eda.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b752b165",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1c79782c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Please provide your password: ········\n",
      "Connected.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import psycopg2\n",
    "import getpass\n",
    "import pandas.io.sql as psql\n",
    "\n",
    "password = getpass.getpass(\"Please provide your password: \")\n",
    "conn = psycopg2.connect(\n",
    "    host=\"pg.analytics.northwestern.edu\",\n",
    "    database=\"everything2023\",\n",
    "    user=\"bvt1891\", # change here!\n",
    "    password=password)\n",
    "print(\"Connected.\")\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "202d43cd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/251906476.py:2: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  print(psql.read_sql(query, conn))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       count\n",
      "0  120916896\n"
     ]
    }
   ],
   "source": [
    "query = \"\"\"SELECT count(*) from group_4.trnsact\"\"\"\n",
    "print(psql.read_sql(query, conn))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "78cdd922",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/3929071350.py:2: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  trnsact_df = psql.read_sql(query,conn)\n"
     ]
    },
    {
     "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>register</th>\n",
       "      <th>trannum</th>\n",
       "      <th>interid</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>seq</th>\n",
       "      <th>mic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1217607</td>\n",
       "      <td>1002</td>\n",
       "      <td>160</td>\n",
       "      <td>1600</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-07-23</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>328800053</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7437469</td>\n",
       "      <td>4104</td>\n",
       "      <td>410</td>\n",
       "      <td>2400</td>\n",
       "      <td>0</td>\n",
       "      <td>2004-12-23</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>42500207</td>\n",
       "      <td>562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9242227</td>\n",
       "      <td>4409</td>\n",
       "      <td>750</td>\n",
       "      <td>2800</td>\n",
       "      <td>0</td>\n",
       "      <td>2004-11-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>436000013</td>\n",
       "      <td>400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8377230</td>\n",
       "      <td>3003</td>\n",
       "      <td>120</td>\n",
       "      <td>2400</td>\n",
       "      <td>0</td>\n",
       "      <td>2004-11-27</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>935700120</td>\n",
       "      <td>457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5758109</td>\n",
       "      <td>4802</td>\n",
       "      <td>540</td>\n",
       "      <td>3700</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-07-05</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>18.5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>297800043</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store  register  trannum  interid    saledate stype  quantity  \\\n",
       "0  1217607   1002       160     1600        0  2005-07-23     P         1   \n",
       "1  7437469   4104       410     2400        0  2004-12-23     P         1   \n",
       "2  9242227   4409       750     2800        0  2004-11-09     P         1   \n",
       "3  8377230   3003       120     2400        0  2004-11-27     P         1   \n",
       "4  5758109   4802       540     3700        0  2005-07-05     P         1   \n",
       "\n",
       "   orgprice   amt        seq  mic  \n",
       "0      56.0  42.0  328800053   45  \n",
       "1      40.0  40.0   42500207  562  \n",
       "2       6.0   3.0  436000013  400  \n",
       "3      16.0  16.0  935700120  457  \n",
       "4      18.5  18.5  297800043  281  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = \"\"\"SELECT * from group_4.trnsact order by random() LIMIT 1000000\"\"\"\n",
    "trnsact_df = psql.read_sql(query,conn)\n",
    "trnsact_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "459fd2bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2005, 8, 27)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trnsact_df.saledate.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8669928c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2005, 8, 27)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trnsact_df.saledate.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6872b903",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/2721569316.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  strinfo_df = psql.read_sql(\"select * from group_4.strinfo\", conn)\n"
     ]
    },
    {
     "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>store</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>ST. PETERSBURG</td>\n",
       "      <td>FL</td>\n",
       "      <td>33710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>ST. LOUIS</td>\n",
       "      <td>MO</td>\n",
       "      <td>63126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>LITTLE ROCK</td>\n",
       "      <td>AR</td>\n",
       "      <td>72201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>FORT WORTH</td>\n",
       "      <td>TX</td>\n",
       "      <td>76137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>TEMPE</td>\n",
       "      <td>AZ</td>\n",
       "      <td>85281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   store            city state    zip\n",
       "0      2  ST. PETERSBURG    FL  33710\n",
       "1      3       ST. LOUIS    MO  63126\n",
       "2      4     LITTLE ROCK    AR  72201\n",
       "3      7      FORT WORTH    TX  76137\n",
       "4      9           TEMPE    AZ  85281"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strinfo_df = psql.read_sql(\"select * from group_4.strinfo\", conn)\n",
    "strinfo_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cc64054f",
   "metadata": {},
   "outputs": [],
   "source": [
    "trnsact_store_df = pd.merge(trnsact_df, strinfo_df, on='store', how='left')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "728774db",
   "metadata": {},
   "source": [
    "### Top Selling States"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "75dca2ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state\n",
       "TX    5564009.12\n",
       "FL    3435391.28\n",
       "LA    1420495.11\n",
       "OH    1324056.37\n",
       "AZ    1255785.47\n",
       "TN     952154.98\n",
       "OK     881879.30\n",
       "MO     877461.90\n",
       "AR     840495.58\n",
       "AL     779322.11\n",
       "Name: amt, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trnsact_store_df.groupby('state')['amt'].sum().sort_values(ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fc2eadd",
   "metadata": {},
   "source": [
    "With 100 million+ rows, loading the entire dataset is impractical due to its size. Instead, we'll focus on Texas transactions and limit the analysis to a specific one-year period, analyzing the state with the highest sales within a randomly selected subset of 10 million entries. Also, analyzing sales within the same location aids future predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bde06496",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/19278194.py:5: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  trnsact_df = psql.read_sql(query,conn)\n"
     ]
    },
    {
     "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>register</th>\n",
       "      <th>trannum</th>\n",
       "      <th>interid</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>seq</th>\n",
       "      <th>mic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>190</td>\n",
       "      <td>4400</td>\n",
       "      <td>532904186</td>\n",
       "      <td>2005-07-07</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>691000054</td>\n",
       "      <td>557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>260</td>\n",
       "      <td>4000</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-05-24</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>252300048</td>\n",
       "      <td>557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>390</td>\n",
       "      <td>2200</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>451300098</td>\n",
       "      <td>557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>390</td>\n",
       "      <td>2200</td>\n",
       "      <td>290609039</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>69800047</td>\n",
       "      <td>557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>390</td>\n",
       "      <td>2400</td>\n",
       "      <td>0</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>18700042</td>\n",
       "      <td>557</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store  register  trannum    interid    saledate stype  quantity  \\\n",
       "0  5148332   1007       190     4400  532904186  2005-07-07     P         1   \n",
       "1  5148332   1007       260     4000          0  2005-05-24     P         1   \n",
       "2  5148332   1007       390     2200          0  2005-04-09     P         1   \n",
       "3  5148332   1007       390     2200  290609039  2005-05-29     P         1   \n",
       "4  5148332   1007       390     2400          0  2005-06-12     R         1   \n",
       "\n",
       "   orgprice   amt        seq  mic  \n",
       "0      50.0  33.5  691000054  557  \n",
       "1      50.0  50.0  252300048  557  \n",
       "2      50.0  50.0  451300098  557  \n",
       "3      50.0  50.0   69800047  557  \n",
       "4      50.0  50.0   18700042  557  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = \"\"\" SELECT t.*\n",
    "            FROM group_4.trnsact t\n",
    "            LEFT JOIN group_4.strinfo s ON t.store = s.store\n",
    "            WHERE s.state = 'TX' \"\"\"\n",
    "trnsact_df = psql.read_sql(query,conn)\n",
    "trnsact_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a3335bda",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/2049765761.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  sku_df = psql.read_sql(\"select * from group_4.skuinfo\", conn)\n"
     ]
    }
   ],
   "source": [
    "sku_df = psql.read_sql(\"select * from group_4.skuinfo\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "92d070c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "trnsact_sku_df = pd.merge(trnsact_df, sku_df, on='sku', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2bcd7667",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/2620855017.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  skst_df = psql.read_sql(\"select * from group_4.skstinfo\", conn)\n"
     ]
    }
   ],
   "source": [
    "skst_df = psql.read_sql(\"select * from group_4.skstinfo\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "709fcf5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/2636067228.py:1: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
      "  dept_df = psql.read_sql(\"select * from group_4.deptinfo\", conn)\n"
     ]
    }
   ],
   "source": [
    "dept_df = psql.read_sql(\"select * from group_4.deptinfo\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "32cf9c31",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Close the cursor\n",
    "cur.close()\n",
    "# Close the database connection\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ecddfca5",
   "metadata": {},
   "outputs": [
    {
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       "<p>26917532 rows × 23 columns</p>\n",
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      ],
      "text/plain": [
       "              sku  store  register  trannum    interid    saledate stype  \\\n",
       "0         5148332   1007       190     4400  532904186  2005-07-07     P   \n",
       "1         5148332   1007       260     4000          0  2005-05-24     P   \n",
       "2         5148332   1007       390     2200          0  2005-04-09     P   \n",
       "3         5148332   1007       390     2200  290609039  2005-05-29     P   \n",
       "4         5148332   1007       390     2400          0  2005-06-12     R   \n",
       "...           ...    ...       ...      ...        ...         ...   ...   \n",
       "26917527  5148332    907       400      300  850107029  2005-06-28     P   \n",
       "26917528  5148332    907       400     1500  915307232  2005-07-03     P   \n",
       "26917529  5148332    907       400     6400  248704549  2005-07-01     P   \n",
       "26917530  5148332   1007       170     3700  847708909  2005-06-18     P   \n",
       "26917531  5148332   1007       170     5300          0  2005-06-25     P   \n",
       "\n",
       "          quantity  orgprice   amt  ...  classid              upc  \\\n",
       "0                1      50.0  33.5  ...      815  000400008332514   \n",
       "1                1      50.0  50.0  ...      815  000400008332514   \n",
       "2                1      50.0  50.0  ...      815  000400008332514   \n",
       "3                1      50.0  50.0  ...      815  000400008332514   \n",
       "4                1      50.0  50.0  ...      815  000400008332514   \n",
       "...            ...       ...   ...  ...      ...              ...   \n",
       "26917527         1      50.0  50.0  ...      815  000400008332514   \n",
       "26917528         1      50.0  33.5  ...      815  000400008332514   \n",
       "26917529         1      50.0  33.5  ...      815  000400008332514   \n",
       "26917530         1      50.0  50.0  ...      815  000400008332514   \n",
       "26917531         1      50.0  50.0  ...      815  000400008332514   \n",
       "\n",
       "                 style  color size packsize   vendor     brand  cost retail  \n",
       "0         5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "1         5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "2         5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "3         5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "4         5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "...                ...    ...  ...      ...      ...       ...   ...    ...  \n",
       "26917527  5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  12.0   25.0  \n",
       "26917528  5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  12.0   25.0  \n",
       "26917529  5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  12.0   25.0  \n",
       "26917530  5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "26917531  5     LX1J90  BLACK  18W      1.0  5316219  LIZ CLAI  14.4   12.5  \n",
       "\n",
       "[26917532 rows x 23 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tx_transation_df = pd.merge(trnsact_sku_df, skst_df, on = ['sku','store'], how='left')\n",
    "tx_transation_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e4f31f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dept        False\n",
       "deptdesc    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dept_df.head().isna().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c6c4f8bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "tx_transation_df = pd.merge(tx_transation_df, dept_df, on= 'dept')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "40f5815c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['sku', 'store', 'register', 'trannum', 'interid', 'saledate', 'stype',\n",
       "       'quantity', 'orgprice', 'amt', 'seq', 'mic', 'dept', 'classid', 'upc',\n",
       "       'style', 'color', 'size', 'packsize', 'vendor', 'brand', 'cost',\n",
       "       'retail', 'deptdesc'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tx_transation_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a171c96f",
   "metadata": {},
   "outputs": [
    {
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       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store    saledate stype  quantity  orgprice   amt    dept  \\\n",
       "0  5148332   1007  2005-07-07     P         1      50.0  33.5  9801.0   \n",
       "1  5148332   1007  2005-05-24     P         1      50.0  50.0  9801.0   \n",
       "2  5148332   1007  2005-04-09     P         1      50.0  50.0  9801.0   \n",
       "3  5148332   1007  2005-05-29     P         1      50.0  50.0  9801.0   \n",
       "4  5148332   1007  2005-06-12     R         1      50.0  50.0  9801.0   \n",
       "\n",
       "               upc         style  color size  packsize   vendor     brand  \\\n",
       "0  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "1  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "2  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "3  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "4  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "\n",
       "   cost  retail deptdesc  \n",
       "0  14.4    12.5  CATALIN  \n",
       "1  14.4    12.5  CATALIN  \n",
       "2  14.4    12.5  CATALIN  \n",
       "3  14.4    12.5  CATALIN  \n",
       "4  14.4    12.5  CATALIN  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop columns\n",
    "columns_to_drop = ['register', 'trannum', 'interid', 'seq', 'mic', 'classid']\n",
    "tx_transation_df = tx_transation_df.drop(columns=columns_to_drop)\n",
    "tx_transation_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "efac4e3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2004, 8, 1)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tx_transation_df.saledate.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a2ad1a6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.date(2005, 8, 27)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tx_transation_df.saledate.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "61ab26f0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sku                0\n",
       "store              0\n",
       "saledate           0\n",
       "stype              0\n",
       "quantity           0\n",
       "orgprice           0\n",
       "amt                0\n",
       "dept               0\n",
       "upc                0\n",
       "style              0\n",
       "color              0\n",
       "size               0\n",
       "packsize           0\n",
       "vendor             0\n",
       "brand          74939\n",
       "cost        12939826\n",
       "retail      12939826\n",
       "deptdesc           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count missing values in each column\n",
    "tx_transation_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5de0bb9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "303671"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tx_transation_df[(tx_transation_df['orgprice'] == 0) | (tx_transation_df['amt'] == 0)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "20847dc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66087"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tx_transation_df[tx_transation_df['orgprice'] < tx_transation_df['amt']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3596c018",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10835"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tx_transation_df[tx_transation_df['orgprice'] < tx_transation_df['cost']])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6afc8daf",
   "metadata": {},
   "source": [
    "### Observation\n",
    "We observed instances where the original price or the amount the client actually paid was recorded as zero. Furthermore, there are cases where the amount the client actually paid exceeds the original price, suggesting potential mislabeling of the original prices. To rectify this issue, we will proceed to eliminate these inaccurate entries and ignore items with overpriced tags due to unforeseen events, such as the celebrity effect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0e9eabad",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_df = tx_transation_df[~((tx_transation_df['orgprice'] == 0) \n",
    "                               | (tx_transation_df['amt'] == 0)\n",
    "                               | (tx_transation_df['cost'] == 0)\n",
    "                               | (tx_transation_df['orgprice'] < tx_transation_df['amt'])\n",
    "                               | (tx_transation_df['orgprice'] < tx_transation_df['cost']))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3a3e1a67",
   "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>dept</th>\n",
       "      <th>upc</th>\n",
       "      <th>style</th>\n",
       "      <th>color</th>\n",
       "      <th>size</th>\n",
       "      <th>packsize</th>\n",
       "      <th>vendor</th>\n",
       "      <th>brand</th>\n",
       "      <th>cost</th>\n",
       "      <th>retail</th>\n",
       "      <th>deptdesc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-07-07</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-24</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>BLACK</td>\n",
       "      <td>18W</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5316219</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store    saledate stype  quantity  orgprice   amt    dept  \\\n",
       "0  5148332   1007  2005-07-07     P         1      50.0  33.5  9801.0   \n",
       "1  5148332   1007  2005-05-24     P         1      50.0  50.0  9801.0   \n",
       "2  5148332   1007  2005-04-09     P         1      50.0  50.0  9801.0   \n",
       "3  5148332   1007  2005-05-29     P         1      50.0  50.0  9801.0   \n",
       "4  5148332   1007  2005-06-12     R         1      50.0  50.0  9801.0   \n",
       "\n",
       "               upc         style  color size  packsize   vendor     brand  \\\n",
       "0  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "1  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "2  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "3  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "4  000400008332514  5     LX1J90  BLACK  18W       1.0  5316219  LIZ CLAI   \n",
       "\n",
       "   cost  retail deptdesc  \n",
       "0  14.4    12.5  CATALIN  \n",
       "1  14.4    12.5  CATALIN  \n",
       "2  14.4    12.5  CATALIN  \n",
       "3  14.4    12.5  CATALIN  \n",
       "4  14.4    12.5  CATALIN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8648680c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26482728"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(clean_tx_transation_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1462925",
   "metadata": {},
   "source": [
    "### Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3e470049",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>dept</th>\n",
       "      <th>packsize</th>\n",
       "      <th>cost</th>\n",
       "      <th>retail</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>2.648273e+07</td>\n",
       "      <td>1.360839e+07</td>\n",
       "      <td>1.360839e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.962241e+06</td>\n",
       "      <td>3.707842e+03</td>\n",
       "      <td>1.000005e+00</td>\n",
       "      <td>3.768172e+01</td>\n",
       "      <td>2.530263e+01</td>\n",
       "      <td>4.248069e+03</td>\n",
       "      <td>2.001387e+00</td>\n",
       "      <td>1.535346e+01</td>\n",
       "      <td>2.205710e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.849171e+06</td>\n",
       "      <td>2.460020e+03</td>\n",
       "      <td>1.773008e-02</td>\n",
       "      <td>4.052786e+01</td>\n",
       "      <td>2.770898e+01</td>\n",
       "      <td>2.519215e+03</td>\n",
       "      <td>1.000671e+01</td>\n",
       "      <td>1.728327e+01</td>\n",
       "      <td>2.964233e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.070000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>8.000000e+02</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.602507e+06</td>\n",
       "      <td>1.807000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.750000e+01</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>2.102000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>7.250000e+00</td>\n",
       "      <td>9.500000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.838011e+06</td>\n",
       "      <td>3.207000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.900000e+01</td>\n",
       "      <td>1.850000e+01</td>\n",
       "      <td>4.402000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.110000e+01</td>\n",
       "      <td>1.700000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.394276e+06</td>\n",
       "      <td>4.807000e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.900000e+01</td>\n",
       "      <td>3.200000e+01</td>\n",
       "      <td>6.402000e+03</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.848000e+01</td>\n",
       "      <td>2.600000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.999997e+06</td>\n",
       "      <td>8.707000e+03</td>\n",
       "      <td>8.200000e+01</td>\n",
       "      <td>6.017000e+03</td>\n",
       "      <td>6.017000e+03</td>\n",
       "      <td>9.801000e+03</td>\n",
       "      <td>8.010000e+02</td>\n",
       "      <td>2.700000e+03</td>\n",
       "      <td>6.017000e+03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                sku         store      quantity      orgprice           amt  \\\n",
       "count  2.648273e+07  2.648273e+07  2.648273e+07  2.648273e+07  2.648273e+07   \n",
       "mean   4.962241e+06  3.707842e+03  1.000005e+00  3.768172e+01  2.530263e+01   \n",
       "std    2.849171e+06  2.460020e+03  1.773008e-02  4.052786e+01  2.770898e+01   \n",
       "min    3.000000e+00  1.070000e+02  1.000000e+00  1.000000e-02  1.000000e-02   \n",
       "25%    2.602507e+06  1.807000e+03  1.000000e+00  1.750000e+01  1.000000e+01   \n",
       "50%    4.838011e+06  3.207000e+03  1.000000e+00  2.900000e+01  1.850000e+01   \n",
       "75%    7.394276e+06  4.807000e+03  1.000000e+00  4.900000e+01  3.200000e+01   \n",
       "max    9.999997e+06  8.707000e+03  8.200000e+01  6.017000e+03  6.017000e+03   \n",
       "\n",
       "               dept      packsize          cost        retail  \n",
       "count  2.648273e+07  2.648273e+07  1.360839e+07  1.360839e+07  \n",
       "mean   4.248069e+03  2.001387e+00  1.535346e+01  2.205710e+01  \n",
       "std    2.519215e+03  1.000671e+01  1.728327e+01  2.964233e+01  \n",
       "min    8.000000e+02  1.000000e+00  1.000000e-02  0.000000e+00  \n",
       "25%    2.102000e+03  1.000000e+00  7.250000e+00  9.500000e+00  \n",
       "50%    4.402000e+03  1.000000e+00  1.110000e+01  1.700000e+01  \n",
       "75%    6.402000e+03  3.000000e+00  1.848000e+01  2.600000e+01  \n",
       "max    9.801000e+03  8.010000e+02  2.700000e+03  6.017000e+03  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Summary statistics for each numeric column in the DataFrame\n",
    "clean_tx_transation_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd9668b1",
   "metadata": {},
   "source": [
    "### Top Brands by Sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a25f857c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top Brands by Sales'}, xlabel='brand'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_brands = clean_tx_transation_df.groupby('brand')['amt'].sum().sort_values(ascending=False).head(10)\n",
    "top_brands.plot(kind='bar', title='Top Brands by Sales')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c3e26bb",
   "metadata": {},
   "source": [
    "### Sales Distribution by Transaction Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fae068d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Sales Distribution by Transaction Type'}, xlabel='stype'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Type of the transaction (Return or Purchase)\n",
    "# P: purchase, R: return\n",
    "clean_tx_transation_df.groupby('stype')['amt'].sum().plot(kind='bar', title='Sales Distribution by Transaction Type')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6585b60e",
   "metadata": {},
   "source": [
    "### Number of Items Sold per Brand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "247ccb3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Number of Items Sold per Brand'}, xlabel='brand'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "items_per_brand = clean_tx_transation_df.groupby('brand')['quantity'].sum().sort_values(ascending=False).head(10)\n",
    "items_per_brand.plot(kind='bar', title='Number of Items Sold per Brand')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e4da5ee",
   "metadata": {},
   "source": [
    "### Sales Over Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "bdf2bc66",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/3841723340.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['saledate'] = pd.to_datetime(clean_tx_transation_df['saledate'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Sales Over Time'}, xlabel='saledate'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['saledate'] = pd.to_datetime(clean_tx_transation_df['saledate'])\n",
    "sales_over_time = clean_tx_transation_df.groupby('saledate')['amt'].sum()\n",
    "sales_over_time.plot(title='Sales Over Time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6a439020",
   "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>saledate</th>\n",
       "      <th>amt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2004-12-23</td>\n",
       "      <td>4737332.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2004-12-18</td>\n",
       "      <td>4528319.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>2005-02-26</td>\n",
       "      <td>4503995.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>2005-08-06</td>\n",
       "      <td>4346092.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2004-12-21</td>\n",
       "      <td>4097551.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2004-09-13</td>\n",
       "      <td>904696.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>2005-01-24</td>\n",
       "      <td>892899.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2004-08-30</td>\n",
       "      <td>853285.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>2005-01-31</td>\n",
       "      <td>806936.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>2005-02-01</td>\n",
       "      <td>796606.92</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>389 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      saledate         amt\n",
       "143 2004-12-23  4737332.63\n",
       "138 2004-12-18  4528319.43\n",
       "207 2005-02-26  4503995.87\n",
       "367 2005-08-06  4346092.37\n",
       "141 2004-12-21  4097551.05\n",
       "..         ...         ...\n",
       "43  2004-09-13   904696.86\n",
       "174 2005-01-24   892899.15\n",
       "29  2004-08-30   853285.09\n",
       "181 2005-01-31   806936.86\n",
       "182 2005-02-01   796606.92\n",
       "\n",
       "[389 rows x 2 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_over_time.reset_index().sort_values('amt', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7da03462",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of U.S. Federal Holidays:\n",
      "2004-09-06\n",
      "2004-10-11\n",
      "2004-11-11\n",
      "2004-11-25\n",
      "2004-12-24\n",
      "2004-12-31\n",
      "2005-01-17\n",
      "2005-02-21\n",
      "2005-05-30\n",
      "2005-07-04\n",
      "      saledate         amt\n",
      "143 2004-12-23  4737332.63\n",
      "138 2004-12-18  4528319.43\n",
      "207 2005-02-26  4503995.87\n",
      "367 2005-08-06  4346092.37\n",
      "141 2004-12-21  4097551.05\n",
      "..         ...         ...\n",
      "43  2004-09-13   904696.86\n",
      "174 2005-01-24   892899.15\n",
      "29  2004-08-30   853285.09\n",
      "181 2005-01-31   806936.86\n",
      "182 2005-02-01   796606.92\n",
      "\n",
      "[389 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "from pandas.tseries.holiday import USFederalHolidayCalendar\n",
    "cal = USFederalHolidayCalendar()\n",
    "holidays = cal.holidays(start=sales_over_time.index.min().strftime('%Y-%m-%d'), \n",
    "                        end=sales_over_time.index.max().strftime('%Y-%m-%d')).to_pydatetime()\n",
    "print(\"List of U.S. Federal Holidays:\")\n",
    "for holiday in holidays:\n",
    "    print(holiday.strftime('%Y-%m-%d'))\n",
    "    \n",
    "print(sales_over_time.reset_index().sort_values('amt', ascending=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0825c776",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/548331687.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['holiday'] = clean_tx_transation_df['saledate'].apply(lambda x: x in holidays)\n"
     ]
    }
   ],
   "source": [
    "clean_tx_transation_df['holiday'] = clean_tx_transation_df['saledate'].apply(lambda x: x in holidays)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d65e497",
   "metadata": {},
   "source": [
    "### Observation\n",
    "The time series plot illustrates the daily sales volume, revealing numerous peaks in sales occurring around holiday periods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "684843ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/4249159716.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['month'] = clean_tx_transation_df['saledate'].dt.month_name()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Sales by Month'}, xlabel='month'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract the month and year from SALEDATE and store in a new column 'MONTH'\n",
    "clean_tx_transation_df['month'] = clean_tx_transation_df['saledate'].dt.month_name()\n",
    "\n",
    "# Group by the 'MONTH' column and sum the sales amounts\n",
    "sales_by_month = clean_tx_transation_df.groupby('month')['amt'].sum()\n",
    "\n",
    "# If you want to plot this data:\n",
    "sales_by_month.plot(title='Sales by Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "71068a99",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/878784388.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['quarter'] = clean_tx_transation_df['saledate'].dt.to_period('Q').dt.quarter\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Sales by Quarter'}, xlabel='quarter'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['quarter'] = clean_tx_transation_df['saledate'].dt.to_period('Q').dt.quarter\n",
    "# Group by the 'MONTH' column and sum the sales amounts\n",
    "sales_by_quarter = clean_tx_transation_df.groupby('quarter')['amt'].sum()\n",
    "\n",
    "# If you want to plot this data:\n",
    "sales_by_quarter.plot(title='Sales by Quarter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "810141ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/2623737031.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['weekday'] = clean_tx_transation_df['saledate'].dt.day_name()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['weekday'] = clean_tx_transation_df['saledate'].dt.day_name()\n",
    "\n",
    "# Group by the 'WEEKDAY' column and sum the sales amounts\n",
    "sales_by_weekday = clean_tx_transation_df.groupby('weekday')['amt'].sum()\n",
    "\n",
    "# Order the data by the days of the week\n",
    "ordered_days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "sales_by_weekday = sales_by_weekday.reindex(ordered_days)\n",
    "\n",
    "# Plotting the results\n",
    "sales_by_weekday.plot(kind='bar', title='Sales by Weekday')\n",
    "plt.ylabel('Sales Amount')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b62f561d",
   "metadata": {},
   "source": [
    "### Observation\n",
    "Customers exhibit a preference for increased shopping activities each Saturday throughout the week. Additionally, stores in TX are operating well, with sales showing steady growth. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71776f79",
   "metadata": {},
   "source": [
    "### Distribution of Item Sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "5829612d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Distribution of Item Sizes'}, xlabel='size'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['size'].value_counts().head(10).plot(kind='bar', title='Distribution of Item Sizes')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df231906",
   "metadata": {},
   "source": [
    "### Top Selling Stores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "43ce0bcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top Selling Stores'}, xlabel='store'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_stores = clean_tx_transation_df.groupby('store')['amt'].sum().sort_values(ascending=False).head(10)\n",
    "top_stores.plot(kind='bar', title='Top Selling Stores')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "334cb220",
   "metadata": {},
   "source": [
    "### Most Common Colors Sold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "4287ca2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top 10 Most Common Colors Sold'}, xlabel='color'>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['color'].value_counts().head(10).plot(kind='bar', title='Top 10 Most Common Colors Sold')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f588d2ba",
   "metadata": {},
   "source": [
    "### Distribution of top vendors in Transactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b5bea8c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Distribution of Item Quantities in Transactions'}, xlabel='vendor'>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_df['vendor'].value_counts().head(10).plot(kind='bar', title='Distribution of Item Quantities in Transactions')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d3c71d1",
   "metadata": {},
   "source": [
    "### Sales vs Discount Percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "486068cc",
   "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>stype</th>\n",
       "      <th>sku</th>\n",
       "      <th>P</th>\n",
       "      <th>R</th>\n",
       "      <th>purchase_pct</th>\n",
       "      <th>return_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>24</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>107</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>156</td>\n",
       "      <td>34.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>75.555556</td>\n",
       "      <td>24.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>164</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>94.444444</td>\n",
       "      <td>5.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>180</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>190</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "stype  sku     P     R  purchase_pct  return_pct\n",
       "0        3   3.0   1.0     75.000000   25.000000\n",
       "1       23   1.0   0.0    100.000000    0.000000\n",
       "2       24   4.0   0.0    100.000000    0.000000\n",
       "3       55   6.0   0.0    100.000000    0.000000\n",
       "4      107   1.0   0.0    100.000000    0.000000\n",
       "5      131   4.0   0.0    100.000000    0.000000\n",
       "6      156  34.0  11.0     75.555556   24.444444\n",
       "7      164  17.0   1.0     94.444444    5.555556\n",
       "8      180  11.0   0.0    100.000000    0.000000\n",
       "9      190   8.0   2.0     80.000000   20.000000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tx_sku_stype_df = clean_tx_transation_df.groupby(['sku', 'stype'])[\"stype\"].aggregate(['count']).reset_index()\n",
    "tx_sku_stype_sum = tx_sku_stype_df.pivot(index = 'sku', columns = 'stype', values = 'count').reset_index().fillna(0)\n",
    "tx_sku_stype_sum[\"purchase_pct\"] = tx_sku_stype_sum.apply(lambda x: 100 * x['P'] / (x['P'] + x['R']), axis = 1)\n",
    "tx_sku_stype_sum[\"return_pct\"] = tx_sku_stype_sum.apply(lambda x: 100 * x['R'] / (x['P'] + x['R']), axis = 1)\n",
    "tx_sku_stype_sum.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "849fe823",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/3510714510.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['discount_percentage'] = 100 * clean_tx_transation_df['amt'] / clean_tx_transation_df['orgprice'] * clean_tx_transation_df['quantity']\n",
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/3510714510.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  clean_tx_transation_df['profit'] = (clean_tx_transation_df['amt'] - clean_tx_transation_df['cost']) * clean_tx_transation_df['quantity']\n"
     ]
    }
   ],
   "source": [
    "clean_tx_transation_df['discount_percentage'] = 100 * clean_tx_transation_df['amt'] / clean_tx_transation_df['orgprice'] * clean_tx_transation_df['quantity']\n",
    "clean_tx_transation_df['profit'] = (clean_tx_transation_df['amt'] - clean_tx_transation_df['cost']) * clean_tx_transation_df['quantity']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e01dfe42",
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_discount_rate_each_sku = clean_tx_transation_df.groupby(['sku'])['discount_percentage'].mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "0e4a883b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<p>424014 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            sku  discount_percentage\n",
       "416716  9829884           100.000000\n",
       "23134    554745           100.000000\n",
       "395723  9329839           100.000000\n",
       "394495  9299839           100.000000\n",
       "131194  3090025           100.000000\n",
       "...         ...                  ...\n",
       "341167  8032336             0.875000\n",
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       "340673  8020010             0.589286\n",
       "252491  5930003             0.303030\n",
       "215900  5076741             0.066667\n",
       "\n",
       "[424014 rows x 2 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_discount_rate_each_sku.sort_values('discount_percentage', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "2255629b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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      ],
      "text/plain": [
       "            sku  max_discount_percentage  median_discount_percentage  \\\n",
       "49222   1169816               100.000000                   25.000000   \n",
       "254276  5973491               100.000000                   75.140000   \n",
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       "208512  4898309                25.000000                   25.000000   \n",
       "212007  4980746               100.000000                  100.000000   \n",
       "\n",
       "        min_discount_percentage  q1_discount_percentage  \\\n",
       "49222                  0.001681               25.000000   \n",
       "254276                 0.002857               50.000000   \n",
       "330669                 0.005587               55.860335   \n",
       "29487                  0.007752               56.500000   \n",
       "411502                 0.010204               25.000000   \n",
       "...                         ...                     ...   \n",
       "350663                 3.773585                3.773585   \n",
       "208492               100.000000              100.000000   \n",
       "208502                25.000000               25.000000   \n",
       "208512                25.000000               25.000000   \n",
       "212007               100.000000              100.000000   \n",
       "\n",
       "        q3_discount_percentage  count_gb_sku  discount_percentage_range  \\\n",
       "49222                35.000000            13                  99.998319   \n",
       "254276              100.000000           311                  99.997143   \n",
       "330669              100.000000           121                  99.994413   \n",
       "29487               100.000000            20                  99.992248   \n",
       "411502               71.418367           640                  99.989796   \n",
       "...                        ...           ...                        ...   \n",
       "350663                3.773585             1                   0.000000   \n",
       "208492              100.000000             2                   0.000000   \n",
       "208502               25.000000             1                   0.000000   \n",
       "208512               25.000000             1                   0.000000   \n",
       "212007              100.000000            16                   0.000000   \n",
       "\n",
       "        discount_iqr  \n",
       "49222      10.000000  \n",
       "254276     50.000000  \n",
       "330669     44.139665  \n",
       "29487      43.500000  \n",
       "411502     46.418367  \n",
       "...              ...  \n",
       "350663      0.000000  \n",
       "208492      0.000000  \n",
       "208502      0.000000  \n",
       "208512      0.000000  \n",
       "212007      0.000000  \n",
       "\n",
       "[424014 rows x 9 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Custom function to calculate Q1\n",
    "import numpy as np\n",
    "def calculate_q1(column):\n",
    "    return np.percentile(column, 25)\n",
    "\n",
    "# Custom function to calculate Q3\n",
    "def calculate_q3(column):\n",
    "    return np.percentile(column, 75)\n",
    "\n",
    "discount_percentage_range_sum = clean_tx_transation_df.groupby(['sku']).agg(max_discount_percentage = (\"discount_percentage\", \"max\"),\n",
    "                                                                            median_discount_percentage = (\"discount_percentage\", \"median\"), \n",
    "                                                                            min_discount_percentage = (\"discount_percentage\", \"min\"), \n",
    "                                                                            q1_discount_percentage = (\"discount_percentage\", calculate_q1),\n",
    "                                                                            q3_discount_percentage = (\"discount_percentage\", calculate_q3),\n",
    "                                                                            count_gb_sku = (\"sku\", \"size\")).reset_index() \n",
    "discount_percentage_range_sum['discount_percentage_range'] = discount_percentage_range_sum['max_discount_percentage'] - discount_percentage_range_sum['min_discount_percentage']\n",
    "discount_percentage_range_sum['discount_iqr'] = discount_percentage_range_sum['q3_discount_percentage'] - discount_percentage_range_sum['q1_discount_percentage']\n",
    "\n",
    "discount_percentage_range_sum.sort_values('discount_percentage_range', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f267b4ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "discount_percentage_range\n",
       "(80, 90]     70644\n",
       "(70, 80]     60549\n",
       "(60, 70]     43752\n",
       "(40, 50]     35387\n",
       "(20, 30]     23780\n",
       "(30, 40]     22228\n",
       "(50, 60]     21042\n",
       "(10, 20]     20770\n",
       "(90, 100]    10315\n",
       "(0, 10]       7528\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bins = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100]\n",
    "# Use pd.cut to bin the data\n",
    "bins_data = pd.cut(discount_percentage_range_sum['discount_percentage_range'], bins)\n",
    "# Count the occurrences in each discount bin\n",
    "bin_counts = pd.value_counts(bins_data)\n",
    "bin_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "30229820",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_temp = pd.merge(clean_tx_transation_df, discount_percentage_range_sum, on='sku', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "16fb02da",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We want rows with complete transaction information\n",
    "clean_tx_transation_temp = clean_tx_transation_temp[~clean_tx_transation_temp['profit'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "8e74c562",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>dept</th>\n",
       "      <th>upc</th>\n",
       "      <th>style</th>\n",
       "      <th>...</th>\n",
       "      <th>discount_percentage</th>\n",
       "      <th>profit</th>\n",
       "      <th>max_discount_percentage</th>\n",
       "      <th>median_discount_percentage</th>\n",
       "      <th>min_discount_percentage</th>\n",
       "      <th>q1_discount_percentage</th>\n",
       "      <th>q3_discount_percentage</th>\n",
       "      <th>count_gb_sku</th>\n",
       "      <th>discount_percentage_range</th>\n",
       "      <th>discount_iqr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-07-07</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>...</td>\n",
       "      <td>67.0</td>\n",
       "      <td>19.1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>298</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-24</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>35.6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>298</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>35.6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>298</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>35.6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>298</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>000400008332514</td>\n",
       "      <td>5     LX1J90</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>35.6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>298</td>\n",
       "      <td>65.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store   saledate stype  quantity  orgprice   amt    dept  \\\n",
       "0  5148332   1007 2005-07-07     P         1      50.0  33.5  9801.0   \n",
       "1  5148332   1007 2005-05-24     P         1      50.0  50.0  9801.0   \n",
       "2  5148332   1007 2005-04-09     P         1      50.0  50.0  9801.0   \n",
       "3  5148332   1007 2005-05-29     P         1      50.0  50.0  9801.0   \n",
       "4  5148332   1007 2005-06-12     R         1      50.0  50.0  9801.0   \n",
       "\n",
       "               upc         style  ... discount_percentage profit  \\\n",
       "0  000400008332514  5     LX1J90  ...                67.0   19.1   \n",
       "1  000400008332514  5     LX1J90  ...               100.0   35.6   \n",
       "2  000400008332514  5     LX1J90  ...               100.0   35.6   \n",
       "3  000400008332514  5     LX1J90  ...               100.0   35.6   \n",
       "4  000400008332514  5     LX1J90  ...               100.0   35.6   \n",
       "\n",
       "   max_discount_percentage median_discount_percentage min_discount_percentage  \\\n",
       "0                    100.0                       75.0                    35.0   \n",
       "1                    100.0                       75.0                    35.0   \n",
       "2                    100.0                       75.0                    35.0   \n",
       "3                    100.0                       75.0                    35.0   \n",
       "4                    100.0                       75.0                    35.0   \n",
       "\n",
       "   q1_discount_percentage  q3_discount_percentage count_gb_sku  \\\n",
       "0                    67.0                   100.0          298   \n",
       "1                    67.0                   100.0          298   \n",
       "2                    67.0                   100.0          298   \n",
       "3                    67.0                   100.0          298   \n",
       "4                    67.0                   100.0          298   \n",
       "\n",
       "   discount_percentage_range discount_iqr  \n",
       "0                       65.0         33.0  \n",
       "1                       65.0         33.0  \n",
       "2                       65.0         33.0  \n",
       "3                       65.0         33.0  \n",
       "4                       65.0         33.0  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_temp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "11179807",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_temp['lower_bound'] = clean_tx_transation_temp['q1_discount_percentage'] \\\n",
    "                                            - clean_tx_transation_temp['discount_iqr'] * 5 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d632b28d",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_subset = clean_tx_transation_temp[~((clean_tx_transation_temp['discount_percentage'] < 3)\n",
    "                              & (clean_tx_transation_temp['discount_percentage'] < clean_tx_transation_temp['lower_bound']) \\\n",
    "                              & (clean_tx_transation_temp['discount_percentage_range'] > 70))]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e62139d8",
   "metadata": {},
   "source": [
    "### Observation\n",
    "We decide to exclude transactions with excessively high discounts, such as selling items at prices less than 3% of the original price. This is necessary because we cannot ascertain whether these transactions are a result of inventory clearance or pricing errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "62d634a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of Percentage')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "clean_tx_transation_subset['discount_percentage'].hist(bins = 20)\n",
    "plt.title('Histogram of Percentage')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7236b2d",
   "metadata": {},
   "source": [
    "### Observation\n",
    "We have observed many instances of transactions with exceptionally high discount rates during inventory clearance. Consequently, we are exploring the possibility of predicting the profit margin before stocking these items."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0bd08b01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['sku', 'store', 'saledate', 'stype', 'quantity', 'orgprice', 'amt',\n",
       "       'dept', 'upc', 'style', 'color', 'size', 'packsize', 'vendor', 'brand',\n",
       "       'cost', 'retail', 'deptdesc', 'holiday', 'month', 'quarter', 'weekday',\n",
       "       'discount_percentage', 'profit', 'max_discount_percentage',\n",
       "       'median_discount_percentage', 'min_discount_percentage',\n",
       "       'q1_discount_percentage', 'q3_discount_percentage', 'count_gb_sku',\n",
       "       'discount_percentage_range', 'discount_iqr', 'lower_bound'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_subset.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "314d65e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_drop = ['discount_percentage', 'profit',\n",
    "       'max_discount_percentage', 'median_discount_percentage',\n",
    "       'min_discount_percentage', 'q1_discount_percentage',\n",
    "       'q3_discount_percentage', 'count_gb_sku', 'discount_percentage_range',\n",
    "       'discount_iqr', 'lower_bound', 'upc', 'vendor', 'color', 'style', 'size', 'dept']\n",
    "clean_tx_transation_final = clean_tx_transation_subset.drop(columns=columns_to_drop,  errors='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "0dca8fdf",
   "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>packsize</th>\n",
       "      <th>brand</th>\n",
       "      <th>cost</th>\n",
       "      <th>retail</th>\n",
       "      <th>deptdesc</th>\n",
       "      <th>holiday</th>\n",
       "      <th>month</th>\n",
       "      <th>quarter</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-07-07</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>July</td>\n",
       "      <td>3</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-24</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sku  store   saledate stype  quantity  orgprice   amt  packsize  \\\n",
       "0  5148332   1007 2005-07-07     P         1      50.0  33.5       1.0   \n",
       "1  5148332   1007 2005-05-24     P         1      50.0  50.0       1.0   \n",
       "2  5148332   1007 2005-04-09     P         1      50.0  50.0       1.0   \n",
       "3  5148332   1007 2005-05-29     P         1      50.0  50.0       1.0   \n",
       "4  5148332   1007 2005-06-12     R         1      50.0  50.0       1.0   \n",
       "\n",
       "      brand  cost  retail deptdesc  holiday  month  quarter   weekday  \n",
       "0  LIZ CLAI  14.4    12.5  CATALIN    False   July        3  Thursday  \n",
       "1  LIZ CLAI  14.4    12.5  CATALIN    False    May        2   Tuesday  \n",
       "2  LIZ CLAI  14.4    12.5  CATALIN    False  April        2  Saturday  \n",
       "3  LIZ CLAI  14.4    12.5  CATALIN    False    May        2    Sunday  \n",
       "4  LIZ CLAI  14.4    12.5  CATALIN    False   June        2    Sunday  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "3910d59d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Rv379FBISovnz52vFihWqU6eOBg0a5HDf6Llq166tUaNG6emnn9bKlSv1j3/844I/93N98MEHys/P12OPPXbevnbt2unVV19Vnz59dNFFF+mVV17RsmXLFBISoiuvvFJTp0516RYJAKXPZvnBw+TGjh2rn3/+2f54qtatW2vQoEG65ZZbzju2du3a+vjjjzVy5Ejt2rXL/pgUqWBqatOmTfrPf/5TarUDgKds27ZNd999t5YsWWK/9QEAfEm5vUf1r/ztb3/T999/rwYNGtg/jh49qhdeeEG///676tWrJ0n69ttvHV63f/9+NWjQwBslAwAA+B2/DKqDBw/Wf//7XyUmJurgwYPasmWLxo0bp4yMDNWuXVutW7dWmzZtFB8fr61bt9rvtdqyZUuR01gAAAAwyy+n/qWCt1H817/+pZSUFFWrVk3dunXT6NGj7Y8sOX36tGbMmKGPPvpIp0+fVpMmTfTwww87fcwJAAAAzPOLoAoAAICyxy+n/gEAAOD7CKoAAADwSeXqOapffvmlLMtSYGCgt0sBAACAE7m5ubLZbIqOjr7gseVqRNWyLJXmLbeWZSknJ6dUr1kW0Jei0Rvn6EvR6I1z9MU5+lI0euOcN/pSkrxWrkZUC0dSIyIiSuV6mZmZ2rt3r8LDwxUSElIq1ywL6EvR6I1z9KVo9MY5+uIcfSkavXHOG335+uuvi31suRpRBQAAQPlBUAUAAIBPIqgCAADAJxFUAQAA4JMIqgAAAPBJBFUAAAD4JIIqAAAAfBJBFQAAAD6JoAoAAACfRFAFAACATyKoAgAAwCcRVAEAAOCTCKoAAADwSQRVAAAA+CSCKgAAAHwSQdUN6enS+vUXKzPT25UAAACUPwRVNyQkBOrJJ6/Q669X9HYpAAAA5Q5B1Q2nT9skSSdPerkQAACAcoig6oaAAEuSlJ/v5UIAAADKIYKqGwL+1z2CKgAAgHkEVTf8EVRt3i0EAACgHCKouoERVQAAAM8hqLrB9r+BVIIqAACAeQRVNzCiCgAA4DkEVTcQVAEAADyHoOoGgioAAIDnEFTdQFAFAADwHIKqGwiqAAAAnkNQdQNBFQAAwHMIqm4oDKqW5d06AAAAyiOCqhsYUQUAAPAcgqobAgIKhlIJqgAAAOYRVN3AiCoAAIDnEFTd8EdQtXm3EAAAgHKIoOoG2//yKSOqAAAA5hFU3cDUPwAAgOcQVN1AUAUAAPAcgqobCKoAAACeQ1B1A0EVAADAcwiqbiCoAgAAeA5B1Q28hSoAAIDnEFTdwIgqAACA5xBU3UBQBQAA8ByCqhsIqgAAAJ5DUHVDQEDBzakEVQAAAPMIqm5gRBUAAMBzCKpusNkKPufn27xbCAAAQDlEUHUDI6oAAACeQ1B1A0EVAADAcwiqbiCoAgAAeA5B1Q0EVQAAAM8hqLqBoAoAAOA5BFU3FAZVy/JuHQAAAOURQdUNjKgCAAB4DkHVDQRVAAAAzyGouqHwgf9M/QMAAJhHUHUDI6oAAACeQ1B1Q0BAwVAqQRUAAMA8gqobCqf+CaoAAADmEVTd8MfUv827hQAAAJRDBFU3cI8qAACA5xBU3UBQBQAA8ByCqhsIqgAAAJ5DUHUDb6EKAADgOQRVNzCiCgAA4DkEVTcQVAEAADyHoOoGgioAAIDnEFTdQFAFAADwHIKqGwiqAAAAnuNTQfXgwYOKjo7WqlWrvF1KsRBUAQAAPMdngmpubq4effRRZWZmeruUYrPZCp5LRVAFAAAwz2eCamJioi666CJvl1EijKgCAAB4jk8E1e3bt2vZsmV6/vnnvV1KifwRVG3eLQQAAKAcqujtAjIyMjRmzBg98cQTqlevntvnsyyr1G4fyM3NkRSs/HxLmZlZpXLNsiArK8vhM/5Ab5yjL0WjN87RF+foS9HojXPe6ItlWbLZijfI5/WgOnHiREVFRemmm24ycr7c3Fzt3bvXyLku5PDhypKqKzc3r9SuWZakpqZ6uwSfRW+coy9FozfO0Rfn6EvR6I1zpd2XoKCgYh3n1aC6evVq7dixQ2vXrjV2zsDAQIWHhxs731/Jzc2WJNlsFdS8efNSuWZZkJWVpdTUVDVs2FDBwcHeLsen0Bvn6EvR6I1z9MU5+lI0euOcN/qSkpJS7GO9GlRXrlyp9PR0de3a1WH7hAkTNH/+fP3nP/8p8TltNptCQkIMVfjXgoMLhq0tq/SuWZYEBwfTlyLQG+foS9HojXP0xTn6UjR641xp9qW40/6Sl4Pq1KlTdebMGYdtPXv21IMPPqhevXp5qariY9U/AACA53g1qNapU8fp9po1a+rSSy8t5WpKjqAKAADgOT7xeKqyiqAKAADgOV5f9f9n3377rbdLKDaCKgAAgOcwouoGgioAAIDnEFTdQFAFAADwHIKqG2w2SxJBFQAAwBMIqm74Y0S1+M8DAwAAQPEQVN0QcE73LMt7dQAAAJRHBFU3nBtUmf4HAAAwi6DqBoIqAACA5xBU3UBQBQAA8ByCqhsIqgAAAJ5DUHUDQRUAAMBzCKpuIKgCAAB4DkHVDQRVAAAAzyGouoGgCgAA4DkEVTcQVAEAADyHoOoG2znvnEpQBQAAMIug6gabTbLZCt47laAKAABgFkHVTYXT/wRVAAAAswiqbmJEFQAAwDMIqm4qHFG1LO/WAQAAUN4QVN1UuKCKEVUAAACzCKpuYuofAADAMwiqbmIxFQAAgGcQVN3E1D8AAIBnEFTdFBDA1D8AAIAnEFTdxNQ/AACAZxBU3cRiKgAAAM8gqLqJEVUAAADPIKi6icVUAAAAnkFQdROLqQAAADyDoOompv4BAAA8g6DqJhZTAQAAeAZB1U2MqAIAAHgGQdVNLKYCAADwDIKqm1hMBQAA4BkEVTcxogoAAOAZBFU3MaIKAADgGQRVN7GYCgAAwDMIqm5i6h8AAMAzCKpuYuofAADAMwiqbmJEFQAAwDMIqm5iRBUAAMAzCKpuYjEVAACAZxBU3cTUPwAAgGcQVN3E1D8AAIBnEFTdxIgqAACAZxBU3cSIKgAAgGcQVN3EYioAAADPIKi6ial/AAAAzyCouompfwAAAM8gqLqJEVUAAADPIKi6iRFVAAAAzyCouonFVAAAAJ5BUHUTU/8AAACeQVB1E1P/AAAAnkFQdRMjqgAAAJ5BUHUTI6oAAACeQVB1EyOqAAAAnkFQdROr/gEAADyDoOompv4BAAA8g6DqJqb+AQAAPIOg6iZGVAEAADyDoOomRlQBAAA8g6DqJhZTAQAAeAZB1U2FU/+W5eVCAAAAyhmCqpuY+gcAAPAMrwfV9PR0jR49Wh06dFB0dLTuu+8+paSkeLusYmMxFQAAgGd4PagOHTpUP/30k+bNm6cVK1aocuXKGjhwoLKysrxdWrEwogoAAOAZXg2qJ0+eVP369TVp0iRFRESocePGGjZsmI4dO6bvvvvOm6UVG0EVAADAMyp68+I1atTQtGnT7F8fP35c8+fPV926dRUeHu7FyoqPqX8AAADP8GpQPdeTTz6pN998U0FBQZozZ45CQkK8XVKxMKIKAADgGT4TVAcMGKC+ffvq3//+t4YPH67XX39dLVu2LPF5LMtSZmamByo8X1ZWlv05qtnZucrMzC2V6/q6wvuLy8p9xqWJ3jhHX4pGb5yjL87Rl6LRG+e80RfLsmQrHOm7AJtl+dYTQPPz83XTTTepdevWmjJlSole+/XXXysnJ8dDlTmXkFBf//53Hd1zz2ENH/5LqV4bAACgLAoKClJERMQFj/PqiGp6erq2bNmi66+/XhUqVJAkBQQEqHHjxkpLS3PpnIGBgaV2f2tWVpZstrOSpIsvrqXmzauVynV9XVZWllJTU9WwYUMFBwd7uxyfQm+coy9FozfO0Rfn6EvR6I1z3uhLSR5D6lJQnT17tuLi4lSvXj1XXm6XlpamRx55RDVr1tRVV10lScrNzdWePXsUGxvr0jltNlup3t8aEJAhSapQIVAhIYGldt2yIDg4uMzca1za6I1z9KVo9MY5+uIcfSkavXGuNPtS3Gl/ycXHUy1evFjdu3fXPffco7Vr1yo7O9uV06hZs2bq2LGjnnrqKe3YsUP79+9XfHy8MjIyNHDgQJfOWdpYTAUAAOAZLgXVzZs3a+rUqQoMDNTYsWMVExOj8ePH68svvyzReWw2m2bMmKEOHTpo5MiR6tOnj06fPq3XXntNl1xyiSullbrCxVQEVQAAALNcmvoPCgpSr1691KtXL6WlpWnNmjVav369li9froYNGyouLk5xcXGqWbPmBc9VpUoVTZw4URMnTnSlFK/jOaoAAACe4fY7U4WFhenuu+/WkCFD1KZNGx08eFDTpk1Tly5d9OSTT+q3334zUafPYuofAADAM9xa9f/555/r7bff1rvvvqvMzEx16NDBHlI//vhjPf300zpy5IjmzZtnql6fw4gqAACAZ7gUVKdPn661a9fq8OHDqlevngYOHKi4uDiH+0p79eqlb7/9VkuWLDFWrC9iRBUAAMAzXAqqCxcu1DXXXKNJkybp6quvLvIxAxERERo5cqQ79fk8FlMBAAB4hktB9ZNPPlG1atV07Ngxe0g9ffq0Dh8+rGbNmtmPu+aaa8xU6cNsNqb+AQAAPMGlxVQBAQG655571L9/f/u2r776Sn//+981bNgwv3ofXUZUAQAAPMOloPriiy/qu+++08MPP2zf1qFDByUlJWn37t2aOXOmsQJ9HYupAAAAPMOloPrBBx8oPj5ePXv2tG8LCgpSbGysHn74Ya1fv95Ygb6OxVQAAACe4VJQ/f3331W1alWn+2rWrKmTJ0+6VVRZwtQ/AACAZ7gUVFu2bKmVK1c63bdq1So1bdrUraLKEhZTAQAAeIZLq/6HDh2qwYMHKy4uTj169FDNmjV14sQJbdy4Ud98843mzp1ruk6fxYgqAACAZ7gUVGNiYjRnzhzNnDlTM2fOlGVZstlsat68uZKSktS5c2fTdfosFlMBAAB4hstvodqlSxd16dJF2dnZOnXqlKpUqaKQkBCTtZUJLKYCAADwDJeDqlTwkP+srCzl5+fr1KlTOnXqlH3fuW+nWp4x9Q8AAOAZLgXV1NRUjR07Vl999VWRx+zdu9flosoSFlMBAAB4hktBddKkSUpNTdUDDzygunXrKiDApYcHlAuMqAIAAHiGS0F1x44devbZZ3XjjTearqfMYTEVAACAZ7g0FBoaGqpq1aqZrqVMYjEVAACAZ7gUVG+++Wa99tprsizLdD1lDlP/AAAAnuHS1H9wcLCSk5PVo0cPRUREqHLlyg77bTabJk+ebKRAX8diKgAAAM9wKai+9dZbqlKlivLz852u/LcVzof7AUZUAQAAPMOloPrBBx+YrqPMYjEVAACAZ7j1XKn8/Hzt27dPmzZt0m+//ebwwH9/wWIqAAAAz3D5nanefvttJSQkKC0tTTabTStWrFBiYqICAwOVkJCgoKAgk3X6LKb+AQAAPMOlEdV169YpPj5eHTp00PTp0+2r/3v27KlNmzYpKSnJaJG+jMVUAAAAnuHSiOrcuXN1++23a+LEicrLy7Nvj4uLU3p6ut58802NHDnSVI0+jRFVAAAAz3BpRPXgwYPq0aOH032RkZE6evSoW0WVJSymAgAA8AyXgmrNmjV14MABp/sOHDigmjVrulVUWcJiKgAAAM9wKaj26tVLM2fO1IYNG5STkyOp4Nmpu3fvVlJSkq677jqjRfoypv4BAAA8w6V7VEeOHKn9+/dr5MiRCvhfUuvfv78yMzPVpk0bPfTQQ0aL9GUspgIAAPAMl4JqUFCQXnnlFX366afasmWLTp8+rSpVqqhdu3bq0qWLX74z1f8efAAAAABDXH6OqiTFxMQoJibGVC1lEoupAAAAPMOloDpr1qwLHvPAAw+4cuoyh8VUAAAAnmE8qIaGhiosLMxvgiqLqQAAADzDpaC6b9++87ZlZmYqOTlZEydO1JNPPul2YWUFi6kAAAA8w6XHUzkTEhKiTp06afjw4XrhhRdMndbnMaIKAADgGcaCaqF69eoV+WYA5RGLqQAAADzDrVX/57IsS4cPH9a8efN06aWXmjptmUFQBQAAMMuloNqsWbMin5VqWRZT/wAAAHCbS0F1+PDhToNqaGiounbtqoYNG7pbV5nB1D8AAIBnuBRUR4wYYbqOMovnqAIAAHiGS0H1l19+KdHxl1xyiSuXKROY+gcAAPAMl4JqbGxskfeoOrN3715XLlMm8BxVAAAAz3ApqM6YMUMTJkxQy5Yt1bt3b9WpU0cnT57UBx98oPXr12vo0KF+s/KfEVUAAADPcCmorl69WrGxsZoyZYrD9l69eqlmzZr64osv/OgtVBlRBQAA8ASXHvi/detW3XjjjU73de7cWcnJyW4VVZawmAoAAMAzXAqqNWrU0M6dO53u+/TTT1WnTh13aipTmPoHAADwDJem/m+99VbNmTNHWVlZio2N1cUXX6zjx49r3bp1euONNzR+/HjTdfosFlMBAAB4hktBddiwYfr111+1aNEizZ8/X1LBO1IFBwfr4Ycf1u233260SF/GiCoAAIBnuBRUbTabxo4dq2HDhmnnzp06ffq0atSooaioKIWGhpqu0aexmAoAAMAzXAqqhUJDQxUWFiZJioqK0tmzZ40UVZawmAoAAMAzXA6qb7/9thISEnTs2DHZbDYtX75ciYmJCgwMVEJCgoKCgkzW6bOY+gcAAPAMl1b9r1u3TvHx8erQoYOmTZum/P+ltJ49e2rTpk1KSkoyWqQvYzEVAACAZ7g0ojp37lzdfvvtmjhxovLy8uzb4+LilJ6erjfffFMjR440VaNPY0QVAADAM1waUT148KB69OjhdF9kZKSOHj3qVlFlCYupAAAAPMOloFqzZk0dOHDA6b4DBw6oZs2abhVVlrCYCgAAwDNcCqq9evXSzJkztWHDBuXk5EgqeGTV7t27lZSUpOuuu85okb6scOrfsgo+AAAAYIZL96iOHDlS+/fv18iRIxXwv6TWv39/ZWZmqk2bNnrooYeMFunLChdTSQVBtXCEFQAAAO5xKagGBQXplVde0aeffqqtW7fq1KlTqlKlitq1a6cuXbrI5kdpLeCcMen8fMevAQAA4DqXguqQIUN09913KyYmRjExMaZrKlMKF1NJ3KcKAABgkkvjf9u3b1eFChVM11ImnTt4TFAFAAAwx6WgGhMTo+XLlys7O9t0PWXOn6f+AQAAYIZLU/+VKlXS+vXr9d5776l+/frnPY7KZrNp8eLFRgr0decupiKoAgAAmONSUD1y5Iiio6PtX1t/ei7Tn78uzxhRBQAA8IxiB9W1a9eqU6dOql69ul599VVP1lSmsJgKAADAM4p9j+qYMWP0448/OmybO3eujh8/bryosoTFVAAAAJ5R7KD65+n8vLw8vfTSSzp69KhbBZw6dUrjx49X586ddeWVV+qOO+7Qjh073DpnaWLqHwAAwDPcejy9iXtRH374YX311VeaNm2aVqxYoZYtW+ree+/VgQMH3D53aWBEFQAAwDO8+j5KP/zwgz799FNNmDBBbdq0UaNGjfT444+rTp06euedd7xZWokU3qdKUAUAADDHq0G1Ro0aevnll9WqVSv7NpvNJsuydPr0aS9WVjKF0/8EVQAAAHNcejzVuWznzn2XUNWqVdWlSxeHbevXr9ePP/6ojh07unROy7KUmZnpck0lkZWVJemPoPr771nKzPSfR3MVpbAvhZ/xB3rjHH0pGr1xjr44R1+KRm+c80ZfLMsqdn60WcW80bRZs2aqXbu2goKC7Nt+/vlnhYWFKTAw0PGkNpvef//9EpRcIDk5Wf/85z911VVXKSkpqcSv//rrr5WTk1Pi17krJiZa2dkBeuedXapbN7fUrw8AAFCWBAUFKSIi4oLHFXtE9ZZbbnGroAt5//339eijjyoyMlLTpk1z+TyBgYEKDw83WFnRsrKylJqaqgoVCv6voFGjv6lBA0ZUC/vSsGFDBQcHe7scn0JvnKMvRaM3ztEX5+hL0eiNc97oS0pKSrGPLXZQnTJlikvFFMfSpUv17LPPqkePHpo6darDqG1J2Ww2hYSEGKzuwgqn/itVClYpX9qnBQcHl/rPoqygN87Rl6LRG+foi3P0pWj0xrnS7EtJbhv16mIqSXr99dc1adIk9evXTzNmzHArpHoLi6kAAADMc3sxlTsOHjyoyZMnq0ePHrr//vuVnp5u31e5cmVVqVLFi9UVX2FQNfBYWQAAAPyPV4Pqu+++q9zcXL333nt67733HPbdcssteu6557xUWckwogoAAGCeV4PqkCFDNGTIEG+WYARBFQAAwDyv36NaHhTeE0xQBQAAMIegagAjqgAAAOYRVA0ICChYRUVQBQAAMIegagAjqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAVv0DAACYR1A1gBFVAAAA8wiqBhBUAQAAzCOoGkBQBQAAMI+gagBBFQAAwDyCqgEspgIAADCPoGoAI6oAAADmEVQNIKgCAACYR1A1gKAKAABgHkHVgIAASxJBFQAAwCSCqgGMqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQNIKgCAACYR1A1gKAKAABgHkHVAN5CFQAAwDyCqgGMqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQNIKgCAACYR1A1ICDAkkRQBQAAMImgagAjqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQNsNkKPhNUAQAAzCGoGsCIKgAAgHkEVQMIqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQNCAiwJEmW5eVCAAAAyhGCqgGMqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDeAtVAAAA8wiqBjCiCgAAYB5B1QCCKgAAgHkEVQMIqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQN4DmqAAAA5hFUDQgIsCQRVAEAAEwiqBrA1D8AAIB5BFUDCKoAAADmEVQN4B5VAAAA8wiqBjCiCgAAYB5B1QCCKgAAgHkEVQMIqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAgioAAIB5BFUDCKoAAADm+VRQTUpKUv/+/b1dRokRVAEAAMzzmaC6aNEizZw509tluISgCgAAYF5Fbxdw9OhRPf7440pOTtYVV1zh7XJcEhBgSSKoAgAAmOT1EdVvvvlG1apV05o1axQZGentclzCiCoAAIB5Xh9RjY2NVWxsrLHzWZalzMxMY+f7K1lZWZKks2dzJVVSbm6eMjOzS+XavqywL4Wf8Qd64xx9KRq9cY6+OEdfikZvnPNGXyzLks1mK9axXg+qpuXm5mrv3r2les0TJ45JClVGxm/auzelVK/ty1JTU71dgs+iN87Rl6LRG+foi3P0pWj0xrnS7ktQUFCxjit3QTUwMFDh4eGlcq2srCylpqYqLKyWJCkkJFTNmzcvlWv7ssK+NGzYUMHBwd4ux6fQG+foS9HojXP0xTn6UjR645w3+pKSUvxBvXIXVG02m0JCQkr1mpUqBf3v2hVK/dq+LDg4mH4Ugd44R1+KRm+coy/O0Zei0RvnSrMvxZ32l3xgMVV5wGIqAAAA8wiqBhBUAQAAzCOoGkBQBQAAMM+n7lF97rnnvF2CSwiqAAAA5jGiagBBFQAAwDyCqgEEVQAAAPMIqgYQVAEAAMwjqBoQEGBJIqgCAACYRFA1oPC5tQRVAAAAcwiqBjD1DwAAYB5B1QCCKgAAgHkEVQMIqgAAAOYRVA0gqAIAAJhHUDWgMKhalnfrAAAAKE8IqgYwogoAAGAeQdUAgioAAIB5BFUDCKoAAADmEVQNIKgCAACYR1A1gKAKAABgHkHVgICAguX+BFUAAABzCKoG2GwFnwmqAAAA5hBUDWDqHwAAwDyCqgEEVQAAAPMIqgYQVAEAAMwjqBpAUAUAADCPoGoAQRUAAMA8gqoBBFUAAADzCKoG8HgqAAAA8wiqBjCiCgAAYB5B1QCCKgAAgHkEVQMIqgAAAOYRVA0gqAIAAJhHUDWAoAoAAGAeQdUAm82SRFAFAAAwiaBqACOqAAAA5hFUDQg4p4uW5b06AAAAyhOCqgHnBlVGVQEAAMwgqBpAUAUAADCPoGoAQRUAAMA8gqoBBFUAAADzCKoGEFQBAADMI6gaQFAFAAAwj6BqAEEVAADAPIKqAQRVAAAA8wiqBhBUAQAAzCOoGmCz/fFngioAAIAZBFUDbLY/wipBFQAAwAyCqiGF0/8EVQAAADMIqoYQVAEAAMwiqBpCUAUAADCLoGoIQRUAAMAsgqohBFUAAACzCKqGEFQBAADMIqgaQlAFAAAwi6BqCEEVAADALIKqIQRVAAAAswiqhhBUAQAAzCKoGlIYVC3Lu3UAAACUFwRVQxhRBQAAMIugaghBFQAAwCyCqiEEVQAAALMIqoYQVAEAAMwiqBpCUAUAADCLoOqmwMBA2Ww2gioAAIBhFb1dQFlms9nUokUrVawYYCSo5uf/MTILAADg7wiqbqpYMUBvvnlWGRkFrXzrLenrr0t+nlq1pH/8w3BxAAAAZRhB1YBjxyzl5RX8+fhx6aKLvFsPAABAecBEsyE2W8Fn3pkKAADADIKqIQRVAAAAs7weVPPz8zVz5kx16tRJkZGRGjRokH744Qdvl1ViBFUAAACzvB5Uk5KS9MYbb+iZZ57RsmXLZLPZNHjwYOXk5Hi7tBIhqAIAAJjl1aCak5OjBQsWaMSIEerSpYuaNWum6dOn6+jRo3rvvfe8WVqJEVQBAADM8mpQ3bdvn37//Xd16NDBvq1q1apq0aKFtm/f7sXKSo6gCgAAYJZXH0915MgRSVK9evUctoeFhenw4cMlPl9ubq4sy9KuXbuM1HchlmUpICBAV15pad48m3JzpQoV/gitJWGzSRs2mK/RWywrUMeOHfB2GT6J3jhHX4pGb5yjL87Rl6LRG+csK1AZGSmqWbN0rpebmytbMcOSV4NqVlaWJCkoKMhhe6VKlXT69OkSn6/wmy7uN++uwuuEhtoUGloqlyxDSudnUDbRG+foS9HojXP0xTn6UjR641zp9sVms5WNoFq5cmVJBfeqFv5ZkrKzsxUcHFzi80VHRxurDQAAAN7l1XtUC6f809LSHLanpaWpbt263igJAAAAPsKrQbVZs2YKDQ3Vtm3b7NsyMjK0Z88etWnTxouVAQAAwNu8OvUfFBSku+66S1OnTtXFF1+sSy+9VC+++KLq1q2rHj16eLM0AAAAeJlXg6okPfjggzp79qyeeOIJnTlzRm3bttX8+fPPW2AFAAAA/2KzLJ78CQAAAN/j9bdQBQAAAJwhqAIAAMAnEVQBAADgkwiqAAAA8EkEVQAAAPgkgioAAAB8EkEVAAAAPomg6oL8/HzNnDlTnTp1UmRkpAYNGqQffvjB22WVqqSkJPXv399h2969e3XXXXcpKipKXbt21fz58x32l9e+nTp1SuPHj1fnzp115ZVX6o477tCOHTvs+/21L5KUnp6u0aNHq0OHDoqOjtZ9992nlJQU+35/7k2hgwcPKjo6WqtWrbJv8+e+/Pzzz2ratOl5H8uXL5fk371ZvXq1evXqpYiICN1www1av369fZ+/9mXbtm1Of1+aNm2q7t27S/Lf3uTm5mr69Onq2rWroqOjdeedd+qLL76w7y8zfbFQYomJidZVV11lffTRR9bevXutQYMGWT169LCys7O9XVqpWLhwodW0aVPrrrvusm87ceKE1b59e+vxxx+3UlJSrBUrVlgRERHWihUr7MeU177dc889Vu/eva3t27dbBw4csCZNmmS1bt3aSklJ8eu+WJZl9enTx+rbt6+1a9cuKyUlxRoxYoQVExNjZWZm+n1vLMuycnJyrLi4OKtJkybWypUrLcvy7/+WLMuyNm7caEVERFhHjx610tLS7B9ZWVl+3ZvVq1dbzZs3txYtWmSlpqZas2bNspo1a2Z98cUXft2X7Oxsh9+TtLQ0a/PmzVaLFi2sN998069789JLL1kxMTHWJ598YqWmplqPP/64deWVV1pHjhwpU30hqJZQdna2FR0dbb3++uv2badPn7Zat25tvfPOO16szPOOHDli3XvvvVZUVJR13XXXOQTVuXPnWp06dbJyc3Pt2xISEqxrr73Wsqzy27fU1FSrSZMmVnJysn1bfn6+1aNHD2vGjBl+2xfLKghco0aNsvbv32/ftnfvXqtJkybWV1995de9KZSQkGD179/fIaj6e1/mzJlj9e7d2+k+f+1Nfn6+1a1bN+u5555z2D5o0CBr7ty5ftsXZ3JycqwbbrjBGjlypGVZ/vs7Y1mW1bt3b2vKlCn2r3/99VerSZMm1oYNG8pUX5j6L6F9+/bp999/V4cOHezbqlatqhYtWmj79u1erMzzvvnmG1WrVk1r1qxRZGSkw74dO3aobdu2qlixon1bhw4ddPDgQaWnp5fbvtWoUUMvv/yyWrVqZd9ms9lkWZZOnz7tt32RCnozbdo0/e1vf5MkHT9+XPPnz1fdunUVHh7u172RpO3bt2vZsmV6/vnnHbb7e1++/fZbhYeHO93nr735/vvv9fPPP+umm25y2D5//nzdf//9ftsXZ1577TUdPnxY48aNk+S/vzOSVL16dX344Yc6dOiQ8vLytGzZMgUFBal58+Zlqi8E1RI6cuSIJKlevXoO28PCwnT48GFvlFRqYmNjlZCQoMsuu+y8fUeOHFHdunUdtoWFhUmSfvnll3Lbt6pVq6pLly4KCgqyb1u/fr1+/PFHdezY0W/78mdPPvmkYmJitGHDBj377LMKCQnx695kZGRozJgxeuKJJ877/vy5L5K0f/9+paen684779TVV1+tO+64Q5988okk/+1NamqqJCkzM1P33nuvrrrqKvXp00cffPCBJP/ty59lZ2dr7ty5GjBggP379+fePP7446pYsaK6d++uiIgITZ8+XTNmzNDll19epvpCUC2hrKwsSXIIJpJUqVIlZWdne6Mkn3DmzBmnPZEK/vLwl74lJyfrscceU/fu3RUbG0tf/mfAgAFauXKlevfureHDh+ubb77x695MnDhRUVFR542QSf7931JOTo5SU1P122+/aeTIkXr55ZcVERGhwYMHa8uWLX7bm99++02SFB8frxtvvFELFixQTEyMhg0b5td9+bO3335b2dnZDgt9/bk3Bw4cUNWqVTV79mwtW7ZMcXFxio+P1759+8pUXype+BCcq3LlypIK/kIt/LNU8IMNDg72VlleV7lyZeXk5DhsK/xlDgkJ8Yu+vf/++3r00UcVGRmpadOmSaIvhQqncidNmqSdO3dq6dKlftub1atXa8eOHVq7dq3T/f7aF6ngH8Xt27erYsWK9n8gW7VqpQMHDmj+/Pl+25vAwEBJ0r333qtbbrlFktS8eXPt2bNHCxcu9Nu+/Nnq1avVs2dP1ahRw77NX3vz888/a/To0Vq0aJHatGkjSYqIiFBKSooSExPLVF8YUS2hwmHwtLQ0h+1paWnnDaP7k7p16zrtiSTVqVOn3Pdt6dKlGjFihDp37qx58+bZ/8P2576kp6frnXfeUV5enn1bQECAGjdubP/+/LE3K1euVHp6uv2RMdHR0ZKkCRMm6IYbbvDbvhQKCQk5bxSnSZMmOnr0qN/2prD2Jk2aOGwPDw/XoUOH/LYv5zpx4oS+/PJL9erVy2G7v/Zm165dys3NVUREhMP2yMhIpaamlqm+EFRLqFmzZgoNDdW2bdvs2zIyMrRnzx77/7X4o7Zt2yo5OdkhlGzZskVXXHGFatasWa779vrrr2vSpEnq16+fZsyY4fCPrD/3JS0tTY888og+//xz+7bc3Fzt2bNHjRs39tveTJ06VevWrdPq1avtH5L04IMP6uWXX/bbvkgFi1Wjo6MdnkMsSbt371Z4eLjf9qZFixa66KKL9NVXXzls379/vy6//HK/7cu5vvjiC9lsNrVr185hu7/2pjBofvvttw7b9+/frwYNGpStvpTqMwbKiWnTplnt2rWz3n//ffuzxXr27Fnmn7lWEvHx8Q6Ppzp+/LjVtm1bKz4+3vruu++slStXWhEREdaqVavsx5THvn3//fdWy5YtreHDh5/3LL+MjAy/7YtlFTxSZ9CgQda1115rbd++3fr222+tUaNGWW3btrV+/vlnv+7Nn537eCp/7kteXp7Vp08f68Ybb7S2b99upaSkWJMnT7ZatWpl7du3z697M3v2bCs6Otpau3at9cMPP1hJSUlWs2bNrK1bt/p1XwolJiZaPXv2PG+7v/YmLy/PuvPOO63rrrvO2rJli3Xw4EFr+vTpVvPmza0vv/yyTPWFoOqCs2fPWi+88ILVoUMHKyoqyho8eLD1008/ebusUvXnoGpZlvXVV19Zt912m9WqVSurW7du1quvvuqwvzz2bc6cOVaTJk2cfsTHx1uW5Z99KZSRkWFNmDDBiomJsVq3bm0NGjTI4bmq/tybc50bVC3Lv/uSnp5ujRs3zoqJibEiIiKsvn37Wtu3b7fv9+feLFiwwIqNjbVatmxp9e7d23rvvffs+/y5L5ZlWRMmTLBuu+02p/v8tTenTp2yJk6caHXt2tWKjo62+vbta23bts2+v6z0xWZZllW6Y7gAAADAhXGPKgAAAHwSQRUAAAA+iaAKAAAAn0RQBQAAgE8iqAIAAMAnEVQBAADgkwiqAAAA8EkEVQDwEYcOHVLTpk21atUql8+RmJiopk2bGqwKALynorcLAACY06dPH3Xq1MnbZQCAEQRVAChH6tatq7p163q7DAAwgql/ACiG2NhYTZ8+XVOmTFG7du3Url07jR49WidPnrQfs3z5csXFxSkqKkqtW7fWzTffrHXr1jmc58cff9SDDz6odu3aqW3btho8eLC+++47p9e0LEtjx45VRESENm3aJEn66aefNHToULVv316RkZHq27evPv74Y/trzp3637Ztm5o2ber0IzY21v6aX375RQ8//LDatWunyMhIDRgwQHv27DHWOwBwFSOqAFBMr7/+uho0aKDJkyfrxIkTSkhI0Pfff6/ly5fr3//+t5555hk98MADio+P16lTpzRv3jyNHj1aUVFRuuSSS5SWlqY+ffqodu3amjBhgkJDQzV79mwNHDhQa9euPe96zzzzjN555x3Nnj1bnTt3Vn5+vu6//37Vrl1bL7zwgipWrKglS5Zo2LBhWrdunRo0aODw+pYtW2rZsmUO2zZv3qzExETddtttkqQTJ07o9ttvV3BwsJ588kkFBwdr8eLF6tevn1asWKHGjRt7rqEAcAEEVQAoJpvNpoULF6pKlSqSpIsvvljDhw/Xpk2b9NNPP2nQoEEaPny4/fj69esrLi5OX3zxhS655BItXLhQZ86c0cKFC1W7dm1JUvPmzdW3b1/t3LlTTZo0sb82ISFBy5YtU2Jiorp06SJJSk9P14EDBzRkyBD7ttatW2vWrFnKzs4+r97Q0FBFRUXZvz548KAWL16s66+/XkOGDJEkLV68WKdOndK///1vXXrppZKkzp07q1evXnrppZc0c+ZMgx0EgJIhqAJAMXXr1s0eUqWC2wECAwO1Y8cOjR07VpL066+/KjU1VampqdqyZYskKTc3V5KUnJysqKgoe0iVpLCwMH344YeSClb9S9Jrr72m3bt36+abb1a3bt3sx9aqVUvh4eF68skn9dlnn6lz587q2LGjxo0bd8HaMzIyNHToUNWvX19Tpkyxb9+yZYuaN2+uOnXq6OzZs5KkgIAAde7cWWvWrHGpTwBgCkEVAIopLCzM4euAgABVr15dGRkZ+vHHHzV+/Hht3bpVFStWVKNGjez3ilqWJUk6deqU6tevf8Hr7Nu3T506ddI777yjAQMGqGXLlpIKRnQXLFigOXPm6L333tNbb72lwMBAXXPNNZo4caKqV6/u9Hx5eXkaNWqUMjIytGDBAgUHB9v3nTp1Sj/88IP9Gn+WlZXlcDwAlCaCKgAU06lTpxy+zsvL08mTJ3XxxRfrvvvuU2BgoN588021aNFCFStWVEpKisOoZJUqVXTixInzzrtlyxbVr19fNptNkvTQQw9pwIABuvHGG/XEE09o+fLlqlix4K/rOnXqaOLEiZowYYL27dunDRs2aN68eapWrZqeeuopp3U///zz2rZtmxYtWqRLLrnEYV+VKlXUrl07jRkzxulrg4KCit0fADCNVf8AUEyffPKJcnJy7F9v3LhRZ8+eVZMmTXTw4EHdeuutat26tT1UFq7Uz8/PlyS1adNGO3fuVHp6uv0cJ06c0ODBg7Vx40b7tlq1aqlSpUoaP3689uzZowULFkiSvvzyS1199dXatWuXbDabmjdvrlGjRqlJkyY6cuSI05pXrlypxYsXa/z48WrTps15+9u1a6eDBw/qiiuuUEREhP1jzZo1Wr58uSpUqOBm1wDAdYyoAkAxHTlyREOHDtXdd9+tw4cPa9q0aerYsaN69eqlqVOn6rXXXlPdunVVtWpVbd68WYsXL5ZUMH0uSQMHDtTq1at17733asiQIapUqZL+9a9/KSwsTH//+9/122+/OVyvU6dOuv766zVr1iz17NlTLVq0UOXKlTVmzBiNGDFCtWrV0meffaa9e/fq7rvvPq/enTt3asKECerRo4datWqlr776yn4bgiS1aNFCAwcO1Ntvv62BAwdq0KBBqlGjhtatW6c333yzWPe+AoAn2axz/9YCADgVGxur6OhoVa1aVatXr1ZISIhuvPFGjRo1SpUrV9a+ffv07LPPavfu3QoKClJ4eLiGDBmiyZMnq0mTJnrppZckSQcOHNCLL76obdu2KSgoyD7tftlll+nQoUPq3r27pkyZori4OElSWlqarr/+erVo0UJLlizRDz/8oISEBCUnJysjI0MNGzZU//791bdvX0kFz1GdNWuWvv32W/ufi7Jx40bVr19fP/74oxISErRlyxZlZ2fbz3nrrbd6vrEA8BcIqgBQDLGxsWrXrp2ee+45b5cCAH6De1QBAADgkwiqAAAA8ElM/QMAAMAnMaIKAAAAn0RQBQAAgE8iqAIAAMAnEVQBAADgkwiqAAAA8EkEVQAAAPgkgioAAAB8EkEVAAAAPomgCgAAAJ/0//fvXFutlD9lAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<__array_function__ internals>:200: RuntimeWarning: Converting input from bool to <class 'numpy.uint8'> for compatibility.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming 'df' is your DataFrame\n",
    "# Load your DataFrame or replace 'df' with your DataFrame variable\n",
    "\n",
    "# Set the style of seaborn\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "# Iterate through each column in the DataFrame and plot the distribution\n",
    "for column in ['store', 'saledate', 'quantity', 'orgprice', 'amt', 'packsize',\n",
    "       'cost', 'retail', 'deptdesc', 'brand', 'holiday', 'month', 'quarter', 'weekday']:\n",
    "    plt.figure(figsize=(8, 5))\n",
    "    sns.histplot(clean_tx_transation_final[column], kde=True, color='blue', bins=30)\n",
    "    plt.title(f'Distribution of {column}')\n",
    "    plt.xlabel(column)\n",
    "    plt.ylabel('Frequency')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "20695d0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final.to_pickle(f'clean_tx_transation.pkl')\n",
    "# pd.read_pickle(f\"clean_tx_transation.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "20bb8f63",
   "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>stype</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>packsize</th>\n",
       "      <th>brand</th>\n",
       "      <th>cost</th>\n",
       "      <th>retail</th>\n",
       "      <th>deptdesc</th>\n",
       "      <th>holiday</th>\n",
       "      <th>month</th>\n",
       "      <th>quarter</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-07-07</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>July</td>\n",
       "      <td>3</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-24</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-04-09</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>April</td>\n",
       "      <td>2</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-05-29</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>May</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5148332</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-06-12</td>\n",
       "      <td>R</td>\n",
       "      <td>1</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LIZ CLAI</td>\n",
       "      <td>14.4</td>\n",
       "      <td>12.5</td>\n",
       "      <td>CATALIN</td>\n",
       "      <td>False</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunday</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",
       "      <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>26482636</th>\n",
       "      <td>5093166</td>\n",
       "      <td>7707</td>\n",
       "      <td>2004-11-27</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>34.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>BLUE</td>\n",
       "      <td>False</td>\n",
       "      <td>November</td>\n",
       "      <td>4</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26482637</th>\n",
       "      <td>5093166</td>\n",
       "      <td>7707</td>\n",
       "      <td>2004-12-21</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>34.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>BLUE</td>\n",
       "      <td>False</td>\n",
       "      <td>December</td>\n",
       "      <td>4</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26482638</th>\n",
       "      <td>5093166</td>\n",
       "      <td>7707</td>\n",
       "      <td>2004-12-23</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>34.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>BLUE</td>\n",
       "      <td>False</td>\n",
       "      <td>December</td>\n",
       "      <td>4</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26482639</th>\n",
       "      <td>5093166</td>\n",
       "      <td>7707</td>\n",
       "      <td>2004-12-23</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>34.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>BLUE</td>\n",
       "      <td>False</td>\n",
       "      <td>December</td>\n",
       "      <td>4</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26482640</th>\n",
       "      <td>5093166</td>\n",
       "      <td>7707</td>\n",
       "      <td>2004-12-05</td>\n",
       "      <td>P</td>\n",
       "      <td>1</td>\n",
       "      <td>57.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>DESIGNER</td>\n",
       "      <td>34.5</td>\n",
       "      <td>57.5</td>\n",
       "      <td>BLUE</td>\n",
       "      <td>False</td>\n",
       "      <td>December</td>\n",
       "      <td>4</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13608192 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              sku  store   saledate stype  quantity  orgprice   amt  packsize  \\\n",
       "0         5148332   1007 2005-07-07     P         1      50.0  33.5       1.0   \n",
       "1         5148332   1007 2005-05-24     P         1      50.0  50.0       1.0   \n",
       "2         5148332   1007 2005-04-09     P         1      50.0  50.0       1.0   \n",
       "3         5148332   1007 2005-05-29     P         1      50.0  50.0       1.0   \n",
       "4         5148332   1007 2005-06-12     R         1      50.0  50.0       1.0   \n",
       "...           ...    ...        ...   ...       ...       ...   ...       ...   \n",
       "26482636  5093166   7707 2004-11-27     P         1      57.5  57.5       6.0   \n",
       "26482637  5093166   7707 2004-12-21     P         1      57.5  57.5       6.0   \n",
       "26482638  5093166   7707 2004-12-23     P         1      57.5  57.5       6.0   \n",
       "26482639  5093166   7707 2004-12-23     P         1      57.5  57.5       6.0   \n",
       "26482640  5093166   7707 2004-12-05     P         1      57.5  57.5       6.0   \n",
       "\n",
       "             brand  cost  retail deptdesc  holiday     month  quarter  \\\n",
       "0         LIZ CLAI  14.4    12.5  CATALIN    False      July        3   \n",
       "1         LIZ CLAI  14.4    12.5  CATALIN    False       May        2   \n",
       "2         LIZ CLAI  14.4    12.5  CATALIN    False     April        2   \n",
       "3         LIZ CLAI  14.4    12.5  CATALIN    False       May        2   \n",
       "4         LIZ CLAI  14.4    12.5  CATALIN    False      June        2   \n",
       "...            ...   ...     ...      ...      ...       ...      ...   \n",
       "26482636  DESIGNER  34.5    57.5     BLUE    False  November        4   \n",
       "26482637  DESIGNER  34.5    57.5     BLUE    False  December        4   \n",
       "26482638  DESIGNER  34.5    57.5     BLUE    False  December        4   \n",
       "26482639  DESIGNER  34.5    57.5     BLUE    False  December        4   \n",
       "26482640  DESIGNER  34.5    57.5     BLUE    False  December        4   \n",
       "\n",
       "           weekday  \n",
       "0         Thursday  \n",
       "1          Tuesday  \n",
       "2         Saturday  \n",
       "3           Sunday  \n",
       "4           Sunday  \n",
       "...            ...  \n",
       "26482636  Saturday  \n",
       "26482637   Tuesday  \n",
       "26482638  Thursday  \n",
       "26482639  Thursday  \n",
       "26482640    Sunday  \n",
       "\n",
       "[13608192 rows x 16 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exclude rows containing null values for the 'brands' column\n",
    "clean_tx_transation_final"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b834be1e",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "568e8a6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "stype\n",
       "P    12600008\n",
       "R     1008184\n",
       "dtype: int64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_final.groupby('stype').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "05d55e72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Only focus on successful transactions\n",
    "clean_tx_transation_final = clean_tx_transation_final[clean_tx_transation_final['stype'] == 'P']\n",
    "clean_tx_transation_final = clean_tx_transation_final.drop(columns=['stype', 'retail'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "c2dd595d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sku             0\n",
       "store           0\n",
       "saledate        0\n",
       "quantity        0\n",
       "orgprice        0\n",
       "amt             0\n",
       "packsize        0\n",
       "brand       13917\n",
       "cost            0\n",
       "deptdesc        0\n",
       "holiday         0\n",
       "month           0\n",
       "quarter         0\n",
       "weekday         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_final.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "c7d287ab",
   "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>packsize</th>\n",
       "      <th>brand</th>\n",
       "      <th>cost</th>\n",
       "      <th>deptdesc</th>\n",
       "      <th>holiday</th>\n",
       "      <th>month</th>\n",
       "      <th>quarter</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [sku, store, saledate, quantity, orgprice, amt, packsize, brand, cost, deptdesc, holiday, month, quarter, weekday]\n",
       "Index: []"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exclude rows containing null values for the 'deptdesc' column\n",
    "\n",
    "clean_tx_transation_final[clean_tx_transation_final['cost'] == 0]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd826bc5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "aa3d0c98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exclude rows where a single transaction is associated with a specific (sku, store) combination.\n",
    "clean_tx_transation_final = clean_tx_transation_final.groupby(['sku', 'store']).filter(lambda group: len(group) > 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "78200ef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11151734"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove outliers\n",
    "columns_to_check = ['quantity', 'orgprice', 'packsize', 'cost']\n",
    "quantile_threshold = 0.99\n",
    "quantiles = clean_tx_transation_final[columns_to_check].quantile(quantile_threshold)\n",
    "filter_condition = clean_tx_transation_final[columns_to_check] <= quantiles\n",
    "\n",
    "clean_tx_transation_final = clean_tx_transation_final[filter_condition.all(axis=1)]\n",
    "len(clean_tx_transation_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "2af43e7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Exclude rows where a single transaction is associated with a specific (sku, store) combination.\n",
    "clean_tx_transation_final = clean_tx_transation_final.groupby(['sku', 'store']).filter(lambda group: len(group) > 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c49f215e",
   "metadata": {},
   "source": [
    "## Lagged Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "f55fa557",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/bj/583srb2d5dz2jkljm63jkstw0000gn/T/ipykernel_51421/3501694491.py:3: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
      "  Before: .apply(func)\n",
      "  After:  .apply(func, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
      "  or:     .apply(func, meta=('x', 'f8'))            for series result\n",
      "  clean_tx_transation_final = dask_df.groupby(['sku', 'store']).apply(lambda group: group.sort_values('saledate')).compute().reset_index(drop=True)\n"
     ]
    }
   ],
   "source": [
    "import dask.dataframe as dd\n",
    "dask_df = dd.from_pandas(clean_tx_transation_final, npartitions=10)  # Adjust the number of partitions as needed\n",
    "clean_tx_transation_final = dask_df.groupby(['sku', 'store']).apply(lambda group: group.sort_values('saledate')).compute().reset_index(drop=True)\n",
    "clean_tx_transation_final.to_pickle(f'sorted_clean_tx_transation.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "e6101ac6",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final['lagged_amt'] = clean_tx_transation_final.groupby(['sku', 'store'])['amt'].shift()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "5415a372",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final['lagged_amt'].fillna(clean_tx_transation_final['orgprice'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "340c0efa",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final['lagged_orgprice'] = clean_tx_transation_final.groupby(['sku', 'store'])['orgprice'].shift()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "16eca05d",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final['lagged_orgprice'].fillna(clean_tx_transation_final['orgprice'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "6126d5d9",
   "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>sku</th>\n",
       "      <th>store</th>\n",
       "      <th>saledate</th>\n",
       "      <th>quantity</th>\n",
       "      <th>orgprice</th>\n",
       "      <th>amt</th>\n",
       "      <th>packsize</th>\n",
       "      <th>brand</th>\n",
       "      <th>cost</th>\n",
       "      <th>deptdesc</th>\n",
       "      <th>holiday</th>\n",
       "      <th>month</th>\n",
       "      <th>quarter</th>\n",
       "      <th>weekday</th>\n",
       "      <th>lagged_amt</th>\n",
       "      <th>lagged_orgprice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>262</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-08-07</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JOLIE IN</td>\n",
       "      <td>0.95</td>\n",
       "      <td>CARTERS</td>\n",
       "      <td>False</td>\n",
       "      <td>August</td>\n",
       "      <td>3</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>262</td>\n",
       "      <td>1007</td>\n",
       "      <td>2005-08-12</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JOLIE IN</td>\n",
       "      <td>0.95</td>\n",
       "      <td>CARTERS</td>\n",
       "      <td>False</td>\n",
       "      <td>August</td>\n",
       "      <td>3</td>\n",
       "      <td>Friday</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>262</td>\n",
       "      <td>1807</td>\n",
       "      <td>2005-06-03</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JOLIE IN</td>\n",
       "      <td>0.95</td>\n",
       "      <td>CARTERS</td>\n",
       "      <td>False</td>\n",
       "      <td>June</td>\n",
       "      <td>2</td>\n",
       "      <td>Friday</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>262</td>\n",
       "      <td>1807</td>\n",
       "      <td>2005-08-13</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JOLIE IN</td>\n",
       "      <td>0.95</td>\n",
       "      <td>CARTERS</td>\n",
       "      <td>False</td>\n",
       "      <td>August</td>\n",
       "      <td>3</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>262</td>\n",
       "      <td>2607</td>\n",
       "      <td>2005-08-08</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JOLIE IN</td>\n",
       "      <td>0.95</td>\n",
       "      <td>CARTERS</td>\n",
       "      <td>False</td>\n",
       "      <td>August</td>\n",
       "      <td>3</td>\n",
       "      <td>Monday</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sku  store   saledate  quantity  orgprice  amt  packsize     brand  cost  \\\n",
       "0  262   1007 2005-08-07         1       4.0  2.0       1.0  JOLIE IN  0.95   \n",
       "1  262   1007 2005-08-12         1       4.0  2.0       1.0  JOLIE IN  0.95   \n",
       "2  262   1807 2005-06-03         1       4.0  4.0       1.0  JOLIE IN  0.95   \n",
       "3  262   1807 2005-08-13         1       4.0  2.0       1.0  JOLIE IN  0.95   \n",
       "4  262   2607 2005-08-08         1       4.0  2.0       1.0  JOLIE IN  0.95   \n",
       "\n",
       "  deptdesc  holiday   month  quarter   weekday  lagged_amt  lagged_orgprice  \n",
       "0  CARTERS    False  August        3    Sunday         4.0              4.0  \n",
       "1  CARTERS    False  August        3    Friday         2.0              4.0  \n",
       "2  CARTERS    False    June        2    Friday         4.0              4.0  \n",
       "3  CARTERS    False  August        3  Saturday         4.0              4.0  \n",
       "4  CARTERS    False  August        3    Monday         4.0              4.0  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_tx_transation_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "8f895e1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sku                         int64\n",
       "store                      object\n",
       "saledate           datetime64[ns]\n",
       "quantity                    int64\n",
       "orgprice                  float64\n",
       "amt                       float64\n",
       "packsize                  float64\n",
       "brand                      object\n",
       "cost                      float64\n",
       "deptdesc                   object\n",
       "holiday                      bool\n",
       "month                      object\n",
       "quarter                    object\n",
       "weekday                    object\n",
       "lagged_amt                float64\n",
       "lagged_orgprice           float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns_to_change = ['store', 'quarter']\n",
    "clean_tx_transation_final[columns_to_change] = clean_tx_transation_final[columns_to_change].astype('object')\n",
    "clean_tx_transation_final.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "df1b7b95",
   "metadata": {},
   "outputs": [],
   "source": [
    "clean_tx_transation_final.to_pickle(f'sorted_clean_tx_transation.pkl')"
   ]
  }
 ],
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