desafio-bootcamp_dados.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f43ac730",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(\"seaborn\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "911d10ba",
   "metadata": {},
   "source": [
    "# Importando e conferindo o dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9739b8c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel(\"datasets/AdventureWorks.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8db02417",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.display.float_format = '{:20,.2f}'.format #formatando os números de ponto flutuante"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "53259fbd",
   "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>758.00</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",
       "    </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>758.00</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",
       "    </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>758.00</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",
       "    </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",
       "\n",
       "        Custo Unitário       Preço Unitário  Quantidade       Valor Desconto  \\\n",
       "0               348.58               758.00           6                 0.00   \n",
       "1               348.58               758.00           6                 0.00   \n",
       "2               348.58               758.00           6                 0.00   \n",
       "\n",
       "           Valor Venda                                Produto  \\\n",
       "0             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "1             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "2             4,548.00  Adventure Works Laptop15.4W M1548 Red   \n",
       "\n",
       "        Fabricante            Marca   Classe  Cor  \n",
       "0  Adventure Works  Adventure Works  Regular  Red  \n",
       "1  Adventure Works  Adventure Works  Regular  Red  \n",
       "2  Adventure Works  Adventure Works  Regular  Red  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)\n",
    "#Conferindo as 3 primeiras linhas do dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9bc02ae8",
   "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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes\n",
    "#verificando o tipo dos dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "af9c6822",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 904 entries, 0 to 903\n",
      "Data columns (total 16 columns):\n",
      " #   Column          Non-Null Count  Dtype         \n",
      "---  ------          --------------  -----         \n",
      " 0   Data Venda      904 non-null    datetime64[ns]\n",
      " 1   Data Envio      904 non-null    datetime64[ns]\n",
      " 2   ID Loja         904 non-null    int64         \n",
      " 3   ID Produto      904 non-null    int64         \n",
      " 4   ID Cliente      904 non-null    int64         \n",
      " 5   No. Venda       904 non-null    object        \n",
      " 6   Custo Unitário  904 non-null    float64       \n",
      " 7   Preço Unitário  904 non-null    float64       \n",
      " 8   Quantidade      904 non-null    int64         \n",
      " 9   Valor Desconto  904 non-null    float64       \n",
      " 10  Valor Venda     904 non-null    float64       \n",
      " 11  Produto         904 non-null    object        \n",
      " 12  Fabricante      904 non-null    object        \n",
      " 13  Marca           904 non-null    object        \n",
      " 14  Classe          904 non-null    object        \n",
      " 15  Cor             904 non-null    object        \n",
      "dtypes: datetime64[ns](2), float64(4), int64(4), object(6)\n",
      "memory usage: 113.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()\n",
    "#consultando os dados do dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "46de78bb",
   "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",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()\n",
    "#Verificando se existem dados nulos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cf9cdb3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Data Venda', 'Data Envio', 'ID Loja', 'ID Produto', 'ID Cliente',\n",
       "       'No. Venda', 'Custo Unitário', 'Preço Unitário', 'Quantidade',\n",
       "       'Valor Desconto', 'Valor Venda', 'Produto', 'Fabricante', 'Marca',\n",
       "       'Classe', 'Cor'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns\n",
    "#listando cabeçalhos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ef966a7",
   "metadata": {},
   "source": [
    "# Enriquecendo o Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4ffb16de",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Dias de Envio\"] = df[\"Data Envio\"] - df[\"Data Venda\"] \n",
    "#Cria nova coluna com o tempo de envio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e39f8d4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     20 days\n",
      "1      5 days\n",
      "2      6 days\n",
      "3      6 days\n",
      "4      7 days\n",
      "        ...  \n",
      "899   13 days\n",
      "900   11 days\n",
      "901    4 days\n",
      "902    4 days\n",
      "903    4 days\n",
      "Name: Dias de Envio, Length: 904, dtype: timedelta64[ns]\n"
     ]
    }
   ],
   "source": [
    "print(df[\"Dias de Envio\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f5f6b06f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Dias de Envio\"] = (df[\"Data Envio\"] - df[\"Data Venda\"]).dt.days\n",
    "#Retira a string da coluna \"Dias de Envio\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "154d98cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Custo Total\"] = df[\"Custo Unitário\"] * df[\"Quantidade\"] \n",
    "#Calcula o custo total em uma nova coluna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "dfdb7c50",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Lucro Bruto\"] = df[\"Valor Venda\"] - df[\"Custo Total\"]\n",
    "#Calcula e cria a coluna 'Lucro Bruto'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "de345296",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Lucro Líquido\"] = df[\"Lucro Bruto\"] - df[\"Valor Desconto\"] \n",
    "#'Lucro Líquido'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf3c951",
   "metadata": {},
   "source": [
    "# Analisando os dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e65858d5",
   "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": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"Produto\")[\"Quantidade\"].sum().sort_values(ascending=False)\n",
    "#Vendo a quantidade de cada produto vendido"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "abe42543",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data Venda  Marca          \n",
       "2008        Adventure Works             241,528.96\n",
       "            Contoso                      41,130.30\n",
       "            Fabrikam                  1,344,984.43\n",
       "2009        Adventure Works             308,022.40\n",
       "            Contoso                     102,043.60\n",
       "            Fabrikam                    837,145.94\n",
       "Name: Lucro Líquido, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([df[\"Data Venda\"].dt.year, \"Marca\"])[\"Lucro Líquido\"].sum()\n",
    "#Marcas mais vendidas por ano"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6c29515a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                 904.00\n",
       "mean                6,620.14\n",
       "std                 4,319.41\n",
       "min                   159.84\n",
       "25%                 3,920.00\n",
       "50%                 5,798.70\n",
       "75%                 7,986.00\n",
       "max                29,400.00\n",
       "Name: Valor Venda, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Valor Venda\"].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23024feb",
   "metadata": {},
   "source": [
    "# Plotando gráficos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0bb6f2d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(\"Produto\")[\"Quantidade\"].sum().sort_values(ascending=True).plot.barh(title=\"Total Produtos Vendidos\")\n",
    "plt.xlabel(\"Total\")\n",
    "plt.ylabel(\"Produto\");\n",
    "#gráfico de barras horizontais (barh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "96d3e7f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(df[\"Data Venda\"].dt.year)[\"Lucro Líquido\"].sum().plot.bar(color=\"crimson\")\n",
    "plt.title(\"Lucro x Ano\")\n",
    "plt.xlabel(\"Ano\")\n",
    "plt.ylabel(\"Receita\")\n",
    "plt.xticks(rotation='horizontal');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "073bf31c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2008 = df[df[\"Data Venda\"].dt.year == 2008]\n",
    "#Seleciona apenas as vendas de 2008\n",
    "\n",
    "df_2009 = df[df[\"Data Venda\"].dt.year == 2009]\n",
    "#Seleciona vendas de 2009"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c467c00e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_2008.groupby(df_2008[\"Data Venda\"].dt.month)[\"Lucro Líquido\"].sum().plot(color='darkmagenta', label='Ano 2008')\n",
    "df_2009.groupby(df_2009[\"Data Venda\"].dt.month)[\"Lucro Líquido\"].sum().plot(color='darkturquoise', label='Ano 2009')\n",
    "plt.title(\"Lucro x Mês\")\n",
    "plt.xlabel(\"Mês\")\n",
    "plt.ylabel(\"Lucro Líquido\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a41cefda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_2009.groupby(\"Marca\")[\"Lucro Líquido\"].sum().plot.bar(title=\"Lucro x Marca\", color=\"teal\")\n",
    "plt.xlabel(\"Marca\")\n",
    "plt.ylabel(\"Lucro\")\n",
    "plt.xticks(rotation='horizontal'); \n",
    "#xticks rotaciona a marcação no eixo x"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "398ceaa4",
   "metadata": {},
   "source": [
    "# identificando outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "70ab3d65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(df[\"Dias de Envio\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "85064b52",
   "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: Dias de Envio, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Dias de Envio\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4f0aecd0",
   "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>Dias de Envio</th>\n",
       "      <th>Custo Total</th>\n",
       "      <th>Lucro Bruto</th>\n",
       "      <th>Lucro Líquido</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>20</td>\n",
       "      <td>2,091.48</td>\n",
       "      <td>2,456.52</td>\n",
       "      <td>2,456.52</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  Dias de Envio  \\\n",
       "0  Adventure Works  Adventure Works  Regular  Red             20   \n",
       "\n",
       "           Custo Total          Lucro Bruto        Lucro Líquido  \n",
       "0             2,091.48             2,456.52             2,456.52  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Dias de Envio\"] == 20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5edd0576",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeQAAAFKCAYAAADMuCxnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAXRklEQVR4nO3dcWxV9f3/8ddtb28uzBug9LaxxBnCQiDStTPXLCB1xotQXL7zDmGQDpchMLNWgkkRKjSbicuEgovK2HCwIrIZO67GX3/R2MZpE/+4dIG7NDQzUYxbJtb2FurK2luQ7nz/MN4vDO1Fest933uej39KT2/v+XzeFp+957YXj+M4jgAAQFYVZHsBAACAIAMAYAJBBgDAAIIMAIABBBkAAAMIMgAABnizefJE4lxG72/GjKkaHBzJ6H3mGmbADNy+f4kZSMxAsjmDYDDwpR/Lq0fIXm9htpeQdcyAGbh9/xIzkJiBlHszyKsgAwCQqwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYkNV/7SnT/qfh/2V7CWm1NN6V7SUAAAziETIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAFp/z3knp4e1dXV6eabb5YkzZ07Vxs2bNDWrVs1NjamYDCo3bt3y+fzqa2tTYcPH1ZBQYFWr16tlStXTvoGAADIB2mDPDIyomXLlmnHjh2pY48++qhqa2u1fPlyNTc3KxqNKhKJaN++fYpGoyoqKlIkEtGSJUs0ffr0yVw/AAB5Ie0l6+Hh4SuOdXV1KRwOS5LC4bBisZi6u7tVUVGhQCAgv9+vUCikeDye+RUDAJCHruoR8okTJ7RhwwYlk0lt2rRJyWRSPp9PkhQMBpVIJDQwMKDi4uLU55WUlCiRSEzeygEAyCNpgzxv3jzV19crHA7rgw8+0Lp163Tx4sXUxx3Hueztpcc9Hs+49z1jxlR5vYXXsu6cFQwG8uIc1rl9Bm7fv8QMJGYg5dYM0gZ5zpw5mjNnjiRp9uzZKikpUW9vr0ZHR+X3+9XX16fS0lKVlZWps7Mz9Xn9/f2qqqoa974HB0cmtPhclEicm9T7DwYDk34O69w+A7fvX2IGEjOQbM5gvG8Q0j6HHI1G9fzzz0uSEomEzpw5oxUrVqi9vV2S1NHRoerqalVWVurkyZMaGhrS8PCw4vG4QqFQhrYAAEB+S/sI+e6779aWLVvU3t6uCxcu6LHHHtP8+fO1bds2tba2qry8XJFIREVFRWpoaND69evl8XhUX1+vQCB3LhUAAJBNaYM8bdo0HThw4Irjhw4duuJYTU2NampqMrMyAABchFfqAgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAZcVZBHR0cVDof18ssvq7e3V/fff79qa2u1efNmXbhwQZLU1tam++67T6tWrVI0Gp3URQMAkG+uKsi//e1vNX36dEnSM888o9raWr3wwguaNWuWotGoRkZGtG/fPj333HM6cuSIDh48qE8++WQSlw0AQH5JG+T3339fp06d0p133ilJ6urqUjgcliSFw2HFYjF1d3eroqJCgUBAfr9foVBI8Xh8UhcOAEA+SRvkXbt2qbGxMfV+MpmUz+eTJAWDQSUSCQ0MDKi4uDh1m5KSEiUSiUlYLgAA+ck73gdfeeUVVVVV6aabbkod83g8qT87jnPZ20uPX3q7LzNjxlR5vYVfacG5LhgM5MU5rHP7DNy+f4kZSMxAyq0ZjBvkzs5O/fOf/1RnZ6c+/vhj+Xw+TZkyRaOjo/L7/err61NpaanKysrU2dmZ+rz+/n5VVVWlPfng4MhE159zEolzk3r/wWBg0s9hndtn4Pb9S8xAYgaSzRmM9w3CuEF+6qmnUn/eu3evZs2apb/+9a9qb2/Xvffeq46ODlVXV6uyslJNTU0aGhpSYWGh4vG4tm/fnrENAACQ78YN8hfZtGmTtm3bptbWVpWXlysSiaioqEgNDQ1av369PB6P6uvrFQjkzmUCAACy7aqDvGnTptSfDx06dMXHa2pqVFNTk5lVAQDgMrxSFwAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADDAm+4GyWRSjY2NOnPmjM6fP6+6ujrNmzdPW7du1djYmILBoHbv3i2fz6e2tjYdPnxYBQUFWr16tVauXHk99gAAQM5LG+S33npLCxYs0MaNG3X69Gk98MADuvXWW1VbW6vly5erublZ0WhUkUhE+/btUzQaVVFRkSKRiJYsWaLp06dfh20AAJDb0l6yvueee7Rx40ZJUm9vr8rKytTV1aVwOCxJCofDisVi6u7uVkVFhQKBgPx+v0KhkOLx+OSuHgCAPJH2EfLn1qxZo48//lj79+/XunXr5PP5JEnBYFCJREIDAwMqLi5O3b6kpESJRCLzKwYAIA9ddZBffPFFvfPOO3rkkUfk8XhSxx3Hueztpccvvd0XmTFjqrzewq+y3pwXDAby4hzWuX0Gbt+/xAwkZiDl1gzSBrmnp0czZ87UjTfeqPnz52tsbExTpkzR6Oio/H6/+vr6VFpaqrKyMnV2dqY+r7+/X1VVVePe9+DgyETXn3MSiXOTev/BYGDSz2Gd22fg9v1LzEBiBpLNGYz3DULa55CPHz+ulpYWSdLAwIBGRka0aNEitbe3S5I6OjpUXV2tyspKnTx5UkNDQxoeHlY8HlcoFMrQFgAAyG9pHyGvWbNGO3bsUG1trUZHR/Wzn/1MCxYs0LZt29Ta2qry8nJFIhEVFRWpoaFB69evl8fjUX19vQKB3LlUAABANqUNst/v15NPPnnF8UOHDl1xrKamRjU1NZlZGQAALsIrdQEAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADvFdzo+bmZp04cUIXL17Ugw8+qIqKCm3dulVjY2MKBoPavXu3fD6f2tradPjwYRUUFGj16tVauXLlZK8fAIC8kDbIx44d03vvvafW1lYNDg7q+9//vhYuXKja2lotX75czc3NikajikQi2rdvn6LRqIqKihSJRLRkyRJNnz79Omwjdzyw881sLyGtlsa7sr0EAHCdtJesb7vtNj399NOSpGnTpimZTKqrq0vhcFiSFA6HFYvF1N3drYqKCgUCAfn9foVCIcXj8cldPQAAeSJtkAsLCzV16lRJ0tGjR3XHHXcomUzK5/NJkoLBoBKJhAYGBlRcXJz6vJKSEiUSiUlaNgAA+eWqnkOWpDfeeEPRaFQtLS1atmxZ6rjjOJe9vfS4x+MZ9z5nzJgqr7fwq6wX10EwGMj2EiYsH/YwEW7fv8QMJGYg5dYMrirIb7/9tvbv36+DBw8qEAhoypQpGh0dld/vV19fn0pLS1VWVqbOzs7U5/T396uqqmrc+x0cHJnI2jFJEolz2V7ChASDgZzfw0S4ff8SM5CYgWRzBuN9g5D2kvW5c+fU3NysZ599NvUDWosWLVJ7e7skqaOjQ9XV1aqsrNTJkyc1NDSk4eFhxeNxhUKhzOwAAIA8l/YR8muvvabBwUE9/PDDqWM7d+5UU1OTWltbVV5erkgkoqKiIjU0NGj9+vXyeDyqr69XIJA7lwoAAMgmj/PfT/5eR5m+lJALv1KUC3L9154sXqa6nty+f4kZSMxAsjmDCV2yBgAAk48gAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABVxXkd999V0uWLNEf/vAHSVJvb6/uv/9+1dbWavPmzbpw4YIkqa2tTffdd59WrVqlaDQ6easGACDPpA3yyMiIHn/8cS1cuDB17JlnnlFtba1eeOEFzZo1S9FoVCMjI9q3b5+ee+45HTlyRAcPHtQnn3wymWsHACBvpA2yz+fTgQMHVFpamjrW1dWlcDgsSQqHw4rFYuru7lZFRYUCgYD8fr9CoZDi8fjkrRwAgDziTXsDr1de7+U3SyaT8vl8kqRgMKhEIqGBgQEVFxenblNSUqJEIpHh5QIAkJ/SBvmLeDye1J8dx7ns7aXHL73dF5kxY6q83sJrWQImUTAYyPYSJiwf9jARbt+/xAwkZiDl1gyuKchTpkzR6Oio/H6/+vr6VFpaqrKyMnV2dqZu09/fr6qqqnHvZ3Bw5FpOj0mWSJzL9hImJBgM5PweJsLt+5eYgcQMJJszGO8bhGv6tadFixapvb1dktTR0aHq6mpVVlbq5MmTGhoa0vDwsOLxuEKh0LWtGAAAl0n7CLmnp0e7du3S6dOn5fV61d7erj179qixsVGtra0qLy9XJBJRUVGRGhoatH79enk8HtXX1ysQyJ1LBQAAZFPaIC9YsEBHjhy54vihQ4euOFZTU6OamprMrAwAABfhlboAADCAIAMAYABBBgDAAIIMAIAB1/R7yMhvD+x8M9tLGFdL413ZXgIAZByPkAEAMIAgAwBgAEEGAMAAggwAgAEEGQAAAwgyAAAGEGQAAAwgyAAAGECQAQAwgCADAGAAQQYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAY4M32AoCv6oGdb2Z7CWm1NN6V7SUAyDE8QgYAwACCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYABBBgDAAIIMAIABBBkAAAMIMgAABhBkAAAMIMgAABhAkAEAMIAgAwBgAEEGAMAAb7YXAOSjB3a+me0ljKul8a5sLwHAf+ERMgAABhBkAAAMIMgAABhAkAEAMCDjP9T1y1/+Ut3d3fJ4PNq+fbu++c1vZvoUACbI+g+dSfzgGdwno0H+y1/+on/84x9qbW3VqVOn9Oijj+ro0aOZPAUAAHkpo0GOxWJasmSJJOkb3/iGhoaG9O9//1s33HBDJk8DAFnHVQZkWkaDPDAwoFtuuSX1/syZM5VIJAgygK8sF4KHibP+3/l6flOT0SA7jnPF+x6P50tvHwwGMnl6/f8n783o/QEAJhf/3/4/Gf0p67KyMg0MDKTe7+/vV0lJSSZPAQBAXspokG+//Xa1t7dLkv72t7+ptLSUy9UAAFyFjF6yvvXWW3XLLbdozZo18ng8+vnPf57JuwcAIG95nP9+4hcAAFx3vFIXAAAGEGQAAAzIm38P2Q0v2fnuu++qrq5OP/7xj7V27Vr19vZq69atGhsbUzAY1O7du+Xz+dTW1qbDhw+roKBAq1ev1sqVK/Xpp5+qsbFRH330kQoLC/XEE0/opptuyvaWvpLm5madOHFCFy9e1IMPPqiKigpX7T+ZTKqxsVFnzpzR+fPnVVdXp3nz5rlqBpI0Ojqq7373u6qvr9fChQtdtf+enh7V1dXp5ptvliTNnTtXGzZscNUMJKmtrU0HDx6U1+vV5s2bNXfu3PyYgZMHurq6nJ/85CeO4zjOe++956xcuTLLK8q84eFhZ+3atU5TU5Nz5MgRx3Ecp7Gx0Xnttdccx3GcXbt2OX/84x+d4eFhZ+nSpc7Q0JCTTCadZcuWOYODg87LL7/sPPbYY47jOE5nZ6ezefPmbG3lmsRiMWfDhg2O4zjO2bNnne985zuu2r/jOM6rr77q/O53v3Mcx3E+/PBDZ+nSpa6bgeM4zq9+9StnxYoVzksvveS6/Xd1dTm/+MUvLjvmthmcPXvWWbp0qXPu3Dmnr6/PaWpqypsZ5MUl6y97yc584vP5dODAAZWWlqaOdXV1KRwOS5LC4bBisZi6u7tVUVGhQCAgv9+vUCikeDyuWCymu+++W5K0ePFinThxIiv7uFa33Xabnn76aUnStGnTlEwmXbV/Sbrnnnu0ceNGSVJvb6/KyspcN4P3339fp06d0p133inJXX8HJGl4ePiKY26bQSwW08KFC3XDDTeotLRUjz/+eN7MIC+CPDAwoBkzZqTe//wlO/OJ1+uV3++/7FgymZTP55MkBYNBJRIJDQwMqLi4OHWbkpKSK44XFhaqoKBAFy5cuH4bmKDCwkJNnTpVknT06FHdcccdrtr/pdasWaMtW7Zo+/btrpvBrl271NjYmHrfbfsfGRnRiRMntGHDBv3whz/UsWPHXDeDDz/8UI7j6OGHH1Ztba1isVjezCAvnkN2vuJLduaLS/f4+Qy+bBb5MqM33nhD0WhULS0tWrZsWeq4W/YvSS+++KLeeecdPfLII676GnjllVdUVVV12fN9btq/JM2bN0/19fUKh8P64IMPtG7dOl28eDH1cTfMQJL6+vr061//Wh999JF+9KMf5c3XQV48QnbrS3ZOmTJFo6Ojkj77Ai0tLf3CWQSDQZWVlaWuGnz66adyHEdFRUVZWfe1evvtt7V//34dOHBAgUDAdfvv6elRb2+vJGn+/PkaGxtz1Qw6Ozv15z//WT/4wQ909OhR/eY3v3HV/iVpzpw5qUuzs2fPVklJiYaGhlw1g5kzZ+pb3/qWvF6vvv71r+trX/ta3nwd5EWQ3fqSnYsWLUrtu6OjQ9XV1aqsrNTJkyc1NDSk4eFhxeNxhUIh3X777Xr99dclSW+99Za+/e1vZ3PpX9m5c+fU3NysZ599VtOnT5fkrv1L0vHjx9XS0iLps6dpRkZGXDWDp556Si+99JL+9Kc/adWqVaqrq3PV/iUpGo3q+eeflyQlEgmdOXNGK1ascNUMFi9erGPHjuk///mPzp49m1d/D/Lmlbr27Nmj48ePp16yc968edleUkb19PRo165dOn36tLxer8rKyrRnzx41Njbq/PnzKi8v1xNPPKGioiK9/vrr+v3vfy+Px6O1a9fqe9/7nsbGxtTU1KS///3v8vl82rlzp2688cZsb+uqtba2au/evZo9e3bq2M6dO9XU1OSK/Uuf/brPjh071Nvbq9HRUT300ENasGCBtm3b5poZfG7v3r2aNWuWFi9e7Kr9/+tf/9KWLVs0MjKiCxcu6KGHHtL8+fNdNQPps6dtXn31VSWTSf30pz9VRUVFXswgb4IMAEAuy4tL1gAA5DqCDACAAQQZAAADCDIAAAYQZAAADCDIAAAYQJABADCAIAMAYMD/AilQh/FhOdrJAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df[\"Valor Desconto\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a0b7c199",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                 904.00\n",
       "mean                  689.12\n",
       "std                   822.36\n",
       "min                     0.00\n",
       "25%                     0.00\n",
       "50%                   461.17\n",
       "75%                 1,005.08\n",
       "max                 6,272.00\n",
       "Name: Valor Desconto, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Valor Desconto\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e8628835",
   "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>Dias de Envio</th>\n",
       "      <th>Custo Total</th>\n",
       "      <th>Lucro Bruto</th>\n",
       "      <th>Lucro Líquido</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>2008-12-16</td>\n",
       "      <td>2008-12-27</td>\n",
       "      <td>199</td>\n",
       "      <td>1203</td>\n",
       "      <td>18897</td>\n",
       "      <td>200812164CS805</td>\n",
       "      <td>324.69</td>\n",
       "      <td>980.00</td>\n",
       "      <td>32</td>\n",
       "      <td>6,272.00</td>\n",
       "      <td>25,088.00</td>\n",
       "      <td>Fabrikam Trendsetter 2/3'' 17mm X100 Grey</td>\n",
       "      <td>Fabrikam, Inc.</td>\n",
       "      <td>Fabrikam</td>\n",
       "      <td>Regular</td>\n",
       "      <td>Grey</td>\n",
       "      <td>11</td>\n",
       "      <td>10,390.08</td>\n",
       "      <td>14,697.92</td>\n",
       "      <td>8,425.92</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Data Venda Data Envio  ID Loja  ID Produto  ID Cliente       No. Venda  \\\n",
       "339 2008-12-16 2008-12-27      199        1203       18897  200812164CS805   \n",
       "\n",
       "          Custo Unitário       Preço Unitário  Quantidade  \\\n",
       "339               324.69               980.00          32   \n",
       "\n",
       "          Valor Desconto          Valor Venda  \\\n",
       "339             6,272.00            25,088.00   \n",
       "\n",
       "                                       Produto      Fabricante     Marca  \\\n",
       "339  Fabrikam Trendsetter 2/3'' 17mm X100 Grey  Fabrikam, Inc.  Fabrikam   \n",
       "\n",
       "      Classe   Cor  Dias de Envio          Custo Total          Lucro Bruto  \\\n",
       "339  Regular  Grey             11            10,390.08            14,697.92   \n",
       "\n",
       "           Lucro Líquido  \n",
       "339             8,425.92  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Valor Desconto\"] == 6272.00]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ff35a3d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#salvando arquivo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f53a2a83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('datasets/AdventureWorks_final.csv', index=False)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.10.6 64-bit",
   "language": "python",
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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