lab2.1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ideal-presentation",
   "metadata": {},
   "source": [
    "### Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "acoustic-visit",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "import gc\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "import pickle\n",
    "import bz2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "crude-throat",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "09.csv\t\t     10.csv  products_20200901.txt  products_20201101.txt\r\n",
      "09_prepared.pkl.bz2  11.csv  products_20201001.txt\r\n"
     ]
    }
   ],
   "source": [
    "data_path = Path('./data/').resolve()\n",
    "!ls {data_path}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bibliographic-duration",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3,8G\t/data/Projects/inno_stats/data/09.csv\n",
      "4,1G\t/data/Projects/inno_stats/data/10.csv\n",
      "4,2G\t/data/Projects/inno_stats/data/11.csv\n"
     ]
    }
   ],
   "source": [
    "!du -sh {data_path / '09.csv'}\n",
    "!du -sh {data_path / '10.csv'}\n",
    "!du -sh {data_path / '11.csv'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "double-occurrence",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = data_path/'09.csv' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fuzzy-powder",
   "metadata": {},
   "outputs": [],
   "source": [
    "# sed -i '274011d' 10.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "intimate-istanbul",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>id_doc</th>\n",
       "      <th>id_order</th>\n",
       "      <th>id_card</th>\n",
       "      <th>id_tov</th>\n",
       "      <th>id_kontr</th>\n",
       "      <th>quantity</th>\n",
       "      <th>sum</th>\n",
       "      <th>is_green</th>\n",
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       "      <th>0</th>\n",
       "      <td>2020-09-01 17:01:25</td>\n",
       "      <td>0E05D308-5CEC-EA11-B444-005056A7539A</td>\n",
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       "      <td>8594499</td>\n",
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       "      <td>271.0</td>\n",
       "      <td>1,000</td>\n",
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       "      <th>2</th>\n",
       "      <td>2020-09-01 19:19:21</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-09-01 21:53:34</td>\n",
       "      <td>EB6C71A3-84EC-EA11-B444-005056A7539A</td>\n",
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       "      <td>2491281</td>\n",
       "      <td>52</td>\n",
       "      <td>271.0</td>\n",
       "      <td>1,000</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-09-01 18:42:31</td>\n",
       "      <td>0706023F-6BEC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>5732396</td>\n",
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       "      <td>97.0</td>\n",
       "      <td>2,000</td>\n",
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      "text/plain": [
       "                 date                                id_doc  id_order  \\\n",
       "0 2020-09-01 17:01:25  0E05D308-5CEC-EA11-B444-005056A7539A         0   \n",
       "1 2020-09-01 17:35:36  610205A1-61EC-EA11-B444-005056A7539A         0   \n",
       "2 2020-09-01 19:19:21  8AF19602-70EC-EA11-B444-005056A7539A         0   \n",
       "3 2020-09-01 21:53:34  EB6C71A3-84EC-EA11-B444-005056A7539A         0   \n",
       "4 2020-09-01 18:42:31  0706023F-6BEC-EA11-B444-005056A7539A         0   \n",
       "\n",
       "      id_card  id_tov  id_kontr quantity     sum  is_green  \n",
       "0  8594499         52     271.0    1,000     108         0  \n",
       "1  1452388         52     271.0    1,000     108         0  \n",
       "2  3493538         52     271.0    1,000  107,95         0  \n",
       "3  2491281         52     271.0    1,000     108         0  \n",
       "4  5732396         61      97.0    2,000      88         0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(file_path, sep=';',\n",
    "                 parse_dates=['date'], \n",
    "                 infer_datetime_format=True, \n",
    "                 dtype={'id_doc':'category', 'id_card':'category'}\n",
    "                )\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "demanding-cambridge",
   "metadata": {},
   "outputs": [
    {
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       "      <th>id_tov</th>\n",
       "      <th>id_kontr</th>\n",
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       "      <td>271.0</td>\n",
       "      <td>1,000</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-09-01 19:19:21</td>\n",
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       "    <tr>\n",
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       "      <td>2020-09-01 21:53:34</td>\n",
       "      <td>EB6C71A3-84EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>2491281</td>\n",
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       "      <td>271.0</td>\n",
       "      <td>1,000</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-09-01 18:42:31</td>\n",
       "      <td>0706023F-6BEC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>5732396</td>\n",
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       "      <td>97.0</td>\n",
       "      <td>2,000</td>\n",
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      "text/plain": [
       "                 date                                id_doc  id_order  \\\n",
       "0 2020-09-01 17:01:25  0E05D308-5CEC-EA11-B444-005056A7539A         0   \n",
       "1 2020-09-01 17:35:36  610205A1-61EC-EA11-B444-005056A7539A         0   \n",
       "2 2020-09-01 19:19:21  8AF19602-70EC-EA11-B444-005056A7539A         0   \n",
       "3 2020-09-01 21:53:34  EB6C71A3-84EC-EA11-B444-005056A7539A         0   \n",
       "4 2020-09-01 18:42:31  0706023F-6BEC-EA11-B444-005056A7539A         0   \n",
       "\n",
       "      id_card  id_tov  id_kontr quantity     sum  is_green  \n",
       "0  8594499         52     271.0    1,000     108         0  \n",
       "1  1452388         52     271.0    1,000     108         0  \n",
       "2  3493538         52     271.0    1,000  107,95         0  \n",
       "3  2491281         52     271.0    1,000     108         0  \n",
       "4  5732396         61      97.0    2,000      88         0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "coordinated-campbell",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date        datetime64[ns]\n",
       "id_doc            category\n",
       "id_order             int64\n",
       "id_card           category\n",
       "id_tov               int64\n",
       "id_kontr           float64\n",
       "quantity            object\n",
       "sum                 object\n",
       "is_green             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "promising-bridges",
   "metadata": {},
   "outputs": [],
   "source": [
    "na_int_val = -9999\n",
    "df['quantity'] = df['quantity'].str.replace(',', '.').astype(float)\n",
    "df['sum'] = df['sum'].str.replace(',', '.').astype(float)\n",
    "df['is_green'] = df['is_green'].astype('bool')\n",
    "df['id_kontr'] = df['id_kontr'].fillna(na_int_val).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fundamental-advancement",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date        datetime64[ns]\n",
       "id_doc            category\n",
       "id_order             int64\n",
       "id_card           category\n",
       "id_tov               int64\n",
       "id_kontr             int64\n",
       "quantity           float64\n",
       "sum                float64\n",
       "is_green              bool\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "threaded-primary",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['id_card'] = df['id_card'].str.strip()\n",
    "df['id_doc'] = df['id_doc'].str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "editorial-roman",
   "metadata": {},
   "outputs": [
    {
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       "      <td>52</td>\n",
       "      <td>271</td>\n",
       "      <td>1.0</td>\n",
       "      <td>108.00</td>\n",
       "      <td>False</td>\n",
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       "      <th>6</th>\n",
       "      <td>2020-09-01 19:50:31</td>\n",
       "      <td>1B34A539-74EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>4119786</td>\n",
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       "      <td>97</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.00</td>\n",
       "      <td>False</td>\n",
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      "text/plain": [
       "                 date                                id_doc  id_order  \\\n",
       "0 2020-09-01 17:01:25  0E05D308-5CEC-EA11-B444-005056A7539A         0   \n",
       "1 2020-09-01 17:35:36  610205A1-61EC-EA11-B444-005056A7539A         0   \n",
       "2 2020-09-01 19:19:21  8AF19602-70EC-EA11-B444-005056A7539A         0   \n",
       "3 2020-09-01 21:53:34  EB6C71A3-84EC-EA11-B444-005056A7539A         0   \n",
       "6 2020-09-01 19:50:31  1B34A539-74EC-EA11-B444-005056A7539A         0   \n",
       "\n",
       "   id_card  id_tov  id_kontr  quantity     sum  is_green  \n",
       "0  8594499      52       271       1.0  108.00     False  \n",
       "1  1452388      52       271       1.0  108.00     False  \n",
       "2  3493538      52       271       1.0  107.95     False  \n",
       "3  2491281      52       271       1.0  108.00     False  \n",
       "6  4119786      61        97       1.0   56.00     False  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "divine-auction",
   "metadata": {},
   "outputs": [
    {
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       "      <th>id_card</th>\n",
       "      <th>id_tov</th>\n",
       "      <th>id_kontr</th>\n",
       "      <th>quantity</th>\n",
       "      <th>sum</th>\n",
       "      <th>is_green</th>\n",
       "      <th>id_card_int</th>\n",
       "      <th>id_doc_int</th>\n",
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       "      <td>0E05D308-5CEC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>8594499</td>\n",
       "      <td>52</td>\n",
       "      <td>271</td>\n",
       "      <td>1.0</td>\n",
       "      <td>108.00</td>\n",
       "      <td>False</td>\n",
       "      <td>1087018</td>\n",
       "      <td>386563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-09-01 17:35:36</td>\n",
       "      <td>610205A1-61EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>1452388</td>\n",
       "      <td>52</td>\n",
       "      <td>271</td>\n",
       "      <td>1.0</td>\n",
       "      <td>108.00</td>\n",
       "      <td>False</td>\n",
       "      <td>199266</td>\n",
       "      <td>2676152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-09-01 19:19:21</td>\n",
       "      <td>8AF19602-70EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>3493538</td>\n",
       "      <td>52</td>\n",
       "      <td>271</td>\n",
       "      <td>1.0</td>\n",
       "      <td>107.95</td>\n",
       "      <td>False</td>\n",
       "      <td>444332</td>\n",
       "      <td>3832560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-09-01 21:53:34</td>\n",
       "      <td>EB6C71A3-84EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>2491281</td>\n",
       "      <td>52</td>\n",
       "      <td>271</td>\n",
       "      <td>1.0</td>\n",
       "      <td>108.00</td>\n",
       "      <td>False</td>\n",
       "      <td>325059</td>\n",
       "      <td>6489899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-09-01 19:50:31</td>\n",
       "      <td>1B34A539-74EC-EA11-B444-005056A7539A</td>\n",
       "      <td>0</td>\n",
       "      <td>4119786</td>\n",
       "      <td>61</td>\n",
       "      <td>97</td>\n",
       "      <td>1.0</td>\n",
       "      <td>56.00</td>\n",
       "      <td>False</td>\n",
       "      <td>533043</td>\n",
       "      <td>750155</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 date                                id_doc  id_order  \\\n",
       "0 2020-09-01 17:01:25  0E05D308-5CEC-EA11-B444-005056A7539A         0   \n",
       "1 2020-09-01 17:35:36  610205A1-61EC-EA11-B444-005056A7539A         0   \n",
       "2 2020-09-01 19:19:21  8AF19602-70EC-EA11-B444-005056A7539A         0   \n",
       "3 2020-09-01 21:53:34  EB6C71A3-84EC-EA11-B444-005056A7539A         0   \n",
       "6 2020-09-01 19:50:31  1B34A539-74EC-EA11-B444-005056A7539A         0   \n",
       "\n",
       "   id_card  id_tov  id_kontr  quantity     sum  is_green  id_card_int  \\\n",
       "0  8594499      52       271       1.0  108.00     False      1087018   \n",
       "1  1452388      52       271       1.0  108.00     False       199266   \n",
       "2  3493538      52       271       1.0  107.95     False       444332   \n",
       "3  2491281      52       271       1.0  108.00     False       325059   \n",
       "6  4119786      61        97       1.0   56.00     False       533043   \n",
       "\n",
       "   id_doc_int  \n",
       "0      386563  \n",
       "1     2676152  \n",
       "2     3832560  \n",
       "3     6489899  \n",
       "6      750155  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lbe_card = LabelEncoder()\n",
    "lbe_doc = LabelEncoder()\n",
    "\n",
    "lbe_card.fit(df['id_card'])\n",
    "df['id_card_int'] = lbe_card.transform(df['id_card'])\n",
    "\n",
    "lbe_doc.fit(df['id_doc'])\n",
    "df['id_doc_int'] = lbe_doc.transform(df['id_doc'])\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "continuing-powell",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date           datetime64[ns]\n",
       "id_doc                 object\n",
       "id_order                int64\n",
       "id_card                object\n",
       "id_tov                  int64\n",
       "id_kontr                int64\n",
       "quantity              float64\n",
       "sum                   float64\n",
       "is_green                 bool\n",
       "id_card_int             int64\n",
       "id_doc_int              int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "provincial-newport",
   "metadata": {},
   "outputs": [],
   "source": [
    "with bz2.open(data_path / '09_prepared.pkl.bz2', 'wb') as f:\n",
    "    pickle.dump(df, f, protocol=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "excited-austria",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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