Explicando a dificuldade de um estudo farmacologico para o grupo da familia.ipynb

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  {
   "cell_type": "markdown",
   "id": "careful-casino",
   "metadata": {},
   "source": [
    "<img src= 'bomdiafamilia.jpeg' width=\"300\" height=\"300\" >"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "continent-machinery",
   "metadata": {},
   "source": [
    "# Introdução\n",
    "#### Bom dia tias! Fiz esse trabalho para mostrar porquê não devemos compartilhar mensagens de zapzap com \"prescrições de medicamentos\" feitas por quem não é profissional da área.\n",
    "#### Esses estudos são complexos, envolvem muito tempo, dados, pesquisas... e muitas vezes um composto pode ter uma ação colateral onde nem imaginamos... por isso é preciso ter uma visão longe de qualquer viés, analisando diversos efeito em diversos genes... segue abaixo."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "undefined-switch",
   "metadata": {},
   "source": [
    "# Capítulo [0] - Carregando e analisando a complexidade dos dados"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "isolated-korean",
   "metadata": {},
   "source": [
    "<img src= 'Gatinho.jpeg' width=\"200\" height=\"150\" >"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "perceived-mumbai",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Aqui estamos importando a biblioteca principal para analisarmos os dados e as tabelas base do estudo\n",
    "import pandas as pd\n",
    "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
    "dados = pd.read_csv(url_dados, compression = 'zip')\n",
    "\n",
    "dados_resultados = pd.read_csv('https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_resultados.csv?raw=true')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "grand-prayer",
   "metadata": {},
   "source": [
    "Abaixo, veremos as 5 primeiras linhas da tabela para termos uma ideia dos seus dados e o seu tamanho. Aqui já vemos algumas coisas interessantes:\n",
    "\n",
    "1 - O ID do composto é codificado, para que não exista qualquer víes na análise dos dados (coisa muito comum nos dias de hoje).\n",
    "2 - A primeira tabela, que avalia droga, dosagem e tempo, possui 23814 linhas e 877 colunas. A segunda tabela, que trata das respostas aos tratamentos, possui 23814 linhas e 207 colunas; juntas totalizando quase 26 milhões de células (daí uma das importâncias do machine learning para cruzamento e análise desses dados)."
   ]
  },
  {
   "cell_type": "code",
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   "id": "incomplete-vanilla",
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   "outputs": [
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       "             id tratamento  tempo dose      droga     g-0     g-1     g-2  \\\n",
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   "cell_type": "code",
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   "id": "immediate-morrison",
   "metadata": {},
   "outputs": [
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       "             id  5-alpha_reductase_inhibitor  11-beta-hsd1_inhibitor  \\\n",
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  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "returning-midwest",
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     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados_resultados.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hidden-character",
   "metadata": {},
   "source": [
    "Abaixo temos um data frame com a distribuição dos compostos analisados. Podemos constatar que tivemos 3289 compostos avaliados (considerando também o controle)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "double-picking",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>droga</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cacb2b860</th>\n",
       "      <td>1866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87d714366</th>\n",
       "      <td>718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9f80f3f77</th>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8b87a7a83</th>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5628cb3ee</th>\n",
       "      <td>202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <th>98c4c858e</th>\n",
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       "      <th>b6b4f212d</th>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>07cca32e8</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866e7bc56</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3289 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           droga\n",
       "cacb2b860   1866\n",
       "87d714366    718\n",
       "9f80f3f77    246\n",
       "8b87a7a83    203\n",
       "5628cb3ee    202\n",
       "...          ...\n",
       "98c4c858e      1\n",
       "d9fcbe12c      1\n",
       "b6b4f212d      1\n",
       "07cca32e8      1\n",
       "866e7bc56      1\n",
       "\n",
       "[3289 rows x 1 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drogas = pd.DataFrame(dados.droga.value_counts())\n",
    "drogas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "quiet-genealogy",
   "metadata": {},
   "source": [
    "Segue a \"droga\" controle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "average-ministry",
   "metadata": {},
   "outputs": [
    {
     "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>droga</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cacb2b860</th>\n",
       "      <td>1866</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           droga\n",
       "cacb2b860   1866"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados_com_controle = dados.query('tratamento == \"com_controle\"')['droga'].value_counts()\n",
    "pd.DataFrame(dados_com_controle)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mathematical-tobago",
   "metadata": {},
   "source": [
    "Aqui temos um resumo dos tipos de exposições diferentes (tempo e dosagem) que cada composto sofreu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "noted-january",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>dose</th>\n",
       "      <th colspan=\"3\" halign=\"left\">D1</th>\n",
       "      <th colspan=\"3\" halign=\"left\">D2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tempo</th>\n",
       "      <th>24</th>\n",
       "      <th>48</th>\n",
       "      <th>72</th>\n",
       "      <th>24</th>\n",
       "      <th>48</th>\n",
       "      <th>72</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>droga</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>00199ff52</th>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>00321ea80</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>0034c0847</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>0060e686f</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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",
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       "    <tr>\n",
       "      <th>ff9565933</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>ffd66e220</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ffe357f8f</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ffed8e1c9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fff7d208d</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3289 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "dose      D1       D2      \n",
       "tempo     24 48 72 24 48 72\n",
       "droga                      \n",
       "00199ff52  1  1  1  1  1  1\n",
       "00251fc41  1  1  1  1  1  1\n",
       "00321ea80  2  2  2  2  2  2\n",
       "0034c0847  1  1  1  1  1  1\n",
       "0060e686f  1  1  1  1  1  1\n",
       "...       .. .. .. .. .. ..\n",
       "ff9565933  1  1  1  1  1  1\n",
       "ffd66e220  1  1  1  1  1  1\n",
       "ffe357f8f  0  1  0  0  0  0\n",
       "ffed8e1c9  1  1  1  1  1  1\n",
       "fff7d208d  1  1  1  1  1  1\n",
       "\n",
       "[3289 rows x 6 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab([dados['dose'], dados['tempo']],  dados['droga']).T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "varying-sphere",
   "metadata": {},
   "source": [
    "# Capítulo [1] - Análise gráfica e estatística\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pharmaceutical-globe",
   "metadata": {},
   "source": [
    "<img src= 'meireles.jpg' width=\"300\" height=\"300\" >"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "present-criticism",
   "metadata": {},
   "source": [
    "Cada teste de tratamento possui um resultado heterogêneo para cada um dos genes e tipos celulares testado (resumo na tabela abaixo), por isso, a importância dos gráficos, para ajudar a ilustrar e entender o comportamento geral do estudo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "worse-commander",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tempo</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>48.020156</td>\n",
       "      <td>19.402807</td>\n",
       "      <td>24.000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>48.00000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>72.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g-0</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>0.248366</td>\n",
       "      <td>1.393399</td>\n",
       "      <td>-5.513</td>\n",
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       "      <td>-0.00885</td>\n",
       "      <td>0.525700</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g-1</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.095684</td>\n",
       "      <td>0.812363</td>\n",
       "      <td>-5.737</td>\n",
       "      <td>-0.562200</td>\n",
       "      <td>-0.04660</td>\n",
       "      <td>0.403075</td>\n",
       "      <td>5.039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g-2</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>0.152253</td>\n",
       "      <td>1.035731</td>\n",
       "      <td>-9.104</td>\n",
       "      <td>-0.437750</td>\n",
       "      <td>0.07520</td>\n",
       "      <td>0.663925</td>\n",
       "      <td>8.257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g-3</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>0.081971</td>\n",
       "      <td>0.950012</td>\n",
       "      <td>-5.998</td>\n",
       "      <td>-0.429575</td>\n",
       "      <td>0.00805</td>\n",
       "      <td>0.463400</td>\n",
       "      <td>10.000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c-95</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.353726</td>\n",
       "      <td>1.629291</td>\n",
       "      <td>-10.000</td>\n",
       "      <td>-0.567975</td>\n",
       "      <td>-0.01025</td>\n",
       "      <td>0.444750</td>\n",
       "      <td>2.814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c-96</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.463485</td>\n",
       "      <td>2.059725</td>\n",
       "      <td>-10.000</td>\n",
       "      <td>-0.552575</td>\n",
       "      <td>-0.00125</td>\n",
       "      <td>0.465225</td>\n",
       "      <td>3.505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c-97</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.378241</td>\n",
       "      <td>1.703615</td>\n",
       "      <td>-10.000</td>\n",
       "      <td>-0.561000</td>\n",
       "      <td>-0.00680</td>\n",
       "      <td>0.446400</td>\n",
       "      <td>2.924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c-98</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.470252</td>\n",
       "      <td>1.834828</td>\n",
       "      <td>-10.000</td>\n",
       "      <td>-0.592600</td>\n",
       "      <td>0.01400</td>\n",
       "      <td>0.461275</td>\n",
       "      <td>3.111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c-99</th>\n",
       "      <td>23814.0</td>\n",
       "      <td>-0.301505</td>\n",
       "      <td>1.407918</td>\n",
       "      <td>-10.000</td>\n",
       "      <td>-0.562900</td>\n",
       "      <td>-0.01950</td>\n",
       "      <td>0.438650</td>\n",
       "      <td>3.805</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>873 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         count       mean        std     min        25%       50%        75%  \\\n",
       "tempo  23814.0  48.020156  19.402807  24.000  24.000000  48.00000  72.000000   \n",
       "g-0    23814.0   0.248366   1.393399  -5.513  -0.473075  -0.00885   0.525700   \n",
       "g-1    23814.0  -0.095684   0.812363  -5.737  -0.562200  -0.04660   0.403075   \n",
       "g-2    23814.0   0.152253   1.035731  -9.104  -0.437750   0.07520   0.663925   \n",
       "g-3    23814.0   0.081971   0.950012  -5.998  -0.429575   0.00805   0.463400   \n",
       "...        ...        ...        ...     ...        ...       ...        ...   \n",
       "c-95   23814.0  -0.353726   1.629291 -10.000  -0.567975  -0.01025   0.444750   \n",
       "c-96   23814.0  -0.463485   2.059725 -10.000  -0.552575  -0.00125   0.465225   \n",
       "c-97   23814.0  -0.378241   1.703615 -10.000  -0.561000  -0.00680   0.446400   \n",
       "c-98   23814.0  -0.470252   1.834828 -10.000  -0.592600   0.01400   0.461275   \n",
       "c-99   23814.0  -0.301505   1.407918 -10.000  -0.562900  -0.01950   0.438650   \n",
       "\n",
       "          max  \n",
       "tempo  72.000  \n",
       "g-0    10.000  \n",
       "g-1     5.039  \n",
       "g-2     8.257  \n",
       "g-3    10.000  \n",
       "...       ...  \n",
       "c-95    2.814  \n",
       "c-96    3.505  \n",
       "c-97    2.924  \n",
       "c-98    3.111  \n",
       "c-99    3.805  \n",
       "\n",
       "[873 rows x 8 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "trained-clinic",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Aqui estamos importando as principais bibliotecas para plotarmos gráficos\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "#Importante para a configuração padrão do gráfico\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "growing-junior",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separando tabelas com a disribuição das ações máximas e mínimas nos testes com droga.\n",
    "dados_com_droga = dados.query('tratamento == \"com_droga\"' )\n",
    "dados_max_com_droga = pd.DataFrame(dados_com_droga.loc[:,'g-0':'g-771'].max())\n",
    "dados_min_com_droga = pd.DataFrame(dados_com_droga.loc[:,'g-0':'g-771'].min())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "alone-atlanta",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separando tabelas com a disribuição das ações máximas e mínimas nos testes sem droga.\n",
    "dados_com_controle = dados.query('tratamento == \"com_controle\"' )\n",
    "dados_max_com_controle = pd.DataFrame(dados_com_controle.loc[:,'g-0':'g-771'].max())\n",
    "dados_min_com_controle = pd.DataFrame(dados_com_controle.loc[:,'g-0':'g-771'].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "steady-remove",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Ação Máxima Genes Com Droga\n",
    "\n",
    "ax = sns.histplot(data=dados_max_com_droga,bins=20)\n",
    "ax.set_title('Ação Máxima Genes Com Droga')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "forced-addiction",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Ação Máxima Genes Sem Droga\n",
    "ay = sns.histplot(data=dados_max_com_controle,bins=20)\n",
    "ay.set_title('Ação Máxima Genes Sem Droga')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "daily-compilation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Ação Mínima Genes Com Droga\n",
    "\n",
    "ax = sns.histplot(data=dados_min_com_droga,bins=20)\n",
    "ax.set_title('Ação Mínima Genes Com Droga')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "threaded-tactics",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Ação Mínima Genes sem Droga\n",
    "\n",
    "ax = sns.histplot(data=dados_min_com_controle,bins=20)\n",
    "ax.set_title('Ação Mínima Genes Sem Droga')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ethical-speed",
   "metadata": {},
   "source": [
    "Como vimos nos gráficos anteriores, o comportamento nos genes varia muito diante das substâncias, dependo da ação resultante, podendo ser um efeito desejado ou não, contudo, cada impacto deve ser avaliado,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "ideal-solomon",
   "metadata": {},
   "outputs": [
    {
     "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>...</th>\n",
       "      <th>g-91</th>\n",
       "      <th>g-92</th>\n",
       "      <th>g-93</th>\n",
       "      <th>g-94</th>\n",
       "      <th>g-95</th>\n",
       "      <th>g-96</th>\n",
       "      <th>g-97</th>\n",
       "      <th>g-98</th>\n",
       "      <th>g-99</th>\n",
       "      <th>g-100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>g-0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.086032</td>\n",
       "      <td>0.176188</td>\n",
       "      <td>0.011266</td>\n",
       "      <td>0.403153</td>\n",
       "      <td>-0.165478</td>\n",
       "      <td>0.238348</td>\n",
       "      <td>-0.374451</td>\n",
       "      <td>-0.604212</td>\n",
       "      <td>-0.428779</td>\n",
       "      <td>...</td>\n",
       "      <td>0.526045</td>\n",
       "      <td>0.472513</td>\n",
       "      <td>0.114816</td>\n",
       "      <td>0.144616</td>\n",
       "      <td>0.536962</td>\n",
       "      <td>-0.540144</td>\n",
       "      <td>0.634276</td>\n",
       "      <td>-0.555911</td>\n",
       "      <td>-0.19658</td>\n",
       "      <td>0.670014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 101 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     g-0       g-1       g-2       g-3       g-4       g-5       g-6  \\\n",
       "g-0  1.0  0.086032  0.176188  0.011266  0.403153 -0.165478  0.238348   \n",
       "\n",
       "          g-7       g-8       g-9  ...      g-91      g-92      g-93  \\\n",
       "g-0 -0.374451 -0.604212 -0.428779  ...  0.526045  0.472513  0.114816   \n",
       "\n",
       "         g-94      g-95      g-96      g-97      g-98     g-99     g-100  \n",
       "g-0  0.144616  0.536962 -0.540144  0.634276 -0.555911 -0.19658  0.670014  \n",
       "\n",
       "[1 rows x 101 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = dados.loc[:,'g-0':'g-100'].corr()\n",
    "corr.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "novel-baghdad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
    "f, ax = plt.subplots(figsize=(20, 20))\n",
    "ax.set_title('Correlação entre os genes', fontsize=20)\n",
    "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "selected-horizon",
   "metadata": {},
   "source": [
    "O gráfico acima mostra a correlação entre os genes, mostrando como uma ação é \"sentida proporcionalmente\" entre os genes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "available-charity",
   "metadata": {},
   "source": [
    "Abaixo vemos nos gráficos de dispersão, como se comportaram os testes com droga e sem droga e a relação entre 2 genes. Isso é para reforçar que tudo deve ser avaliado. As vezes um determinado composto tem uma ação pretendida, porém, ele acaba afetando outra área."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "driven-sensitivity",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(data=dados, x='g-63', y='g-37', line_kws={'color': 'red'}, col='tratamento', row='tempo')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "front-birthday",
   "metadata": {},
   "source": [
    "# Capítulo [2] - Proposta de machine learning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "seasonal-nirvana",
   "metadata": {},
   "source": [
    "<img src= 'orgulho.jpg' width=\"300\" height=\"200\" >"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "special-warrant",
   "metadata": {},
   "source": [
    "Então tias, como vimos até aqui, foi um monte de informações, o que seria impossível para um ser humano analisar, relacionar, gerar um modelo de predição... para isso existe um machine learning! O computador chegará a uma conclusão, baseado em um algoritmo definido."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acting-network",
   "metadata": {},
   "source": [
    "Existem inúmeros modelos para se escolher, conforme a figura abaixo. Vamos tentar testar algum."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "talented-motorcycle",
   "metadata": {},
   "source": [
    "<img src= 'ml_map.png'>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "satellite-somerset",
   "metadata": {},
   "source": [
    "Agora precisamos compilar o resultado da ativação com o tratamento, para podermos criar um modelo que chegue à conclusão se determinado composto/tratamento, produzirá uma ativação."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "compatible-poetry",
   "metadata": {},
   "outputs": [
    {
     "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>5-alpha_reductase_inhibitor</th>\n",
       "      <th>11-beta-hsd1_inhibitor</th>\n",
       "      <th>acat_inhibitor</th>\n",
       "      <th>acetylcholine_receptor_agonist</th>\n",
       "      <th>acetylcholine_receptor_antagonist</th>\n",
       "      <th>acetylcholinesterase_inhibitor</th>\n",
       "      <th>adenosine_receptor_agonist</th>\n",
       "      <th>adenosine_receptor_antagonist</th>\n",
       "      <th>adenylyl_cyclase_activator</th>\n",
       "      <th>...</th>\n",
       "      <th>trpv_antagonist</th>\n",
       "      <th>tubulin_inhibitor</th>\n",
       "      <th>tyrosine_kinase_inhibitor</th>\n",
       "      <th>ubiquitin_specific_protease_inhibitor</th>\n",
       "      <th>vegfr_inhibitor</th>\n",
       "      <th>vitamin_b</th>\n",
       "      <th>vitamin_d_receptor_agonist</th>\n",
       "      <th>wnt_inhibitor</th>\n",
       "      <th>n_moa</th>\n",
       "      <th>ativo_moa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 209 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  5-alpha_reductase_inhibitor  11-beta-hsd1_inhibitor  \\\n",
       "0  id_000644bb2                            0                       0   \n",
       "\n",
       "   acat_inhibitor  acetylcholine_receptor_agonist  \\\n",
       "0               0                               0   \n",
       "\n",
       "   acetylcholine_receptor_antagonist  acetylcholinesterase_inhibitor  \\\n",
       "0                                  0                               0   \n",
       "\n",
       "   adenosine_receptor_agonist  adenosine_receptor_antagonist  \\\n",
       "0                           0                              0   \n",
       "\n",
       "   adenylyl_cyclase_activator  ...  trpv_antagonist  tubulin_inhibitor  \\\n",
       "0                           0  ...                0                  0   \n",
       "\n",
       "   tyrosine_kinase_inhibitor  ubiquitin_specific_protease_inhibitor  \\\n",
       "0                          0                                      0   \n",
       "\n",
       "   vegfr_inhibitor  vitamin_b  vitamin_d_receptor_agonist  wnt_inhibitor  \\\n",
       "0                0          0                           0              0   \n",
       "\n",
       "   n_moa  ativo_moa  \n",
       "0      1       True  \n",
       "\n",
       "[1 rows x 209 columns]"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Somatório de mecanismos de ativação dos resultados. Caso o resultado seja 0, ativo_moa = False\n",
    "dados_resultados['n_moa'] = dados_resultados.drop('id', axis=1).sum(axis=1)\n",
    "dados_resultados['ativo_moa'] = (dados_resultados['n_moa'] != 0)\n",
    "dados_resultados.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "defensive-tribute",
   "metadata": {},
   "outputs": [
    {
     "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>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>...</th>\n",
       "      <th>c-99</th>\n",
       "      <th>n_moa</th>\n",
       "      <th>ativo_moa</th>\n",
       "      <th>tratamento_com_controle</th>\n",
       "      <th>tratamento_com_droga</th>\n",
       "      <th>dose_D1</th>\n",
       "      <th>dose_D2</th>\n",
       "      <th>tempo_24</th>\n",
       "      <th>tempo_48</th>\n",
       "      <th>tempo_72</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_000644bb2</td>\n",
       "      <td>b68db1d53</td>\n",
       "      <td>1.062</td>\n",
       "      <td>0.5577</td>\n",
       "      <td>-0.2479</td>\n",
       "      <td>-0.6208</td>\n",
       "      <td>-0.1944</td>\n",
       "      <td>-1.012</td>\n",
       "      <td>-1.022</td>\n",
       "      <td>-0.0326</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4176</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 883 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id      droga    g-0     g-1     g-2     g-3     g-4    g-5  \\\n",
       "0  id_000644bb2  b68db1d53  1.062  0.5577 -0.2479 -0.6208 -0.1944 -1.012   \n",
       "\n",
       "     g-6     g-7  ...    c-99  n_moa  ativo_moa  tratamento_com_controle  \\\n",
       "0 -1.022 -0.0326  ...  0.4176      1       True                        0   \n",
       "\n",
       "   tratamento_com_droga  dose_D1  dose_D2  tempo_24  tempo_48  tempo_72  \n",
       "0                     1        1        0         1         0         0  \n",
       "\n",
       "[1 rows x 883 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Junção do resultado(n_moa e ativo_moa) com a base de dados do experimento\n",
    "dados_combinados = pd.merge(dados, dados_resultados[['id','n_moa', 'ativo_moa']], on='id')\n",
    "# Transformando as variáveis categóricas do experimento em resultados binários, para facilitar a vida do modelo de machine learnig\n",
    "dados_combinados = pd.get_dummies(dados_combinados, columns=['tratamento', 'dose', 'tempo'])\n",
    "dados_combinados.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "welcome-newfoundland",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia Random Forest: 69.01%\n"
     ]
    }
   ],
   "source": [
    "#Separando treino e teste. Os dados avaliados serão todos os dados numéricos da planilha e o alvo será se ele foi ativado ou não.\n",
    "# Foi destinado 70% da base para treinar e 30% para ver o quão bem ele aprendeu.\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "x = dados_combinados.drop(['id', 'n_moa', 'ativo_moa', 'droga'], axis=1)\n",
    "y = dados_combinados['ativo_moa'] \n",
    "x_treino, x_teste, y_treino, y_teste = train_test_split(x, y, test_size = 0.3, stratify=y, random_state=5)\n",
    "\n",
    "modelo_randomforest = RandomForestClassifier()\n",
    "modelo_randomforest.fit(x_treino, y_treino)\n",
    "modelo_randomforest.score(x_teste, y_teste)\n",
    "print(\"Acurácia Random Forest: {0:.2%}\".format(modelo_randomforest.score(x_teste, y_teste)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "happy-traffic",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia SGD Classifier: 62.97%\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import SGDClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "\n",
    "x = dados_combinados.drop(['id', 'n_moa', 'ativo_moa', 'droga'], axis=1)\n",
    "y = dados_combinados['ativo_moa'] \n",
    "x_treino, x_teste, y_treino, y_teste = train_test_split(x, y, test_size = 0.3, stratify=y, random_state=5)\n",
    "accuracy_all = []\n",
    "\n",
    "\n",
    "\n",
    "clf = SGDClassifier()\n",
    "clf.fit(x_treino, y_treino)\n",
    "prediction = clf.predict(x_teste)\n",
    "accuracy_all.append(accuracy_score(prediction, y_teste))\n",
    "\n",
    "\n",
    "print(\"Acurácia SGD Classifier: {0:.2%}\".format(accuracy_score(prediction, y_teste)))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "junior-syndication",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia do LinearSVC: 61.41%\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\a4mj\\Anaconda3\\lib\\site-packages\\sklearn\\svm\\_base.py:986: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  \"the number of iterations.\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import LinearSVC\n",
    "x = dados_combinados.drop(['id', 'n_moa', 'ativo_moa', 'droga'], axis=1)\n",
    "y = dados_combinados['ativo_moa'] \n",
    "x_treino, x_teste, y_treino, y_teste = train_test_split(x, y, test_size = 0.3, stratify=y, random_state=5)\n",
    "accuracy_all = []\n",
    "clf = LinearSVC()\n",
    "clf.fit(x_treino, y_treino)\n",
    "prediction = clf.predict(x_teste)\n",
    "accuracy_all.append(accuracy_score(prediction, y_teste))\n",
    "\n",
    "print(\"Acurácia do LinearSVC: {0:.2%}\".format(accuracy_score(prediction, y_teste)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "shaped-authority",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia do Kneighbors: 61.64%\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "x = dados_combinados.drop(['id', 'n_moa', 'ativo_moa', 'droga'], axis=1)\n",
    "y = dados_combinados['ativo_moa'] \n",
    "x_treino, x_teste, y_treino, y_teste = train_test_split(x, y, test_size = 0.3, stratify=y, random_state=5)\n",
    "accuracy_all = []\n",
    "\n",
    "clf = KNeighborsClassifier()\n",
    "clf.fit(x_treino, y_treino)\n",
    "prediction = clf.predict(x_teste)\n",
    "\n",
    "accuracy_all.append(accuracy_score(prediction, y_teste))\n",
    "\n",
    "\n",
    "print(\"Acurácia do Kneighbors: {0:.2%}\".format(accuracy_score(prediction, y_teste)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "successful-weather",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia do GaussianNB: 46.94%\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "x = dados_combinados.drop(['id', 'n_moa', 'ativo_moa', 'droga'], axis=1)\n",
    "y = dados_combinados['ativo_moa'] \n",
    "x_treino, x_teste, y_treino, y_teste = train_test_split(x, y, test_size = 0.3, stratify=y, random_state=5)\n",
    "accuracy_all = []\n",
    "\n",
    "clf = GaussianNB()\n",
    "clf.fit(x_treino, y_treino)\n",
    "prediction = clf.predict(x_teste)\n",
    "\n",
    "accuracy_all.append(accuracy_score(prediction, y_teste))\n",
    "\n",
    "print(\"Acurácia do GaussianNB: {0:.2%}\".format(accuracy_score(prediction, y_teste)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "agreed-columbus",
   "metadata": {},
   "source": [
    "# Capítulo [3] - Conclusão"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mediterranean-scanner",
   "metadata": {},
   "source": [
    "Tias Conceião, Celinha, Neuza, Rita... e todas as tias do mundo; o que concluo desse trabalho é que diretamente, eu não sou capaz de concluir nada, apenas que nesse campo de drug discovery é necessário muita pesquisa, ética, investimento e cientistas altamente capazes, tanto no campo da biomedicina quanto da ciência de dados, portanto, quando receberem um zapzap sobre um medicamento, ou uma indicação de figura pública que não seja médico ou da área da pesquisa, verifique.\n",
    "\n",
    "Procure se a informação é fake, procure se existe algum estudo sobre... Nossa saúde vale essa pesquisa!<br>\n",
    "https://g1.globo.com/fato-ou-fake/<br>\n",
    "https://www.nejm.org/doi/full/10.1056/NEJMoa2019014?query=featured_home<br>\n",
    "https://www.bbc.com/portuguese/geral-54360958<br>\n",
    "https://saude.ig.com.br/2021-01-21/covid-19-cloroquina-vai-da-eficacia-nao-comprovada-a-ineficacia-comprovada.html<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "median-alarm",
   "metadata": {},
   "source": [
    "<img src= 'tia.jpg' width=\"300\" height=\"200\" >"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "thirty-thread",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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