{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Groupby\n",
    "\n",
    "O método groupby permite agrupar linhas de dados em conjunto e chamar funções agregadas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# Cria um DataFrame\n",
    "data = {'Empresa':['GOOG','GOOG','MSFT','MSFT','FB','FB'],\n",
    "       'Nome':['Sam','Charlie','Amy','Vanessa','Carl','Sarah'],\n",
    "       'Venda':[200,120,340,124,243,350]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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",
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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>Empresa</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>Sam</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>Charlie</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>Amy</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>Vanessa</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FB</td>\n",
       "      <td>Carl</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>FB</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Empresa     Nome  Venda\n",
       "0    GOOG      Sam    200\n",
       "1    GOOG  Charlie    120\n",
       "2    MSFT      Amy    340\n",
       "3    MSFT  Vanessa    124\n",
       "4      FB     Carl    243\n",
       "5      FB    Sarah    350"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Agora, você pode usar o método .group by () para agrupar as linhas em conjunto com base em um nome de coluna. Por exemplo, vamos agrupar com base na empresa. Isso criará um objeto DataFrameGroupBy:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x109e63d00>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Empresa')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Você pode salvar este objeto como uma nova variável:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "por_companhia = df.groupby(\"Empresa\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "E, em seguida, chamar métodos agregados do objeto:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>296.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>232.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Venda\n",
       "Empresa       \n",
       "FB       296.5\n",
       "GOOG     160.0\n",
       "MSFT     232.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "por_companhia.mean()\n",
    "#retorna a média dos agrupamentos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>296.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>232.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Venda\n",
       "Empresa       \n",
       "FB       296.5\n",
       "GOOG     160.0\n",
       "MSFT     232.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Empresa').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mais exemplos de métodos agregados:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>75.660426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>56.568542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>152.735065</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Venda\n",
       "Empresa            \n",
       "FB        75.660426\n",
       "GOOG      56.568542\n",
       "MSFT     152.735065"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retorna o desvio padrão\n",
    "por_companhia.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>Carl</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>Charlie</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>Amy</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Nome  Venda\n",
       "Empresa                \n",
       "FB          Carl    243\n",
       "GOOG     Charlie    120\n",
       "MSFT         Amy    124"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retorna o menor valor\n",
    "por_companhia.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>Sam</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>Vanessa</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Nome  Venda\n",
       "Empresa                \n",
       "FB         Sarah    350\n",
       "GOOG         Sam    200\n",
       "MSFT     Vanessa    340"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retorna o maior valor\n",
    "por_companhia.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nome</th>\n",
       "      <th>Venda</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Nome  Venda\n",
       "Empresa             \n",
       "FB          2      2\n",
       "GOOG        2      2\n",
       "MSFT        2      2"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# contagem por agrupamento\n",
    "por_companhia.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Venda</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empresa</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>2.0</td>\n",
       "      <td>296.5</td>\n",
       "      <td>75.660426</td>\n",
       "      <td>243.0</td>\n",
       "      <td>269.75</td>\n",
       "      <td>296.5</td>\n",
       "      <td>323.25</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>2.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>56.568542</td>\n",
       "      <td>120.0</td>\n",
       "      <td>140.00</td>\n",
       "      <td>160.0</td>\n",
       "      <td>180.00</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT</th>\n",
       "      <td>2.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>152.735065</td>\n",
       "      <td>124.0</td>\n",
       "      <td>178.00</td>\n",
       "      <td>232.0</td>\n",
       "      <td>286.00</td>\n",
       "      <td>340.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Venda                                                        \n",
       "        count   mean         std    min     25%    50%     75%    max\n",
       "Empresa                                                              \n",
       "FB        2.0  296.5   75.660426  243.0  269.75  296.5  323.25  350.0\n",
       "GOOG      2.0  160.0   56.568542  120.0  140.00  160.0  180.00  200.0\n",
       "MSFT      2.0  232.0  152.735065  124.0  178.00  232.0  286.00  340.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# detalhamento estatístico por agrupamento\n",
    "por_companhia.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">Venda</th>\n",
       "      <th>count</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>296.500000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>232.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>75.660426</td>\n",
       "      <td>56.568542</td>\n",
       "      <td>152.735065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>243.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>124.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>269.750000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>178.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>296.500000</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>232.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>323.250000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>286.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>350.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>340.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empresa              FB        GOOG        MSFT\n",
       "Venda count    2.000000    2.000000    2.000000\n",
       "      mean   296.500000  160.000000  232.000000\n",
       "      std     75.660426   56.568542  152.735065\n",
       "      min    243.000000  120.000000  124.000000\n",
       "      25%    269.750000  140.000000  178.000000\n",
       "      50%    296.500000  160.000000  232.000000\n",
       "      75%    323.250000  180.000000  286.000000\n",
       "      max    350.000000  200.000000  340.000000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reordenação do detalhamento estatístico\n",
    "por_companhia.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Venda  count      2.000000\n",
       "       mean     160.000000\n",
       "       std       56.568542\n",
       "       min      120.000000\n",
       "       25%      140.000000\n",
       "       50%      160.000000\n",
       "       75%      180.000000\n",
       "       max      200.000000\n",
       "Name: GOOG, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "por_companhia.describe().transpose()['GOOG']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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