DataClean.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "188176dc-133f-472f-a7d4-58ace2d3d7ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# import CSV files\n",
    "\n",
    "orders = pd.read_csv('20621098.csv')\n",
    "customer  = pd.read_csv('customer.csv')\n",
    "geolocation= pd.read_csv('geolocation.csv')\n",
    "order_item= pd.read_csv('order_item.csv')\n",
    "order_payment= pd.read_csv('order_payment.csv')\n",
    "order_review= pd.read_csv('order_review.csv')\n",
    "product_category_name_translation= pd.read_csv('product_category_name_translation.csv')\n",
    "product= pd.read_csv('product.csv')\n",
    "seller= pd.read_csv('seller.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d39964f5-89e0-45ac-b908-9f2e08add056",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "order_id                            0\n",
      "customer_id                         0\n",
      "order_status                        0\n",
      "order_purchase_timestamp            0\n",
      "order_approved_at                 111\n",
      "order_delivered_carrier_date     1309\n",
      "order_delivered_customer_date    2208\n",
      "order_estimated_delivery_date       0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "customer_id                 0\n",
      "customer_unique_id          0\n",
      "customer_zip_code_prefix    0\n",
      "customer_city               0\n",
      "customer_state              0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "geolocation_zip_code_prefix    0\n",
      "geolocation_lat                0\n",
      "geolocation_lng                0\n",
      "geolocation_city               0\n",
      "geolocation_state              0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "order_id               0\n",
      "order_item_id          0\n",
      "product_id             0\n",
      "seller_id              0\n",
      "shipping_limit_date    0\n",
      "price                  0\n",
      "freight_value          0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "order_id                0\n",
      "payment_sequential      0\n",
      "payment_type            0\n",
      "payment_installments    0\n",
      "payment_value           0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "review_id                      0\n",
      "order_id                       0\n",
      "review_score                   0\n",
      "review_comment_title       87656\n",
      "review_comment_message     58247\n",
      "review_creation_date           0\n",
      "review_answer_timestamp        0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "product_category_name            0\n",
      "product_category_name_english    0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "product_id                      0\n",
      "product_category_name         610\n",
      "product_name_lenght           610\n",
      "product_description_lenght    610\n",
      "product_photos_qty            610\n",
      "product_weight_g                2\n",
      "product_length_cm               2\n",
      "product_height_cm               2\n",
      "product_width_cm                2\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n",
      "seller_id                 0\n",
      "seller_zip_code_prefix    0\n",
      "seller_city               0\n",
      "seller_state              0\n",
      "dtype: int64 \n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Check NaN data in each files\n",
    "for i in [orders,customer,geolocation,order_item,order_payment,order_review,product_category_name_translation,product,seller]:\n",
    "    print(i.isnull().sum(),'\\n\\n\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "940113bc-9400-45dc-afc0-75a5e3e38589",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop all NaN, except order_review(Lack of comment)\n",
    "orders  = orders.dropna()\n",
    "customer  = customer.dropna()\n",
    "geolocation  = geolocation.dropna()\n",
    "product  = product.dropna()\n",
    "order_item  = order_item.dropna()\n",
    "order_payment  = order_payment.dropna()\n",
    "product_category_name_translation  = product_category_name_translation.dropna()\n",
    "seller  = seller.dropna()\n",
    "\n",
    "data_1 = [orders,customer,geolocation,order_item,order_payment,product_category_name_translation,seller,product]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "c0977d00-9ea3-4856-a29b-f3943de3abb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                order_id                       customer_id  \\\n",
      "count                              72783                             72783   \n",
      "unique                             72783                             72783   \n",
      "top     c9c47f859e747812a921562c2f874229  6425d1369b270b096dfcbce176e3c59c   \n",
      "freq                                   1                                 1   \n",
      "\n",
      "       order_status order_purchase_timestamp    order_approved_at  \\\n",
      "count         72783                    72783                72783   \n",
      "unique            2                    72506                67889   \n",
      "top       delivered      2018-04-11 10:48:14  2018-02-27 04:31:10   \n",
      "freq          72778                        3                    7   \n",
      "\n",
      "       order_delivered_carrier_date order_delivered_customer_date  \\\n",
      "count                         72783                         72783   \n",
      "unique                        62570                         72335   \n",
      "top             2018-05-09 15:48:00           2018-05-14 20:02:44   \n",
      "freq                             33                             3   \n",
      "\n",
      "       order_estimated_delivery_date  \n",
      "count                          72783  \n",
      "unique                           440  \n",
      "top              2018-02-14 00:00:00  \n",
      "freq                             404   \n",
      "\n",
      "       customer_zip_code_prefix\n",
      "count              99441.000000\n",
      "mean               35137.474583\n",
      "std                29797.938996\n",
      "min                 1003.000000\n",
      "25%                11347.000000\n",
      "50%                24416.000000\n",
      "75%                58900.000000\n",
      "max                99990.000000 \n",
      "\n",
      "       geolocation_zip_code_prefix  geolocation_lat  geolocation_lng\n",
      "count                 1.000163e+06     1.000163e+06     1.000163e+06\n",
      "mean                  3.657417e+04    -2.117615e+01    -4.639054e+01\n",
      "std                   3.054934e+04     5.715866e+00     4.269748e+00\n",
      "min                   1.001000e+03    -3.660537e+01    -1.014668e+02\n",
      "25%                   1.107500e+04    -2.360355e+01    -4.857317e+01\n",
      "50%                   2.653000e+04    -2.291938e+01    -4.663788e+01\n",
      "75%                   6.350400e+04    -1.997962e+01    -4.376771e+01\n",
      "max                   9.999000e+04     4.506593e+01     1.211054e+02 \n",
      "\n",
      "       order_item_id          price  freight_value\n",
      "count  112650.000000  112650.000000  112650.000000\n",
      "mean        1.197834     120.653739      19.990320\n",
      "std         0.705124     183.633928      15.806405\n",
      "min         1.000000       0.850000       0.000000\n",
      "25%         1.000000      39.900000      13.080000\n",
      "50%         1.000000      74.990000      16.260000\n",
      "75%         1.000000     134.900000      21.150000\n",
      "max        21.000000    6735.000000     409.680000 \n",
      "\n",
      "       payment_sequential  payment_installments  payment_value\n",
      "count       103886.000000         103886.000000  103886.000000\n",
      "mean             1.092679              2.853349     154.100380\n",
      "std              0.706584              2.687051     217.494064\n",
      "min              1.000000              0.000000       0.000000\n",
      "25%              1.000000              1.000000      56.790000\n",
      "50%              1.000000              1.000000     100.000000\n",
      "75%              1.000000              4.000000     171.837500\n",
      "max             29.000000             24.000000   13664.080000 \n",
      "\n",
      "       review_score\n",
      "count  99224.000000\n",
      "mean       4.086421\n",
      "std        1.347579\n",
      "min        1.000000\n",
      "25%        4.000000\n",
      "50%        5.000000\n",
      "75%        5.000000\n",
      "max        5.000000 \n",
      "\n",
      "       product_category_name product_category_name_english\n",
      "count                     71                            71\n",
      "unique                    71                            71\n",
      "top             beleza_saude                 health_beauty\n",
      "freq                       1                             1 \n",
      "\n",
      "       product_name_lenght  product_description_lenght  product_photos_qty  \\\n",
      "count         32340.000000                32340.000000        32340.000000   \n",
      "mean             48.476592                  771.492393            2.188961   \n",
      "std              10.245699                  635.124831            1.736787   \n",
      "min               5.000000                    4.000000            1.000000   \n",
      "25%              42.000000                  339.000000            1.000000   \n",
      "50%              51.000000                  595.000000            1.000000   \n",
      "75%              57.000000                  972.000000            3.000000   \n",
      "max              76.000000                 3992.000000           20.000000   \n",
      "\n",
      "       product_weight_g  product_length_cm  product_height_cm  \\\n",
      "count      32340.000000       32340.000000       32340.000000   \n",
      "mean        2276.956586          30.854545          16.958813   \n",
      "std         4279.291845          16.955965          13.636115   \n",
      "min            0.000000           7.000000           2.000000   \n",
      "25%          300.000000          18.000000           8.000000   \n",
      "50%          700.000000          25.000000          13.000000   \n",
      "75%         1900.000000          38.000000          21.000000   \n",
      "max        40425.000000         105.000000         105.000000   \n",
      "\n",
      "       product_width_cm  \n",
      "count      32340.000000  \n",
      "mean          23.208596  \n",
      "std           12.078762  \n",
      "min            6.000000  \n",
      "25%           15.000000  \n",
      "50%           20.000000  \n",
      "75%           30.000000  \n",
      "max          118.000000   \n",
      "\n",
      "       seller_zip_code_prefix\n",
      "count             3095.000000\n",
      "mean             32291.059451\n",
      "std              32713.453830\n",
      "min               1001.000000\n",
      "25%               7093.500000\n",
      "50%              14940.000000\n",
      "75%              64552.500000\n",
      "max              99730.000000 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in [orders,customer,geolocation,order_item,order_payment,order_review,product_category_name_translation,product,seller]:\n",
    "    print(i.describe(),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2434b7d8-a9ae-4a8f-a0e0-4e570cbee178",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use Z-score to find and cope the outliner in numeric data\n",
    "\n",
    "data_1 = [orders,customer,geolocation,order_item,order_payment,product_category_name_translation,seller,product]\n",
    "\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "for index, df in enumerate(data_1):\n",
    "    num_cols = df.select_dtypes(exclude=['object']).columns\n",
    "    z = np.abs(stats.zscore(df[num_cols]))\n",
    "    data_1[index] = df[(z < 3).all(axis=1)]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ebc73f49-c529-4839-a2ce-d0c954cc6ca1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert Product Date to int\n",
    "num_product_cols = product.select_dtypes(exclude=['object']).columns\n",
    "product[num_product_cols]= product[num_product_cols].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "6aa7ed59-4cdc-4a56-a2cb-8ab5df051f26",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "order_id                         0\n",
      "customer_id                      0\n",
      "order_status                     0\n",
      "order_purchase_timestamp         0\n",
      "order_approved_at                0\n",
      "order_delivered_carrier_date     0\n",
      "order_delivered_customer_date    0\n",
      "order_estimated_delivery_date    0\n",
      "dtype: int64 \n",
      "\n",
      "customer_id                 0\n",
      "customer_unique_id          0\n",
      "customer_zip_code_prefix    0\n",
      "customer_city               0\n",
      "customer_state              0\n",
      "dtype: int64 \n",
      "\n",
      "geolocation_zip_code_prefix    0\n",
      "geolocation_lat                0\n",
      "geolocation_lng                0\n",
      "geolocation_city               0\n",
      "geolocation_state              0\n",
      "dtype: int64 \n",
      "\n",
      "order_id               0\n",
      "order_item_id          0\n",
      "product_id             0\n",
      "seller_id              0\n",
      "shipping_limit_date    0\n",
      "price                  0\n",
      "freight_value          0\n",
      "dtype: int64 \n",
      "\n",
      "order_id                0\n",
      "payment_sequential      0\n",
      "payment_type            0\n",
      "payment_installments    0\n",
      "payment_value           0\n",
      "dtype: int64 \n",
      "\n",
      "product_category_name            0\n",
      "product_category_name_english    0\n",
      "dtype: int64 \n",
      "\n",
      "seller_id                 0\n",
      "seller_zip_code_prefix    0\n",
      "seller_city               0\n",
      "seller_state              0\n",
      "dtype: int64 \n",
      "\n",
      "product_id                    0\n",
      "product_category_name         0\n",
      "product_name_lenght           0\n",
      "product_description_lenght    0\n",
      "product_photos_qty            0\n",
      "product_weight_g              0\n",
      "product_length_cm             0\n",
      "product_height_cm             0\n",
      "product_width_cm              0\n",
      "dtype: int64 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Check again\n",
    "for i in data_1:\n",
    "    print(i.isnull().sum(),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c5c34c13-7674-44e2-94d6-e6b2c8cbbd96",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                order_id                       customer_id  \\\n",
      "count                              72783                             72783   \n",
      "unique                             72783                             72783   \n",
      "top     c9c47f859e747812a921562c2f874229  6425d1369b270b096dfcbce176e3c59c   \n",
      "freq                                   1                                 1   \n",
      "\n",
      "       order_status order_purchase_timestamp    order_approved_at  \\\n",
      "count         72783                    72783                72783   \n",
      "unique            2                    72506                67889   \n",
      "top       delivered      2018-04-11 10:48:14  2018-02-27 04:31:10   \n",
      "freq          72778                        3                    7   \n",
      "\n",
      "       order_delivered_carrier_date order_delivered_customer_date  \\\n",
      "count                         72783                         72783   \n",
      "unique                        62570                         72335   \n",
      "top             2018-05-09 15:48:00           2018-05-14 20:02:44   \n",
      "freq                             33                             3   \n",
      "\n",
      "       order_estimated_delivery_date  \n",
      "count                          72783  \n",
      "unique                           440  \n",
      "top              2018-02-14 00:00:00  \n",
      "freq                             404   \n",
      "\n",
      "       customer_zip_code_prefix\n",
      "count              99441.000000\n",
      "mean               35137.474583\n",
      "std                29797.938996\n",
      "min                 1003.000000\n",
      "25%                11347.000000\n",
      "50%                24416.000000\n",
      "75%                58900.000000\n",
      "max                99990.000000 \n",
      "\n",
      "       geolocation_zip_code_prefix  geolocation_lat  geolocation_lng\n",
      "count                 1.000163e+06     1.000163e+06     1.000163e+06\n",
      "mean                  3.657417e+04    -2.117615e+01    -4.639054e+01\n",
      "std                   3.054934e+04     5.715866e+00     4.269748e+00\n",
      "min                   1.001000e+03    -3.660537e+01    -1.014668e+02\n",
      "25%                   1.107500e+04    -2.360355e+01    -4.857317e+01\n",
      "50%                   2.653000e+04    -2.291938e+01    -4.663788e+01\n",
      "75%                   6.350400e+04    -1.997962e+01    -4.376771e+01\n",
      "max                   9.999000e+04     4.506593e+01     1.211054e+02 \n",
      "\n",
      "       order_item_id          price  freight_value\n",
      "count  112650.000000  112650.000000  112650.000000\n",
      "mean        1.197834     120.653739      19.990320\n",
      "std         0.705124     183.633928      15.806405\n",
      "min         1.000000       0.850000       0.000000\n",
      "25%         1.000000      39.900000      13.080000\n",
      "50%         1.000000      74.990000      16.260000\n",
      "75%         1.000000     134.900000      21.150000\n",
      "max        21.000000    6735.000000     409.680000 \n",
      "\n",
      "       payment_sequential  payment_installments  payment_value\n",
      "count       103886.000000         103886.000000  103886.000000\n",
      "mean             1.092679              2.853349     154.100380\n",
      "std              0.706584              2.687051     217.494064\n",
      "min              1.000000              0.000000       0.000000\n",
      "25%              1.000000              1.000000      56.790000\n",
      "50%              1.000000              1.000000     100.000000\n",
      "75%              1.000000              4.000000     171.837500\n",
      "max             29.000000             24.000000   13664.080000 \n",
      "\n",
      "       review_score\n",
      "count  99224.000000\n",
      "mean       4.086421\n",
      "std        1.347579\n",
      "min        1.000000\n",
      "25%        4.000000\n",
      "50%        5.000000\n",
      "75%        5.000000\n",
      "max        5.000000 \n",
      "\n",
      "       product_category_name product_category_name_english\n",
      "count                     71                            71\n",
      "unique                    71                            71\n",
      "top             beleza_saude                 health_beauty\n",
      "freq                       1                             1 \n",
      "\n",
      "       product_name_lenght  product_description_lenght  product_photos_qty  \\\n",
      "count         32340.000000                32340.000000        32340.000000   \n",
      "mean             48.476592                  771.492393            2.188961   \n",
      "std              10.245699                  635.124831            1.736787   \n",
      "min               5.000000                    4.000000            1.000000   \n",
      "25%              42.000000                  339.000000            1.000000   \n",
      "50%              51.000000                  595.000000            1.000000   \n",
      "75%              57.000000                  972.000000            3.000000   \n",
      "max              76.000000                 3992.000000           20.000000   \n",
      "\n",
      "       product_weight_g  product_length_cm  product_height_cm  \\\n",
      "count      32340.000000       32340.000000       32340.000000   \n",
      "mean        2276.956586          30.854545          16.958813   \n",
      "std         4279.291845          16.955965          13.636115   \n",
      "min            0.000000           7.000000           2.000000   \n",
      "25%          300.000000          18.000000           8.000000   \n",
      "50%          700.000000          25.000000          13.000000   \n",
      "75%         1900.000000          38.000000          21.000000   \n",
      "max        40425.000000         105.000000         105.000000   \n",
      "\n",
      "       product_width_cm  \n",
      "count      32340.000000  \n",
      "mean          23.208596  \n",
      "std           12.078762  \n",
      "min            6.000000  \n",
      "25%           15.000000  \n",
      "50%           20.000000  \n",
      "75%           30.000000  \n",
      "max          118.000000   \n",
      "\n",
      "       seller_zip_code_prefix\n",
      "count             3095.000000\n",
      "mean             32291.059451\n",
      "std              32713.453830\n",
      "min               1001.000000\n",
      "25%               7093.500000\n",
      "50%              14940.000000\n",
      "75%              64552.500000\n",
      "max              99730.000000 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in [orders,customer,geolocation,order_item,order_payment,order_review,product_category_name_translation,product,seller]:\n",
    "    print(i.describe(),'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "866de7fc-9ac3-4afd-a2b1-29ad08af9882",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(72783, 8) \n",
      "\n",
      "(99441, 5) \n",
      "\n",
      "(1000163, 5) \n",
      "\n",
      "(112650, 7) \n",
      "\n",
      "(103886, 5) \n",
      "\n",
      "(99224, 7) \n",
      "\n",
      "(71, 2) \n",
      "\n",
      "(32340, 9) \n",
      "\n",
      "(3095, 4) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Check again\n",
    "\n",
    "for i in [orders,customer,geolocation,order_item,order_payment,order_review,product_category_name_translation,product,seller]:\n",
    "    print(i.shape,'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "75776bd8-957c-4b30-b366-c85eaba9c1d6",
   "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>product_id</th>\n",
       "      <th>product_category_name</th>\n",
       "      <th>product_name_lenght</th>\n",
       "      <th>product_description_lenght</th>\n",
       "      <th>product_photos_qty</th>\n",
       "      <th>product_weight_g</th>\n",
       "      <th>product_length_cm</th>\n",
       "      <th>product_height_cm</th>\n",
       "      <th>product_width_cm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1e9e8ef04dbcff4541ed26657ea517e5</td>\n",
       "      <td>perfumaria</td>\n",
       "      <td>40.0</td>\n",
       "      <td>287.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3aa071139cb16b67ca9e5dea641aaa2f</td>\n",
       "      <td>artes</td>\n",
       "      <td>44.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>96bd76ec8810374ed1b65e291975717f</td>\n",
       "      <td>esporte_lazer</td>\n",
       "      <td>46.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cef67bcfe19066a932b7673e239eb23d</td>\n",
       "      <td>bebes</td>\n",
       "      <td>27.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9dc1a7de274444849c219cff195d0b71</td>\n",
       "      <td>utilidades_domesticas</td>\n",
       "      <td>37.0</td>\n",
       "      <td>402.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>625.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32946</th>\n",
       "      <td>a0b7d5a992ccda646f2d34e418fff5a0</td>\n",
       "      <td>moveis_decoracao</td>\n",
       "      <td>45.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12300.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32947</th>\n",
       "      <td>bf4538d88321d0fd4412a93c974510e6</td>\n",
       "      <td>construcao_ferramentas_iluminacao</td>\n",
       "      <td>41.0</td>\n",
       "      <td>971.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32948</th>\n",
       "      <td>9a7c6041fa9592d9d9ef6cfe62a71f8c</td>\n",
       "      <td>cama_mesa_banho</td>\n",
       "      <td>50.0</td>\n",
       "      <td>799.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32949</th>\n",
       "      <td>83808703fc0706a22e264b9d75f04a2e</td>\n",
       "      <td>informatica_acessorios</td>\n",
       "      <td>60.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32950</th>\n",
       "      <td>106392145fca363410d287a815be6de4</td>\n",
       "      <td>cama_mesa_banho</td>\n",
       "      <td>58.0</td>\n",
       "      <td>309.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2083.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32340 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             product_id              product_category_name  \\\n",
       "0      1e9e8ef04dbcff4541ed26657ea517e5                         perfumaria   \n",
       "1      3aa071139cb16b67ca9e5dea641aaa2f                              artes   \n",
       "2      96bd76ec8810374ed1b65e291975717f                      esporte_lazer   \n",
       "3      cef67bcfe19066a932b7673e239eb23d                              bebes   \n",
       "4      9dc1a7de274444849c219cff195d0b71              utilidades_domesticas   \n",
       "...                                 ...                                ...   \n",
       "32946  a0b7d5a992ccda646f2d34e418fff5a0                   moveis_decoracao   \n",
       "32947  bf4538d88321d0fd4412a93c974510e6  construcao_ferramentas_iluminacao   \n",
       "32948  9a7c6041fa9592d9d9ef6cfe62a71f8c                    cama_mesa_banho   \n",
       "32949  83808703fc0706a22e264b9d75f04a2e             informatica_acessorios   \n",
       "32950  106392145fca363410d287a815be6de4                    cama_mesa_banho   \n",
       "\n",
       "       product_name_lenght  product_description_lenght  product_photos_qty  \\\n",
       "0                     40.0                       287.0                 1.0   \n",
       "1                     44.0                       276.0                 1.0   \n",
       "2                     46.0                       250.0                 1.0   \n",
       "3                     27.0                       261.0                 1.0   \n",
       "4                     37.0                       402.0                 4.0   \n",
       "...                    ...                         ...                 ...   \n",
       "32946                 45.0                        67.0                 2.0   \n",
       "32947                 41.0                       971.0                 1.0   \n",
       "32948                 50.0                       799.0                 1.0   \n",
       "32949                 60.0                       156.0                 2.0   \n",
       "32950                 58.0                       309.0                 1.0   \n",
       "\n",
       "       product_weight_g  product_length_cm  product_height_cm  \\\n",
       "0                 225.0               16.0               10.0   \n",
       "1                1000.0               30.0               18.0   \n",
       "2                 154.0               18.0                9.0   \n",
       "3                 371.0               26.0                4.0   \n",
       "4                 625.0               20.0               17.0   \n",
       "...                 ...                ...                ...   \n",
       "32946           12300.0               40.0               40.0   \n",
       "32947            1700.0               16.0               19.0   \n",
       "32948            1400.0               27.0                7.0   \n",
       "32949             700.0               31.0               13.0   \n",
       "32950            2083.0               12.0                2.0   \n",
       "\n",
       "       product_width_cm  \n",
       "0                  14.0  \n",
       "1                  20.0  \n",
       "2                  15.0  \n",
       "3                  26.0  \n",
       "4                  13.0  \n",
       "...                 ...  \n",
       "32946              40.0  \n",
       "32947              16.0  \n",
       "32948              27.0  \n",
       "32949              20.0  \n",
       "32950               7.0  \n",
       "\n",
       "[32340 rows x 9 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4b02cb48-88fd-4167-93a2-c957a0021eaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Output the CSV \n",
    "\n",
    "orders.to_csv('20621098.csv', index=False)\n",
    "customer.to_csv('customer.csv', index=False)\n",
    "geolocation.to_csv('geolocation.csv', index=False)\n",
    "order_item.to_csv('order_item.csv', index=False)\n",
    "order_payment.to_csv('order_payment.csv', index=False)\n",
    "order_review.to_csv('order_review.csv', index=False)\n",
    "product_category_name_translation.to_csv('product_category_name_translation.csv', index=False)\n",
    "product.to_csv('product.csv', index=False)\n",
    "seller.to_csv('seller.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3bb2e58f-e0e5-4025-b0b7-09bc5531d58d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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