7_analise_exploratoria.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8ebe07c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importando bibliotecas\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#Mudando estilo dos gráficos\n",
    "plt.style.use(\"seaborn-v0_8-notebook\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ff1ccb95",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Caso utilize google colab, para fazer upload de arquivo, também é possível utilizar a biblioteca google.colab:\n",
    "#from google.colab import files\n",
    "#arq = files.upload()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3ead3f8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lendo arquivo excel em dataframe:\n",
    "df = pd.read_excel(\"datasets\\\\AdventureWorks.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1daa129c",
   "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>Data Venda</th>\n",
       "      <th>Data Envio</th>\n",
       "      <th>ID Loja</th>\n",
       "      <th>ID Produto</th>\n",
       "      <th>ID Cliente</th>\n",
       "      <th>No. Venda</th>\n",
       "      <th>Custo Unitário</th>\n",
       "      <th>Preço Unitário</th>\n",
       "      <th>Quantidade</th>\n",
       "      <th>Valor Desconto</th>\n",
       "      <th>Valor Venda</th>\n",
       "      <th>Produto</th>\n",
       "      <th>Fabricante</th>\n",
       "      <th>Marca</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Cor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-05-09</td>\n",
       "      <td>2008-05-29</td>\n",
       "      <td>199</td>\n",
       "      <td>384</td>\n",
       "      <td>18839</td>\n",
       "      <td>200805093CS607</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4548.0</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008-05-12</td>\n",
       "      <td>2008-05-17</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19051</td>\n",
       "      <td>200805123CS567</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4548.0</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008-05-14</td>\n",
       "      <td>2008-05-20</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19052</td>\n",
       "      <td>200805143CS576</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4548.0</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008-05-21</td>\n",
       "      <td>2008-05-27</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19052</td>\n",
       "      <td>200805213CS576</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4548.0</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2008-06-20</td>\n",
       "      <td>2008-06-27</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19053</td>\n",
       "      <td>200806203CS586</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4548.0</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Data Venda Data Envio  ID Loja  ID Produto  ID Cliente       No. Venda  \\\n",
       "0 2008-05-09 2008-05-29      199         384       18839  200805093CS607   \n",
       "1 2008-05-12 2008-05-17      306         384       19051  200805123CS567   \n",
       "2 2008-05-14 2008-05-20      306         384       19052  200805143CS576   \n",
       "3 2008-05-21 2008-05-27      306         384       19052  200805213CS576   \n",
       "4 2008-06-20 2008-06-27      306         384       19053  200806203CS586   \n",
       "\n",
       "   Custo Unitário  Preço Unitário  Quantidade  Valor Desconto  Valor Venda  \\\n",
       "0          348.58           758.0           6             0.0       4548.0   \n",
       "1          348.58           758.0           6             0.0       4548.0   \n",
       "2          348.58           758.0           6             0.0       4548.0   \n",
       "3          348.58           758.0           6             0.0       4548.0   \n",
       "4          348.58           758.0           6             0.0       4548.0   \n",
       "\n",
       "                                 Produto       Fabricante            Marca  \\\n",
       "0  Adventure Works Laptop15.4W M1548 Red  Adventure Works  Adventure Works   \n",
       "1  Adventure Works Laptop15.4W M1548 Red  Adventure Works  Adventure Works   \n",
       "2  Adventure Works Laptop15.4W M1548 Red  Adventure Works  Adventure Works   \n",
       "3  Adventure Works Laptop15.4W M1548 Red  Adventure Works  Adventure Works   \n",
       "4  Adventure Works Laptop15.4W M1548 Red  Adventure Works  Adventure Works   \n",
       "\n",
       "    Classe  Cor  \n",
       "0  Regular  Red  \n",
       "1  Regular  Red  \n",
       "2  Regular  Red  \n",
       "3  Regular  Red  \n",
       "4  Regular  Red  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Visualizando 5 primeiras linhas:\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "258b6875",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(904, 16)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Quantidade de linhas e colunas:\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e080114a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda        datetime64[ns]\n",
       "Data Envio        datetime64[ns]\n",
       "ID Loja                    int64\n",
       "ID Produto                 int64\n",
       "ID Cliente                 int64\n",
       "No. Venda                 object\n",
       "Custo Unitário           float64\n",
       "Preço Unitário           float64\n",
       "Quantidade                 int64\n",
       "Valor Desconto           float64\n",
       "Valor Venda              float64\n",
       "Produto                   object\n",
       "Fabricante                object\n",
       "Marca                     object\n",
       "Classe                    object\n",
       "Cor                       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Verificando os tipos de dados:\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b7227f63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5984606.1426"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Qual a receita total?\n",
    "df[\"Valor Venda\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c480541c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Custo?\n",
    "#Custo Unitário x Quantidade:\n",
    "df[\"custo\"] = df[\"Custo Unitário\"] * df[\"Quantidade\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ada75f70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2486783.05"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Custo total arredondado\n",
    "round(df[\"custo\"].sum(), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c620013a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lucro?\n",
    "#Receita - custo\n",
    "df[\"lucro\"] = df[\"Valor Venda\"] - df[\"custo\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ca338e9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3497823.09"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lucro total arredondado\n",
    "round(df[\"lucro\"].sum(), 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "acd62ef4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Tempo para envio:\n",
    "df[\"tempo_envio\"] = df[\"Data Envio\"] - df[\"Data Venda\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "eab7c136",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda         datetime64[ns]\n",
       "Data Envio         datetime64[ns]\n",
       "ID Loja                     int64\n",
       "ID Produto                  int64\n",
       "ID Cliente                  int64\n",
       "No. Venda                  object\n",
       "Custo Unitário            float64\n",
       "Preço Unitário            float64\n",
       "Quantidade                  int64\n",
       "Valor Desconto            float64\n",
       "Valor Venda               float64\n",
       "Produto                    object\n",
       "Fabricante                 object\n",
       "Marca                      object\n",
       "Classe                     object\n",
       "Cor                        object\n",
       "custo                     float64\n",
       "lucro                     float64\n",
       "tempo_envio       timedelta64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f83fe5aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Verifica-se que o tempo_envio tem tipo timedelta, e não inteiro. Para acessar o valor inteiro\n",
    "#pode-se usar dt.days por exemplo. Ou pode-se criar a coluna já em dt.days para que ela seja inteiro:\n",
    "df[\"tempo_envio\"] = (df[\"Data Envio\"] - df[\"Data Venda\"]).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a9005827",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda        datetime64[ns]\n",
       "Data Envio        datetime64[ns]\n",
       "ID Loja                    int64\n",
       "ID Produto                 int64\n",
       "ID Cliente                 int64\n",
       "No. Venda                 object\n",
       "Custo Unitário           float64\n",
       "Preço Unitário           float64\n",
       "Quantidade                 int64\n",
       "Valor Desconto           float64\n",
       "Valor Venda              float64\n",
       "Produto                   object\n",
       "Fabricante                object\n",
       "Marca                     object\n",
       "Classe                    object\n",
       "Cor                       object\n",
       "custo                    float64\n",
       "lucro                    float64\n",
       "tempo_envio                int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ef01ff81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Marca\n",
       "Adventure Works    8.663866\n",
       "Contoso            8.470930\n",
       "Fabrikam           8.510121\n",
       "Name: tempo_envio, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Média de tempo de envio por marca:\n",
    "df.groupby(\"Marca\")[\"tempo_envio\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "23c3df72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda        0\n",
       "Data Envio        0\n",
       "ID Loja           0\n",
       "ID Produto        0\n",
       "ID Cliente        0\n",
       "No. Venda         0\n",
       "Custo Unitário    0\n",
       "Preço Unitário    0\n",
       "Quantidade        0\n",
       "Valor Desconto    0\n",
       "Valor Venda       0\n",
       "Produto           0\n",
       "Fabricante        0\n",
       "Marca             0\n",
       "Classe            0\n",
       "Cor               0\n",
       "custo             0\n",
       "lucro             0\n",
       "tempo_envio       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Tem valores ausentes?\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ea97605a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda  Marca          \n",
       "2008        Adventure Works    3.066412e+05\n",
       "            Contoso            5.641600e+04\n",
       "            Fabrikam           1.557021e+06\n",
       "2009        Adventure Works    4.053951e+05\n",
       "            Contoso            1.382590e+05\n",
       "            Fabrikam           1.034091e+06\n",
       "Name: lucro, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Lucro por ano e por marca:\n",
    "df.groupby([df[\"Data Venda\"].dt.year, \"Marca\"])[\"lucro\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6dff35db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda  Marca          \n",
       "2008        Adventure Works             306,641.16\n",
       "            Contoso                      56,416.00\n",
       "            Fabrikam                  1,557,020.55\n",
       "2009        Adventure Works             405,395.08\n",
       "            Contoso                     138,258.95\n",
       "            Fabrikam                  1,034,091.35\n",
       "Name: lucro, dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Mudando os números de notação científica para arredondamento em duas casas:\n",
    "pd.options.display.float_format = '{:20,.2f}'.format\n",
    "df.groupby([df[\"Data Venda\"].dt.year, \"Marca\"])[\"lucro\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9c6d9a8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Resetando o index para criar um dataframe a partir de dados agrupados:\n",
    "lucro_ano = df.groupby([df[\"Data Venda\"].dt.year, \"Marca\"])[\"lucro\"].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c1362cc9",
   "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>Data Venda</th>\n",
       "      <th>Marca</th>\n",
       "      <th>lucro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>306,641.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008</td>\n",
       "      <td>Contoso</td>\n",
       "      <td>56,416.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008</td>\n",
       "      <td>Fabrikam</td>\n",
       "      <td>1,557,020.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>405,395.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>Contoso</td>\n",
       "      <td>138,258.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2009</td>\n",
       "      <td>Fabrikam</td>\n",
       "      <td>1,034,091.35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Data Venda            Marca                lucro\n",
       "0        2008  Adventure Works           306,641.16\n",
       "1        2008          Contoso            56,416.00\n",
       "2        2008         Fabrikam         1,557,020.55\n",
       "3        2009  Adventure Works           405,395.08\n",
       "4        2009          Contoso           138,258.95\n",
       "5        2009         Fabrikam         1,034,091.35"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lucro_ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "10835971",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Produto\n",
       "Headphone Adapter for Contoso Phone E130 Silver    25232\n",
       "Headphone Adapter for Contoso Phone E130 White     25008\n",
       "Adventure Works Laptop15.4W M1548 Black             1089\n",
       "Fabrikam Trendsetter 2/3'' 17mm X100 Grey           1087\n",
       "Adventure Works Laptop15.4W M1548 Red               1047\n",
       "Fabrikam Trendsetter 2/3'' 17mm X100 Black           926\n",
       "Fabrikam Trendsetter 1/3'' 8.5mm X200 Black          884\n",
       "Fabrikam Trendsetter 1/3'' 8.5mm X200 Grey           845\n",
       "Fabrikam Trendsetter 1/3'' 8.5mm X200 White          789\n",
       "Name: Quantidade, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Total de produtos vendidos em ordem do mais vendido para o menos vendido?:\n",
    "df.groupby(\"Produto\")[\"Quantidade\"].sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "43007b6b",
   "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": [
    "#Gráfico total de produtos vendidos:\n",
    "#Verifica-se a necessidade de mudar o sort_values(ascending) de False para True\n",
    "df.groupby(\"Produto\")[\"Quantidade\"].sum().sort_values(ascending=True).plot.barh(title=\"Total de produtos vendidos\")\n",
    "plt.xlabel(\"Total\")\n",
    "plt.ylabel(\"Produto\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "12050686",
   "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": [
    "#Lucro por ano:\n",
    "#Em notação científica\n",
    "df.groupby(df[\"Data Venda\"].dt.year)[\"lucro\"].sum().plot.bar(title=\"Lucro por ano\")\n",
    "plt.xlabel(\"Ano\")\n",
    "plt.ylabel(\"Lucro\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9f90ff76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda\n",
       "2008           1,920,077.71\n",
       "2009           1,577,745.38\n",
       "Name: lucro, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(df[\"Data Venda\"].dt.year)[\"lucro\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "331aa583",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Selecionando apenas as vendas de 2009:\n",
    "df_2009 = df[df[\"Data Venda\"].dt.year == 2009]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "66955517",
   "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>Data Venda</th>\n",
       "      <th>Data Envio</th>\n",
       "      <th>ID Loja</th>\n",
       "      <th>ID Produto</th>\n",
       "      <th>ID Cliente</th>\n",
       "      <th>No. Venda</th>\n",
       "      <th>Custo Unitário</th>\n",
       "      <th>Preço Unitário</th>\n",
       "      <th>Quantidade</th>\n",
       "      <th>Valor Desconto</th>\n",
       "      <th>Valor Venda</th>\n",
       "      <th>Produto</th>\n",
       "      <th>Fabricante</th>\n",
       "      <th>Marca</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Cor</th>\n",
       "      <th>custo</th>\n",
       "      <th>lucro</th>\n",
       "      <th>tempo_envio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2009-05-02</td>\n",
       "      <td>2009-05-14</td>\n",
       "      <td>199</td>\n",
       "      <td>384</td>\n",
       "      <td>18938</td>\n",
       "      <td>200905023CS847</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2009-05-16</td>\n",
       "      <td>2009-05-27</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19067</td>\n",
       "      <td>200905163CS746</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2009-05-31</td>\n",
       "      <td>2009-06-12</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19068</td>\n",
       "      <td>200905313CS748</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2009-06-28</td>\n",
       "      <td>2009-07-11</td>\n",
       "      <td>199</td>\n",
       "      <td>384</td>\n",
       "      <td>18959</td>\n",
       "      <td>200906283CS870</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2009-07-08</td>\n",
       "      <td>2009-07-12</td>\n",
       "      <td>306</td>\n",
       "      <td>384</td>\n",
       "      <td>19070</td>\n",
       "      <td>200907083CS757</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Data Venda Data Envio  ID Loja  ID Produto  ID Cliente       No. Venda  \\\n",
       "11 2009-05-02 2009-05-14      199         384       18938  200905023CS847   \n",
       "12 2009-05-16 2009-05-27      306         384       19067  200905163CS746   \n",
       "13 2009-05-31 2009-06-12      306         384       19068  200905313CS748   \n",
       "14 2009-06-28 2009-07-11      199         384       18959  200906283CS870   \n",
       "15 2009-07-08 2009-07-12      306         384       19070  200907083CS757   \n",
       "\n",
       "         Custo Unitário       Preço Unitário  Quantidade       Valor Desconto  \\\n",
       "11               348.58               758.00           6                 0.00   \n",
       "12               348.58               758.00           6                 0.00   \n",
       "13               348.58               758.00           6                 0.00   \n",
       "14               348.58               758.00           6                 0.00   \n",
       "15               348.58               758.00           6                 0.00   \n",
       "\n",
       "            Valor Venda                                Produto  \\\n",
       "11             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "12             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "13             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "14             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "15             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "\n",
       "         Fabricante            Marca   Classe  Cor                custo  \\\n",
       "11  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "12  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "13  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "14  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "15  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "\n",
       "                  lucro  tempo_envio  \n",
       "11             2,456.52           12  \n",
       "12             2,456.52           11  \n",
       "13             2,456.52           12  \n",
       "14             2,456.52           13  \n",
       "15             2,456.52            4  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2009.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a2f3d701",
   "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": [
    "#Lucro por mês em 2009:\n",
    "df_2009.groupby(df_2009[\"Data Venda\"].dt.month)[\"lucro\"].sum().plot(title=\"Lucro por mês em 2009\")\n",
    "plt.xlabel(\"Mês\")\n",
    "plt.ylabel(\"Lucro\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "81fff89f",
   "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": [
    "#Lucro por marca\n",
    "df_2009.groupby(\"Marca\")[\"lucro\"].sum().plot.bar(title=\"Lucro por marca em 2009\")\n",
    "plt.xlabel(\"Marca\")\n",
    "plt.ylabel(\"Lucro\")\n",
    "#Deixando os valores do eixo X na horizontal:\n",
    "plt.xticks(rotation=\"horizontal\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "30e7aa88",
   "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": [
    "#Lucro por classe\n",
    "df_2009.groupby(\"Classe\")[\"lucro\"].sum().plot.bar(title=\"Lucro por classe em 2009\")\n",
    "plt.xlabel(\"Classe\")\n",
    "plt.ylabel(\"Lucro\")\n",
    "#Deixando os valores do eixo X na horizontal:\n",
    "plt.xticks(rotation=\"horizontal\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "737e6877",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                 904.00\n",
       "mean                    8.54\n",
       "std                     3.06\n",
       "min                     4.00\n",
       "25%                     6.00\n",
       "50%                     9.00\n",
       "75%                    11.00\n",
       "max                    20.00\n",
       "Name: tempo_envio, dtype: float64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"tempo_envio\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "4d04324c",
   "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": [
    "#Gráfico boxplot\n",
    "plt.boxplot(df[\"tempo_envio\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "e9a59748",
   "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": [
    "#Histograma\n",
    "plt.hist(df[\"tempo_envio\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "a6ddb21b",
   "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>Data Venda</th>\n",
       "      <th>Data Envio</th>\n",
       "      <th>ID Loja</th>\n",
       "      <th>ID Produto</th>\n",
       "      <th>ID Cliente</th>\n",
       "      <th>No. Venda</th>\n",
       "      <th>Custo Unitário</th>\n",
       "      <th>Preço Unitário</th>\n",
       "      <th>Quantidade</th>\n",
       "      <th>Valor Desconto</th>\n",
       "      <th>Valor Venda</th>\n",
       "      <th>Produto</th>\n",
       "      <th>Fabricante</th>\n",
       "      <th>Marca</th>\n",
       "      <th>Classe</th>\n",
       "      <th>Cor</th>\n",
       "      <th>custo</th>\n",
       "      <th>lucro</th>\n",
       "      <th>tempo_envio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008-05-09</td>\n",
       "      <td>2008-05-29</td>\n",
       "      <td>199</td>\n",
       "      <td>384</td>\n",
       "      <td>18839</td>\n",
       "      <td>200805093CS607</td>\n",
       "      <td>348.58</td>\n",
       "      <td>758.00</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4,548.00</td>\n",
       "      <td>Adventure Works Laptop15.4W M1548 Red</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Adventure Works</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Red</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Data Venda Data Envio  ID Loja  ID Produto  ID Cliente       No. Venda  \\\n",
       "0 2008-05-09 2008-05-29      199         384       18839  200805093CS607   \n",
       "\n",
       "        Custo Unitário       Preço Unitário  Quantidade       Valor Desconto  \\\n",
       "0               348.58               758.00           6                 0.00   \n",
       "\n",
       "           Valor Venda                                Produto  \\\n",
       "0             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "\n",
       "        Fabricante            Marca   Classe  Cor                custo  \\\n",
       "0  Adventure Works  Adventure Works  Regular  Red             2,091.48   \n",
       "\n",
       "                 lucro  tempo_envio  \n",
       "0             2,456.52           20  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Verificando o outlier de 20 dias para envio:\n",
    "df[df[\"tempo_envio\"] == 20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a7d7195c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Salvando o dataframe analisado em CSV:\n",
    "df.to_csv(\"df_vendas_novo.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf236700",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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