Mod9Tarefa1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Livro para consulta:\n",
    "- https://jakevdp.github.io/PythonDataScienceHandbook/03.08-aggregation-and-grouping.html\n",
    "- https://jakevdp.github.io/PythonDataScienceHandbook/03.09-pivot-tables.html\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Importando bibliotecas <a name=\"import\"></a>\n",
    "\n",
    "<div style=\"text-align: right\"\n",
    "     \n",
    "[Voltar ao índice](#Contents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-06T21:12:37.298706Z",
     "start_time": "2021-06-06T21:12:36.656481Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Carregando o dataframe SINASC <a name=\"read\"></a>\n",
    "<div style=\"text-align: right\"\n",
    "     \n",
    "[Voltar ao índice](#Contents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-06T21:12:37.762376Z",
     "start_time": "2021-06-06T21:12:37.728383Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIGEM</th>\n",
       "      <th>CODESTAB</th>\n",
       "      <th>CODMUNNASC</th>\n",
       "      <th>LOCNASC</th>\n",
       "      <th>IDADEMAE</th>\n",
       "      <th>ESTCIVMAE</th>\n",
       "      <th>ESCMAE</th>\n",
       "      <th>CODOCUPMAE</th>\n",
       "      <th>QTDFILVIVO</th>\n",
       "      <th>QTDFILMORT</th>\n",
       "      <th>...</th>\n",
       "      <th>KOTELCHUCK</th>\n",
       "      <th>CONTADOR</th>\n",
       "      <th>munResStatus</th>\n",
       "      <th>munResTipo</th>\n",
       "      <th>munResNome</th>\n",
       "      <th>munResUf</th>\n",
       "      <th>munResLat</th>\n",
       "      <th>munResLon</th>\n",
       "      <th>munResAlt</th>\n",
       "      <th>munResArea</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2679477.0</td>\n",
       "      <td>110001</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>MUNIC</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "      <td>Rondônia</td>\n",
       "      <td>-11.93554</td>\n",
       "      <td>-61.99982</td>\n",
       "      <td>338.0</td>\n",
       "      <td>7067.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2679477.0</td>\n",
       "      <td>110001</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>999992.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>MUNIC</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "      <td>Rondônia</td>\n",
       "      <td>-11.93554</td>\n",
       "      <td>-61.99982</td>\n",
       "      <td>338.0</td>\n",
       "      <td>7067.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2679477.0</td>\n",
       "      <td>110001</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>513205.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>MUNIC</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "      <td>Rondônia</td>\n",
       "      <td>-11.93554</td>\n",
       "      <td>-61.99982</td>\n",
       "      <td>338.0</td>\n",
       "      <td>7067.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2516500.0</td>\n",
       "      <td>110001</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12 anos ou mais</td>\n",
       "      <td>231205.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>MUNIC</td>\n",
       "      <td>Alto Alegre dos Parecis</td>\n",
       "      <td>Rondônia</td>\n",
       "      <td>-12.13178</td>\n",
       "      <td>-61.85308</td>\n",
       "      <td>397.0</td>\n",
       "      <td>3958.273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2516500.0</td>\n",
       "      <td>110001</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>999992.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>ATIVO</td>\n",
       "      <td>MUNIC</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "      <td>Rondônia</td>\n",
       "      <td>-11.93554</td>\n",
       "      <td>-61.99982</td>\n",
       "      <td>338.0</td>\n",
       "      <td>7067.025</td>\n",
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       "<p>5 rows × 69 columns</p>\n",
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      "text/plain": [
       "   ORIGEM   CODESTAB  CODMUNNASC  LOCNASC  IDADEMAE  ESTCIVMAE  \\\n",
       "0       1  2679477.0      110001        1        19        5.0   \n",
       "1       1  2679477.0      110001        1        29        2.0   \n",
       "2       1  2679477.0      110001        1        37        9.0   \n",
       "3       1  2516500.0      110001        1        30        5.0   \n",
       "4       1  2516500.0      110001        1        30        2.0   \n",
       "\n",
       "            ESCMAE  CODOCUPMAE  QTDFILVIVO  QTDFILMORT  ...  KOTELCHUCK  \\\n",
       "0      8 a 11 anos         NaN         0.0         0.0  ...           5   \n",
       "1      8 a 11 anos    999992.0         1.0         0.0  ...           5   \n",
       "2      8 a 11 anos    513205.0         2.0         0.0  ...           5   \n",
       "3  12 anos ou mais    231205.0         0.0         0.0  ...           4   \n",
       "4      8 a 11 anos    999992.0         1.0         0.0  ...           5   \n",
       "\n",
       "  CONTADOR munResStatus munResTipo               munResNome  munResUf  \\\n",
       "0        1        ATIVO      MUNIC    Alta Floresta D'Oeste  Rondônia   \n",
       "1        2        ATIVO      MUNIC    Alta Floresta D'Oeste  Rondônia   \n",
       "2        3        ATIVO      MUNIC    Alta Floresta D'Oeste  Rondônia   \n",
       "3        4        ATIVO      MUNIC  Alto Alegre dos Parecis  Rondônia   \n",
       "4        5        ATIVO      MUNIC    Alta Floresta D'Oeste  Rondônia   \n",
       "\n",
       "   munResLat munResLon  munResAlt  munResArea  \n",
       "0  -11.93554 -61.99982      338.0    7067.025  \n",
       "1  -11.93554 -61.99982      338.0    7067.025  \n",
       "2  -11.93554 -61.99982      338.0    7067.025  \n",
       "3  -12.13178 -61.85308      397.0    3958.273  \n",
       "4  -11.93554 -61.99982      338.0    7067.025  \n",
       "\n",
       "[5 rows x 69 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinasc_raw = pd.read_csv('SINASC_RO_2019.csv')\n",
    "sinasc_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 27028 entries, 0 to 27027\n",
      "Data columns (total 69 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   ORIGEM        27028 non-null  int64  \n",
      " 1   CODESTAB      26913 non-null  float64\n",
      " 2   CODMUNNASC    27028 non-null  int64  \n",
      " 3   LOCNASC       27028 non-null  int64  \n",
      " 4   IDADEMAE      27028 non-null  int64  \n",
      " 5   ESTCIVMAE     26711 non-null  float64\n",
      " 6   ESCMAE        26716 non-null  object \n",
      " 7   CODOCUPMAE    24121 non-null  float64\n",
      " 8   QTDFILVIVO    25455 non-null  float64\n",
      " 9   QTDFILMORT    24930 non-null  float64\n",
      " 10  CODMUNRES     27028 non-null  int64  \n",
      " 11  GESTACAO      25796 non-null  object \n",
      " 12  GRAVIDEZ      26949 non-null  object \n",
      " 13  PARTO         26979 non-null  object \n",
      " 14  CONSULTAS     27028 non-null  int64  \n",
      " 15  DTNASC        27028 non-null  object \n",
      " 16  HORANASC      27007 non-null  float64\n",
      " 17  SEXO          27024 non-null  object \n",
      " 18  APGAR1        26932 non-null  float64\n",
      " 19  APGAR5        26925 non-null  float64\n",
      " 20  RACACOR       26381 non-null  object \n",
      " 21  PESO          27028 non-null  int64  \n",
      " 22  IDANOMAL      26437 non-null  float64\n",
      " 23  DTCADASTRO    27028 non-null  object \n",
      " 24  CODANOMAL     214 non-null    object \n",
      " 25  NUMEROLOTE    27028 non-null  int64  \n",
      " 26  VERSAOSIST    27028 non-null  object \n",
      " 27  DTRECEBIM     27028 non-null  object \n",
      " 28  DIFDATA       27028 non-null  int64  \n",
      " 29  DTRECORIGA    0 non-null      float64\n",
      " 30  NATURALMAE    26730 non-null  float64\n",
      " 31  CODMUNNATU    26730 non-null  float64\n",
      " 32  CODUFNATU     26730 non-null  float64\n",
      " 33  ESCMAE2010    26779 non-null  float64\n",
      " 34  SERIESCMAE    14318 non-null  float64\n",
      " 35  DTNASCMAE     26988 non-null  float64\n",
      " 36  RACACORMAE    26367 non-null  float64\n",
      " 37  QTDGESTANT    25816 non-null  float64\n",
      " 38  QTDPARTNOR    25149 non-null  float64\n",
      " 39  QTDPARTCES    25237 non-null  float64\n",
      " 40  IDADEPAI      7607 non-null   float64\n",
      " 41  DTULTMENST    16956 non-null  float64\n",
      " 42  SEMAGESTAC    25790 non-null  float64\n",
      " 43  TPMETESTIM    25790 non-null  float64\n",
      " 44  CONSPRENAT    26098 non-null  float64\n",
      " 45  MESPRENAT     24161 non-null  float64\n",
      " 46  TPAPRESENT    26763 non-null  float64\n",
      " 47  STTRABPART    26081 non-null  float64\n",
      " 48  STCESPARTO    26281 non-null  float64\n",
      " 49  TPNASCASSI    26967 non-null  float64\n",
      " 50  TPFUNCRESP    26961 non-null  float64\n",
      " 51  TPDOCRESP     27014 non-null  float64\n",
      " 52  DTDECLARAC    26976 non-null  float64\n",
      " 53  ESCMAEAGR1    26779 non-null  float64\n",
      " 54  STDNEPIDEM    27028 non-null  int64  \n",
      " 55  STDNNOVA      27028 non-null  int64  \n",
      " 56  CODPAISRES    27028 non-null  int64  \n",
      " 57  TPROBSON      27028 non-null  int64  \n",
      " 58  PARIDADE      27028 non-null  int64  \n",
      " 59  KOTELCHUCK    27028 non-null  int64  \n",
      " 60  CONTADOR      27028 non-null  int64  \n",
      " 61  munResStatus  27028 non-null  object \n",
      " 62  munResTipo    27028 non-null  object \n",
      " 63  munResNome    27028 non-null  object \n",
      " 64  munResUf      27028 non-null  object \n",
      " 65  munResLat     27027 non-null  float64\n",
      " 66  munResLon     27027 non-null  float64\n",
      " 67  munResAlt     27027 non-null  float64\n",
      " 68  munResArea    27027 non-null  float64\n",
      "dtypes: float64(38), int64(16), object(15)\n",
      "memory usage: 14.2+ MB\n"
     ]
    }
   ],
   "source": [
    "sinasc_raw.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tarefa 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Idade media das mães e dos pais por município (coluna munResNome)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "      <th>munResNome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>32.0</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Alto Alegre dos Parecis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Alta Floresta D'Oeste</td>\n",
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      ],
      "text/plain": [
       "   IDADEMAE  IDADEPAI               munResNome\n",
       "0        19      26.0    Alta Floresta D'Oeste\n",
       "1        29      24.0    Alta Floresta D'Oeste\n",
       "2        37      32.0    Alta Floresta D'Oeste\n",
       "3        30      24.0  Alto Alegre dos Parecis\n",
       "4        30      27.0    Alta Floresta D'Oeste"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae_pai = sinasc_raw[['IDADEMAE','IDADEPAI','munResNome']]\n",
    "idade_mae_pai.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x00000277FE9E1F70>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae_pai.groupby('munResNome')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>munResNome</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alta Floresta D'Oeste</th>\n",
       "      <td>25.991826</td>\n",
       "      <td>29.548701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Alegre dos Parecis</th>\n",
       "      <td>24.844156</td>\n",
       "      <td>29.179104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Paraíso</th>\n",
       "      <td>24.960177</td>\n",
       "      <td>28.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alvorada D'Oeste</th>\n",
       "      <td>25.770732</td>\n",
       "      <td>30.757282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ariquemes</th>\n",
       "      <td>25.607866</td>\n",
       "      <td>32.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buritis</th>\n",
       "      <td>25.559177</td>\n",
       "      <td>30.812500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabixi</th>\n",
       "      <td>26.037500</td>\n",
       "      <td>34.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cacaulândia</th>\n",
       "      <td>25.546667</td>\n",
       "      <td>36.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cacoal</th>\n",
       "      <td>26.890102</td>\n",
       "      <td>30.931854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Campo Novo de Rondônia</th>\n",
       "      <td>24.825301</td>\n",
       "      <td>30.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Candeias do Jamari</th>\n",
       "      <td>25.243323</td>\n",
       "      <td>29.894737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Castanheiras</th>\n",
       "      <td>27.281250</td>\n",
       "      <td>30.392857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cerejeiras</th>\n",
       "      <td>27.240506</td>\n",
       "      <td>31.652778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chupinguaia</th>\n",
       "      <td>25.333333</td>\n",
       "      <td>29.629630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado do Oeste</th>\n",
       "      <td>27.602804</td>\n",
       "      <td>34.354839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Corumbiara</th>\n",
       "      <td>24.716535</td>\n",
       "      <td>32.470588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Costa Marques</th>\n",
       "      <td>24.412017</td>\n",
       "      <td>30.613636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cujubim</th>\n",
       "      <td>24.482927</td>\n",
       "      <td>31.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Espigão D'Oeste</th>\n",
       "      <td>26.093333</td>\n",
       "      <td>31.198113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Governador Jorge Teixeira</th>\n",
       "      <td>24.401786</td>\n",
       "      <td>29.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Guajará-Mirim</th>\n",
       "      <td>25.462228</td>\n",
       "      <td>30.470588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Itapuã do Oeste</th>\n",
       "      <td>26.064220</td>\n",
       "      <td>42.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jaru</th>\n",
       "      <td>25.982974</td>\n",
       "      <td>32.197183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ji-Paraná</th>\n",
       "      <td>26.361137</td>\n",
       "      <td>31.132239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Machadinho D'Oeste</th>\n",
       "      <td>25.480000</td>\n",
       "      <td>31.326923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ministro Andreazza</th>\n",
       "      <td>27.904762</td>\n",
       "      <td>33.849315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mirante da Serra</th>\n",
       "      <td>26.304878</td>\n",
       "      <td>32.154762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monte Negro</th>\n",
       "      <td>25.648241</td>\n",
       "      <td>34.678571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Município ignorado - RO</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nova Brasilândia D'Oeste</th>\n",
       "      <td>26.222222</td>\n",
       "      <td>30.520833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nova Mamoré</th>\n",
       "      <td>25.326389</td>\n",
       "      <td>31.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nova União</th>\n",
       "      <td>26.894231</td>\n",
       "      <td>31.371429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Novo Horizonte do Oeste</th>\n",
       "      <td>26.938776</td>\n",
       "      <td>31.588235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ouro Preto do Oeste</th>\n",
       "      <td>26.375594</td>\n",
       "      <td>31.233244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parecis</th>\n",
       "      <td>26.454545</td>\n",
       "      <td>32.473684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pimenta Bueno</th>\n",
       "      <td>25.199675</td>\n",
       "      <td>29.745174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pimenteiras do Oeste</th>\n",
       "      <td>25.075000</td>\n",
       "      <td>35.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porto Velho</th>\n",
       "      <td>26.312670</td>\n",
       "      <td>32.352679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Presidente Médici</th>\n",
       "      <td>25.796053</td>\n",
       "      <td>30.150754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Primavera de Rondônia</th>\n",
       "      <td>27.023256</td>\n",
       "      <td>31.888889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rio Crespo</th>\n",
       "      <td>26.660000</td>\n",
       "      <td>28.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rolim de Moura</th>\n",
       "      <td>26.600863</td>\n",
       "      <td>30.360479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Santa Luzia D'Oeste</th>\n",
       "      <td>26.121212</td>\n",
       "      <td>30.703297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seringueiras</th>\n",
       "      <td>24.910714</td>\n",
       "      <td>30.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>São Felipe D'Oeste</th>\n",
       "      <td>26.481481</td>\n",
       "      <td>31.395833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>São Francisco do Guaporé</th>\n",
       "      <td>25.660066</td>\n",
       "      <td>31.638889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>São Miguel do Guaporé</th>\n",
       "      <td>25.926346</td>\n",
       "      <td>32.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Teixeirópolis</th>\n",
       "      <td>26.031250</td>\n",
       "      <td>31.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Theobroma</th>\n",
       "      <td>25.536082</td>\n",
       "      <td>30.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Urupá</th>\n",
       "      <td>26.688235</td>\n",
       "      <td>31.008929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vale do Anari</th>\n",
       "      <td>26.096774</td>\n",
       "      <td>34.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vale do Paraíso</th>\n",
       "      <td>25.679012</td>\n",
       "      <td>29.976744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vilhena</th>\n",
       "      <td>26.433962</td>\n",
       "      <td>34.152941</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            IDADEMAE   IDADEPAI\n",
       "munResNome                                     \n",
       "Alta Floresta D'Oeste      25.991826  29.548701\n",
       "Alto Alegre dos Parecis    24.844156  29.179104\n",
       "Alto Paraíso               24.960177  28.833333\n",
       "Alvorada D'Oeste           25.770732  30.757282\n",
       "Ariquemes                  25.607866  32.466667\n",
       "Buritis                    25.559177  30.812500\n",
       "Cabixi                     26.037500  34.333333\n",
       "Cacaulândia                25.546667  36.333333\n",
       "Cacoal                     26.890102  30.931854\n",
       "Campo Novo de Rondônia     24.825301  30.500000\n",
       "Candeias do Jamari         25.243323  29.894737\n",
       "Castanheiras               27.281250  30.392857\n",
       "Cerejeiras                 27.240506  31.652778\n",
       "Chupinguaia                25.333333  29.629630\n",
       "Colorado do Oeste          27.602804  34.354839\n",
       "Corumbiara                 24.716535  32.470588\n",
       "Costa Marques              24.412017  30.613636\n",
       "Cujubim                    24.482927  31.400000\n",
       "Espigão D'Oeste            26.093333  31.198113\n",
       "Governador Jorge Teixeira  24.401786  29.222222\n",
       "Guajará-Mirim              25.462228  30.470588\n",
       "Itapuã do Oeste            26.064220  42.500000\n",
       "Jaru                       25.982974  32.197183\n",
       "Ji-Paraná                  26.361137  31.132239\n",
       "Machadinho D'Oeste         25.480000  31.326923\n",
       "Ministro Andreazza         27.904762  33.849315\n",
       "Mirante da Serra           26.304878  32.154762\n",
       "Monte Negro                25.648241  34.678571\n",
       "Município ignorado - RO    24.000000  22.000000\n",
       "Nova Brasilândia D'Oeste   26.222222  30.520833\n",
       "Nova Mamoré                25.326389  31.692308\n",
       "Nova União                 26.894231  31.371429\n",
       "Novo Horizonte do Oeste    26.938776  31.588235\n",
       "Ouro Preto do Oeste        26.375594  31.233244\n",
       "Parecis                    26.454545  32.473684\n",
       "Pimenta Bueno              25.199675  29.745174\n",
       "Pimenteiras do Oeste       25.075000  35.600000\n",
       "Porto Velho                26.312670  32.352679\n",
       "Presidente Médici          25.796053  30.150754\n",
       "Primavera de Rondônia      27.023256  31.888889\n",
       "Rio Crespo                 26.660000  28.000000\n",
       "Rolim de Moura             26.600863  30.360479\n",
       "Santa Luzia D'Oeste        26.121212  30.703297\n",
       "Seringueiras               24.910714  30.500000\n",
       "São Felipe D'Oeste         26.481481  31.395833\n",
       "São Francisco do Guaporé   25.660066  31.638889\n",
       "São Miguel do Guaporé      25.926346  32.666667\n",
       "Teixeirópolis              26.031250  31.500000\n",
       "Theobroma                  25.536082  30.083333\n",
       "Urupá                      26.688235  31.008929\n",
       "Vale do Anari              26.096774  34.000000\n",
       "Vale do Paraíso            25.679012  29.976744\n",
       "Vilhena                    26.433962  34.152941"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae_pai.groupby('munResNome').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>ESCMAE</th>\n",
       "      <th>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>19</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>29</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>37</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12 anos ou mais</td>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>30</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27023</th>\n",
       "      <td>12 anos ou mais</td>\n",
       "      <td>32</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27024</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27025</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>24</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27026</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>21</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27027</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27028 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                ESCMAE  IDADEMAE  IDADEPAI\n",
       "0          8 a 11 anos        19      26.0\n",
       "1          8 a 11 anos        29      24.0\n",
       "2          8 a 11 anos        37      32.0\n",
       "3      12 anos ou mais        30      24.0\n",
       "4          8 a 11 anos        30      27.0\n",
       "...                ...       ...       ...\n",
       "27023  12 anos ou mais        32      35.0\n",
       "27024      8 a 11 anos        19       NaN\n",
       "27025      8 a 11 anos        24      30.0\n",
       "27026      8 a 11 anos        21      24.0\n",
       "27027      8 a 11 anos        18       NaN\n",
       "\n",
       "[27028 rows x 3 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esc_mae = sinasc_raw[['ESCMAE','IDADEMAE','IDADEPAI']]\n",
    "\n",
    "esc_mae.groupby('ESCMAE').mean()\n",
    "esc_mae"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Owamashi\\AppData\\Local\\Temp\\ipykernel_16204\\2293000583.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  esc_mae['DIF'] = esc_mae['IDADEMAE'] - esc_mae['IDADEPAI']\n"
     ]
    },
    {
     "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>ESCMAE</th>\n",
       "      <th>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "      <th>DIF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>19</td>\n",
       "      <td>26.0</td>\n",
       "      <td>-7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>29</td>\n",
       "      <td>24.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>37</td>\n",
       "      <td>32.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12 anos ou mais</td>\n",
       "      <td>30</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8 a 11 anos</td>\n",
       "      <td>30</td>\n",
       "      <td>27.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ESCMAE  IDADEMAE  IDADEPAI  DIF\n",
       "0      8 a 11 anos        19      26.0 -7.0\n",
       "1      8 a 11 anos        29      24.0  5.0\n",
       "2      8 a 11 anos        37      32.0  5.0\n",
       "3  12 anos ou mais        30      24.0  6.0\n",
       "4      8 a 11 anos        30      27.0  3.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esc_mae['DIF'] = esc_mae['IDADEMAE'] - esc_mae['IDADEPAI']\n",
    "esc_mae.sort_values('DIF')\n",
    "esc_mae.head(5)\n",
    "\n",
    "#sei lá, eu tentei fazer isso aqui e piorei eu acho kkk "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>DTNASC</th>\n",
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       "    <tr>\n",
       "      <th>ESCMAE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1 a 3 anos</th>\n",
       "      <td>516</td>\n",
       "      <td>516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12 anos ou mais</th>\n",
       "      <td>5767</td>\n",
       "      <td>5767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4 a 7 anos</th>\n",
       "      <td>4760</td>\n",
       "      <td>4760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8 a 11 anos</th>\n",
       "      <td>15633</td>\n",
       "      <td>15633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nenhuma</th>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 DTNASC  IDADEMAE\n",
       "ESCMAE                           \n",
       "1 a 3 anos          516       516\n",
       "12 anos ou mais    5767      5767\n",
       "4 a 7 anos         4760      4760\n",
       "8 a 11 anos       15633     15633\n",
       "Nenhuma              40        40"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_nasc_esc = sinasc_raw[['DTNASC','IDADEMAE','ESCMAE']]\n",
    "\n",
    "dt_nasc_esc.groupby('ESCMAE').count()\n",
    "\n",
    "#eu fiz só por curiosidade mas me deu uma dúvida, porque o DTNASC e IDADEMAE deu o mesmo resultado?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(27028, 3)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae_pai.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19421"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae_pai.IDADEPAI.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7185511321592423"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "19421/27028"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>munResNome</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alta Floresta D'Oeste</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Alegre dos Parecis</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Paraíso</th>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alvorada D'Oeste</th>\n",
       "      <td>26.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ariquemes</th>\n",
       "      <td>28.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         IDADEMAE  IDADEPAI\n",
       "munResNome                                 \n",
       "Alta Floresta D'Oeste        25.0      28.5\n",
       "Alto Alegre dos Parecis      25.0      28.0\n",
       "Alto Paraíso                 22.5      25.5\n",
       "Alvorada D'Oeste             26.0      31.0\n",
       "Ariquemes                    28.0      29.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = idade_mae_pai.dropna().groupby('munResNome').median()\n",
    "result.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Eu fiz os mesmos codigos da aula para ver se era igual "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "      <th>DIF</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>munResNome</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alta Floresta D'Oeste</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Alegre dos Parecis</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Paraíso</th>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alvorada D'Oeste</th>\n",
       "      <td>26.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ariquemes</th>\n",
       "      <td>28.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         IDADEMAE  IDADEPAI  DIF\n",
       "munResNome                                      \n",
       "Alta Floresta D'Oeste        25.0      28.5  3.5\n",
       "Alto Alegre dos Parecis      25.0      28.0  3.0\n",
       "Alto Paraíso                 22.5      25.5  3.0\n",
       "Alvorada D'Oeste             26.0      31.0  5.0\n",
       "Ariquemes                    28.0      29.0  1.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#com coluna DIF\n",
    "\n",
    "result['DIF'] = result['IDADEPAI'] - result['IDADEMAE']\n",
    "result.sort_values('DIF')\n",
    "result.head(5)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>IDADEMAE</th>\n",
       "      <th>IDADEPAI</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>munResNome</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alta Floresta D'Oeste</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Alegre dos Parecis</th>\n",
       "      <td>25.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alto Paraíso</th>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alvorada D'Oeste</th>\n",
       "      <td>26.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ariquemes</th>\n",
       "      <td>28.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         IDADEMAE  IDADEPAI\n",
       "munResNome                                 \n",
       "Alta Floresta D'Oeste        25.0      28.5\n",
       "Alto Alegre dos Parecis      25.0      28.0\n",
       "Alto Paraíso                 22.5      25.5\n",
       "Alvorada D'Oeste             26.0      31.0\n",
       "Ariquemes                    28.0      29.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SEM COLUNA DIF PARA PLOTAR\n",
    "result_1 = idade_mae_pai.dropna().groupby('munResNome').median()\n",
    "result_1.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Eu queria fazer um plot para visualização, mas quando fiz isso a coluna 'munResNome' ficou poluindo demais com suas variaveis gigantes, Então eu procurei uma função para aprender como deixar\n",
    "#tudo em sigla, para ao menos ter o nome da coluna munResNome. ESSE codigo não foi exatamente meu, mas tive interesse de implementar ele para aprender \n",
    "\n",
    "\n",
    "def criar_siglas(nome):\n",
    "    return ''.join([palavra[0] for palavra in nome.split()]).upper()\n",
    "\n",
    "\n",
    "sinasc_grouped = result_1.groupby('munResNome').mean()\n",
    "sinasc_grouped.index = sinasc_grouped.index.to_series().apply(criar_siglas)\n",
    "\n",
    "sinasc_grouped.plot(figsize=[15,8])\n",
    "plt.xlabel('Municípios (Siglas)')\n",
    "plt.xticks(rotation=90)  \n",
    "plt.show()\n",
    "\n",
    "\n",
    "# se houver outro metodo que não haja necessidade de criar uma função, quando forem corrigir essa tarefa, poderiam me dizer?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Peso médio dos bebes por sexo que nasceram no dia do seu aniversário por faixas de escolaridade mae\n",
    "Ex: Você, aluna(o), nasceu no dia 10/01, então você precisa filtrar o conjunto de dados nessa data e calcular o peso médio dos bebês de cada sexo por faixa de escolaridade da mãe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: PESO, dtype: float64)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#utilizando o loc para encontrar a data de nascimento  iguais a minha\n",
    "\n",
    "sinasc_raw_filtrado = sinasc_raw.loc[sinasc_raw['DTNASC'] == '2019/09/26']\n",
    "sinasc_raw_filtrado.groupby(['SEXO','ESCMAE'])['PESO'].mean()    \n",
    "#utilizando groupby para juntar as colunas e fazer a media, mas ainda não entendi bem pq o ['PESO'] fica fora e não pode ficar dentro: ('SEXO','ESCMAE','PESO')?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#utilizando o pd.datetime para fazer a mesma coisa  que o loc mas o que é esse errors = 'coerce'?\n",
    "#sinasc_raw['DTNASC'] = pd.to_datetime(sinasc_raw['DTNASC'], errors='coerce')\n",
    "\n",
    "#filtered_data = sinasc_raw[sinasc_raw['DTNASC'].dt.month == 9] \n",
    "#filtered_data = filtered_data[filtered_data['DTNASC'].dt.day == 26]\n",
    "\n",
    "#peso_medio = filtered_data.groupby(['SEXO', 'ESCMAE'])['PESO'].mean()\n",
    "#peso_medio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Qual o municipio que nasceu menos bebe em 2019?\n",
    "    - qual a idade media, maxima, minima das maes nesse municipio?\n",
    "    - qual a idade media, maxima, minima dos pais nesse municipio?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sinasc = sinasc_raw[[\n",
    "    'IDADEMAE', 'SEXO', 'APGAR1', 'APGAR5', 'PESO', 'CONSULTAS', 'DTNASC',\n",
    "    'GESTACAO', 'GRAVIDEZ', 'ESCMAE', 'IDADEPAI','munResNome'\n",
    "]].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "nascimento_por_municipio = sinasc.groupby('munResNome')['DTNASC'].count()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O município com menos nascimentos é: Município ignorado - RO, com 1 nascimentos.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Quantidade de Nascimentos')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nascimento_por_municipio = sinasc.groupby('munResNome')['DTNASC'].count()\n",
    "\n",
    "menor_nascimentos = nascimento_por_municipio.min()\n",
    "municipio_menos_nascimentos = nascimento_por_municipio[nascimento_por_municipio == menor_nascimentos].index[0]\n",
    "\n",
    "\n",
    "\n",
    "print(f'O município com menos nascimentos é: {municipio_menos_nascimentos}, com {menor_nascimentos} nascimentos.')\n",
    "\n",
    "nascimento_por_municipio.plot(kind='bar', figsize=(12, 3))\n",
    "\n",
    "plt.title('Quantidade de Nascimentos por Município em 2019')\n",
    "plt.xlabel('Município')\n",
    "plt.ylabel('Quantidade de Nascimentos')\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "municipio_especifico = 'Porto Velho'\n",
    "dados_municipio = sinasc_raw[sinasc_raw['munResNome'] == municipio_especifico]\n",
    "\n",
    "idade_mae = dados_municipio['IDADEMAE'].agg(['mean', 'min', 'max'])\n",
    "\n",
    "idade_pai = dados_municipio['IDADEPAI'].dropna().agg(['mean', 'min', 'max'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>IDADEMAE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>26.31267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>12.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>47.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      IDADEMAE\n",
       "mean  26.31267\n",
       "min   12.00000\n",
       "max   47.00000"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mae = pd.DataFrame(idade_mae)\n",
    "\n",
    "df_mae"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>IDADEPAI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>32.352679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>65.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       IDADEPAI\n",
       "mean  32.352679\n",
       "min   16.000000\n",
       "max   65.000000"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_pai = dados_municipio['IDADEPAI'].dropna().agg(['mean', 'min', 'max'])\n",
    "df_pai = pd.DataFrame(idade_pai) \n",
    "df_pai"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Qual o municipio que nasceu mais bebe no mês de março?\n",
    "    - qual a quantidade de filhos vivos media, maxima, minima nesse municipio?\n",
    "    - qual a idade media, maxima, minima dos pais nesse municipio?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "munResNome\n",
       "Porto Velho    744\n",
       "Ji-Paraná      188\n",
       "Vilhena        148\n",
       "Ariquemes      141\n",
       "Cacoal         133\n",
       "Name: DTNASC, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sinasc_raw['DTNASC'] = pd.to_datetime(sinasc_raw['DTNASC'], errors='coerce')\n",
    "\n",
    "# Filtrar os dados para o mês de março\n",
    "filtered_data = sinasc_raw[sinasc_raw['DTNASC'].dt.month == 3]\n",
    "\n",
    "# Agrupar por município e contar o número de nascimentos\n",
    "nascimentos_de_marco= filtered_data.groupby('munResNome')['DTNASC'].count()\n",
    "nascimentos_ordenados = nascimentos_de_marco.sort_values(ascending=False)\n",
    "\n",
    "nascimentos_ordenados.head(5)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Porto Velho foi o município que teve mais nascimentos, com um total de 744 nascimentos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mean     1.167236\n",
       "min      0.000000\n",
       "max     12.000000\n",
       "Name: QTDFILVIVO, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filhos_vivos= dados_municipio['QTDFILVIVO'].agg(['mean', 'min', 'max'])\n",
    "filhos_vivos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mean    32.352679\n",
       "min     16.000000\n",
       "max     65.000000\n",
       "Name: IDADEPAI, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_pai= dados_municipio['IDADEPAI'].agg(['mean', 'min', 'max'])\n",
    "idade_pai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mean    26.31267\n",
       "min     12.00000\n",
       "max     47.00000\n",
       "Name: IDADEMAE, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idade_mae= dados_municipio['IDADEMAE'].agg(['mean', 'min', 'max'])\n",
    "idade_mae\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    ### Analise as respostas encontradas, tire algum insight delas, conte pra gente algo encontrado nos dados. Algo que você julgue relevante e novo pra você."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exemplo:\n",
    "- Ah, descobri que a idade mediana das mulheres que deram a luz no ano de 2019 dos municipios x é maior que y."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Porto Velho foi o município que teve mais nascimentos, com um total de 744 nascimentos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O município com menos nascimentos foi o  Município ignorado - RO, com 1 nascimentos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O município com menos nascimentos em 2019 pode indicar uma área com menor densidade populacional ou acesso limitado a serviços de saúde reprodutiva."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Diferença na Idade dos Pais e Mães, tem uma diferença significativa,podendo ser variados casos para esse ocorrido."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " A escolaridade da mãe influenciou em novos nascimentos, assim como também na IDADEPAI."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " O PAI Sempre é mais velho que a MÃE.\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A idade minima da mãe foi de supreendentes 12 e dos pais de 16."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A média de filhos vivos por mãe no município com mais nascimentos pode indicar uma tendência local de famílias maiores, o que pode impactar os serviços de saúde e educação."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Grande parte dos nascimentos acontecidos em porto velho, pode ser resultado de serviços de saúde melhores e infraestrutura."
   ]
  }
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