analise de graficos de **histograma** e **boxplot** fazendo seleções especificas do nosso dataframe. Usamos a função **describe()** para pegar dados estatisticos do nosso dataframe. Aplicamos a função **query** para fazer algumas seleções. Vide o NoteBook completo para mais informações."]},{"cell_type":"code","metadata":{"id":"thqmkyhi9ndO"},"source":[""],"execution_count":null,"outputs":[]}]}