analise-dados/analise-candidaturas-eleitas.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "b0dd0e23-bda2-4925-85e6-9eb9fde0b80a",
   "metadata": {},
   "source": [
    "Esse notebook destina-se a análise dos dados referentes a candidaturas eleitas entre os anos de 1995 e 2019. As perguntas estabelecidas e as hipóteses a serem comprovadas foram:\n",
    "\n",
    "1. Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação?\n",
    "    - **Hipótese:** Não houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação da Lei 9.504/1997.\n",
    "2. Após a aprovação da Lei 12.034/2009 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação?\n",
    "    - **Hipótese:** Sim, houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação da Lei 12.034/2009. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "349abb0d-516f-4487-8b3a-6e837bd873c8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ca09b14-0945-48a6-9d11-f50ae2060fa1",
   "metadata": {},
   "source": [
    "## 1. Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação?\n",
    "**Hipótese:** Não houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação da Lei 9.504/1997."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "05d199bb-96b5-45ff-8454-3386ba02253d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_legislaturas = pd.read_csv('../dados/legislaturas_1934_2023_limpas.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "24d26dda-b12b-4ad6-ab3f-3c3ff3d0ebd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>uri</th>\n",
       "      <th>dataInicio</th>\n",
       "      <th>dataFim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56</td>\n",
       "      <td>https://dadosabertos.camara.leg.br/api/v2/legi...</td>\n",
       "      <td>2019</td>\n",
       "      <td>2023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>https://dadosabertos.camara.leg.br/api/v2/legi...</td>\n",
       "      <td>2015</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>54</td>\n",
       "      <td>https://dadosabertos.camara.leg.br/api/v2/legi...</td>\n",
       "      <td>2011</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>https://dadosabertos.camara.leg.br/api/v2/legi...</td>\n",
       "      <td>2007</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52</td>\n",
       "      <td>https://dadosabertos.camara.leg.br/api/v2/legi...</td>\n",
       "      <td>2003</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                                                uri  dataInicio  dataFim\n",
       "0  56  https://dadosabertos.camara.leg.br/api/v2/legi...        2019     2023\n",
       "1  55  https://dadosabertos.camara.leg.br/api/v2/legi...        2015     2019\n",
       "2  54  https://dadosabertos.camara.leg.br/api/v2/legi...        2011     2015\n",
       "3  53  https://dadosabertos.camara.leg.br/api/v2/legi...        2007     2011\n",
       "4  52  https://dadosabertos.camara.leg.br/api/v2/legi...        2003     2007"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_legislaturas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b92e5fe7-4f6f-4e05-babb-870c7b7caa93",
   "metadata": {},
   "source": [
    "Restringe os dados a serem analisados para o período a ser analisado (1995 a 2007)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d33cf774-8dc1-4bf7-b82f-e65c8b535606",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_h1 = df_legislaturas[(df_legislaturas['id'] >= 50) & (df_legislaturas['id'] <= 53)]['id'].unique().tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e9ad2488-ed01-4de0-b348-f51cc6dec0c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidaturas_eleitas = pd.read_csv('../dados/candidaturas_eleitas.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "197ec5b4-8f08-422a-ba28-e725de86fe89",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidaturas_eleitas_h1 = df_candidaturas_eleitas[df_candidaturas_eleitas['idLegislatura'].isin(legislaturas_h1)].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e6d1626f-ce9c-4dda-bc3e-92beab378061",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([53, 52, 51, 50])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidaturas_eleitas_h1['idLegislatura'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71a2978b-c256-4ea1-9a9e-26f44e2de2c0",
   "metadata": {},
   "source": [
    "Agrupa os dados por sexo "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9d2b0c18-8c78-4d62-8fb8-690911741597",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo = df_candidaturas_eleitas_h1.groupby(['idLegislatura', 'sexo']).size().to_frame('valorAbsoluto')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c798e0f0-b01d-4ea5-b8f5-a3efc975721e",
   "metadata": {},
   "source": [
    "Estabelece porcentagem de cada categoria em relação ao total de candidaturas eleitas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ce18c43a-59fa-46de-ac0a-b4ab4e9fe15b",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo['porcentagem'] = round(agrupa_sexo['valorAbsoluto'].div(agrupa_sexo.groupby('idLegislatura')['valorAbsoluto'].transform('sum')).mul(100), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "69f90008-902e-4db6-8079-fbbbc15709c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo_df = agrupa_sexo.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "648c6641-5d07-43b0-8fca-36774708913e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>idLegislatura</th>\n",
       "      <th>sexo</th>\n",
       "      <th>valorAbsoluto</th>\n",
       "      <th>porcentagem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50</td>\n",
       "      <td>F</td>\n",
       "      <td>42</td>\n",
       "      <td>6.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>M</td>\n",
       "      <td>593</td>\n",
       "      <td>93.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51</td>\n",
       "      <td>F</td>\n",
       "      <td>39</td>\n",
       "      <td>6.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>51</td>\n",
       "      <td>M</td>\n",
       "      <td>603</td>\n",
       "      <td>93.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52</td>\n",
       "      <td>F</td>\n",
       "      <td>52</td>\n",
       "      <td>8.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>52</td>\n",
       "      <td>M</td>\n",
       "      <td>577</td>\n",
       "      <td>91.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>53</td>\n",
       "      <td>F</td>\n",
       "      <td>52</td>\n",
       "      <td>8.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>53</td>\n",
       "      <td>M</td>\n",
       "      <td>594</td>\n",
       "      <td>91.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   idLegislatura sexo  valorAbsoluto  porcentagem\n",
       "0             50    F             42         6.61\n",
       "1             50    M            593        93.39\n",
       "2             51    F             39         6.07\n",
       "3             51    M            603        93.93\n",
       "4             52    F             52         8.27\n",
       "5             52    M            577        91.73\n",
       "6             53    F             52         8.05\n",
       "7             53    M            594        91.95"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agrupa_sexo_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6e53b88-a45d-43c8-a720-0e79e3514aeb",
   "metadata": {},
   "source": [
    "Prepara os dados para visualização em plano cartesiano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bee635de-d0d3-4eae-9cc3-895593f102e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "mulher_h1 = agrupa_sexo_df[agrupa_sexo_df['sexo'] == 'F']['porcentagem'].tolist()\n",
    "homem_h1 = agrupa_sexo_df[agrupa_sexo_df['sexo'] == 'M']['porcentagem'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c71a61a3-5a9d-4480-ac2d-acf3bdb89604",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_lista_h1 = agrupa_sexo_df['idLegislatura'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "275607c3-7ac5-4773-88bd-c43b7e3ef34d",
   "metadata": {},
   "source": [
    "Substituimos o valor ordinal das legislaturas pelo ano de início para facilitar a compreensão do gráfico."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9f7d88ab-9534-42b9-a3fe-fb688bd8defd",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_lista_h1 = df_legislaturas[(df_legislaturas['id'] >= 50) & (df_legislaturas['id'] <= 53)]['dataInicio'].unique().tolist()\n",
    "legislaturas_lista_h1.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b37dc80a-6c8c-4587-b151-a594f5cb2aeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1995', '1999', '2003', '2007']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "legislaturas_lista_h1 = list(map(str, legislaturas_lista_h1))\n",
    "legislaturas_lista_h1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f113e339-e35c-4cfa-bd19-16fd1d43feab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "agrupa_sexo_df2 = pd.DataFrame({'mulher': mulher_h1,\n",
    "                               'homem': homem_h1\n",
    "                               }, index=legislaturas_lista_h1,\n",
    "                              )\n",
    "agrupa_sexo_df2.plot.line()\n",
    "agrupa_sexo_df2.to_csv('../dados/analise_genero_1995_2007.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e398564-db38-4281-b762-e7bf097bacd2",
   "metadata": {},
   "source": [
    "Para melhor visualizar as variações, estabelecemos gráficos para cada gênero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9b741c36-7746-4613-af53-c2a21f69e631",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:>, <AxesSubplot:>], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "agrupa_sexo_df2.plot.line(subplots=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7d01681b-dad7-4b6d-a6ec-2b20fd3e92df",
   "metadata": {},
   "outputs": [],
   "source": [
    "diferenca_percentual_mulher_h1_total = mulher_h1[-1] - mulher_h1[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f396a8a4-f30d-4ddd-a7a6-6296791585f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Pergunta: Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas \n",
      "3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação? \n",
      " \n",
      "Resposta: Houve aumento de  1.44% no total de mulheres deputadas entre 1995 e 2007.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(f'''\n",
    "Pergunta: Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas \n",
    "3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação? \\n \n",
    "Resposta: Houve aumento de  {round(diferenca_percentual_mulher_h1_total, 2)}% no total de mulheres deputadas entre 1995 e 2007.\n",
    "''')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a282d850-bbdc-448e-8487-52c7442d9bf3",
   "metadata": {},
   "source": [
    "## 2. Após a aprovação da Lei 12.034/2009 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação?\n",
    "**Hipótese:** Sim, houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas 3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação da Lei 12.034/2009."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de47d771-e444-4f78-88fb-d9f4541bc891",
   "metadata": {},
   "source": [
    "Restringe os dados a serem analisados para o período a ser analisado (2007 a 2019)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aebd9912-bd7e-4659-837d-c898cf08bf92",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_h2 = df_legislaturas[(df_legislaturas['id'] >= 53) & (df_legislaturas['id'] <= 56)]['id'].unique().tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fc3ecf44-15c1-4170-82f1-ec97163fd541",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_candidaturas_eleitas_h2 = df_candidaturas_eleitas[df_candidaturas_eleitas['idLegislatura'].isin(legislaturas_h2)].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f13322d8-cc87-4da7-b6bc-ee3e4885fb47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([56, 55, 54, 53])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_candidaturas_eleitas_h2['idLegislatura'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da8840a4-19d3-436c-a7e7-0b69ddf4a22a",
   "metadata": {},
   "source": [
    "Agrua os dados por sexo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2362e44e-daf9-4934-93ef-dd3a4e521635",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo_h2 = df_candidaturas_eleitas_h2.groupby(['idLegislatura', 'sexo']).size().to_frame('valorAbsoluto')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd0e613a-bc45-4802-973b-84e3f6738de0",
   "metadata": {},
   "source": [
    "Estabelece porcentagem de cada categoria em relação ao total de candidaturas eleitas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5460c459-135f-43a1-bfef-0d8e8732a18b",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo_h2['porcentagem'] = round(agrupa_sexo_h2['valorAbsoluto'].div(agrupa_sexo_h2.groupby('idLegislatura')['valorAbsoluto'].transform('sum')).mul(100), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1101276b-2ee2-4846-857a-07f02ea55e31",
   "metadata": {},
   "outputs": [],
   "source": [
    "agrupa_sexo_h2_df = agrupa_sexo_h2.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "430ba62a-7dfd-410b-a3ca-e2030ed3ea93",
   "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></th>\n",
       "      <th>valorAbsoluto</th>\n",
       "      <th>porcentagem</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>idLegislatura</th>\n",
       "      <th>sexo</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">53</th>\n",
       "      <th>F</th>\n",
       "      <td>52</td>\n",
       "      <td>8.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>594</td>\n",
       "      <td>91.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">54</th>\n",
       "      <th>F</th>\n",
       "      <td>60</td>\n",
       "      <td>8.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>611</td>\n",
       "      <td>91.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">55</th>\n",
       "      <th>F</th>\n",
       "      <td>66</td>\n",
       "      <td>10.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>567</td>\n",
       "      <td>89.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">56</th>\n",
       "      <th>F</th>\n",
       "      <td>87</td>\n",
       "      <td>14.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>510</td>\n",
       "      <td>85.43</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    valorAbsoluto  porcentagem\n",
       "idLegislatura sexo                            \n",
       "53            F                52         8.05\n",
       "              M               594        91.95\n",
       "54            F                60         8.94\n",
       "              M               611        91.06\n",
       "55            F                66        10.43\n",
       "              M               567        89.57\n",
       "56            F                87        14.57\n",
       "              M               510        85.43"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agrupa_sexo_h2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5079aa7-f94b-4b29-80e3-f268f1a429ca",
   "metadata": {},
   "source": [
    "Prepara os dados para visualização em plano cartesiano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2e7b21c9-b502-403f-b27d-68e877efdf45",
   "metadata": {},
   "outputs": [],
   "source": [
    "mulher_h2 = agrupa_sexo_h2_df[agrupa_sexo_h2_df['sexo'] == 'F']['porcentagem'].tolist()\n",
    "homem_h2 = agrupa_sexo_h2_df[agrupa_sexo_h2_df['sexo'] == 'M']['porcentagem'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "95c4de74-f602-4a8e-9b55-fd9a0b00ea68",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_lista_h2 = agrupa_sexo_h2_df['idLegislatura'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d7ceb74-788f-4239-b6cd-36045535f9a0",
   "metadata": {},
   "source": [
    "Substituimos o valor ordinal das legislaturas pelo ano de início para facilitar a compreensão do gráfico."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9840aa3c-abe0-457b-a30d-225aa47e164c",
   "metadata": {},
   "outputs": [],
   "source": [
    "legislaturas_lista_h2 = df_legislaturas[(df_legislaturas['id'] >= 53) & (df_legislaturas['id'] <= 56)]['dataInicio'].unique().tolist()\n",
    "legislaturas_lista_h2.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6b576f91-6438-458a-b392-68ea1af23592",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2007', '2011', '2015', '2019']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "legislaturas_lista_h2 = list(map(str, legislaturas_lista_h2))\n",
    "legislaturas_lista_h2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "84e1a7a3-2104-4cc0-b7b8-056cc0ad34a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "agrupa_sexo_h2_df2 = pd.DataFrame({'mulher': mulher_h2,\n",
    "                               'homem': homem_h2\n",
    "                               }, index=legislaturas_lista_h2,\n",
    "                              )\n",
    "agrupa_sexo_h2_df2.plot.line()\n",
    "agrupa_sexo_h2_df2.to_csv('../dados/analise_genero_2007_2019.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8a86cf3-6ffb-412c-b92d-45a0d93f8b49",
   "metadata": {},
   "source": [
    "Para melhor visualizar as variações, estabelecemos gráficos para cada gênero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3fa0e5cf-3cb0-4d83-a49f-7cf3053128d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:>, <AxesSubplot:>], dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "agrupa_sexo_h2_df2.plot.line(subplots=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f7791a2a-e599-445b-abfd-a5c5feeeeabe",
   "metadata": {},
   "outputs": [],
   "source": [
    "diferenca_percentual_mulher_h2_total = mulher_h2[-1] - mulher_h2[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "73e51043-f9e4-40e6-bfe2-d16f2946b5f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Pergunta: Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas \n",
      "3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação? \n",
      " \n",
      "Resposta: Houve aumento de  6.52% no total de mulheres deputadas entre 2007 e 2019.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(f'''\n",
    "Pergunta: Após a aprovação da Lei 9.504/1997 houve aumento no percentual de mulheres eleitas para o cargo de deputada federal nas \n",
    "3 legislações subsequentes em comparação com o percentual existente na data de sua aprovação? \\n \n",
    "Resposta: Houve aumento de  {round(diferenca_percentual_mulher_h2_total, 2)}% no total de mulheres deputadas entre 2007 e 2019.\n",
    "''')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}