Tools Ans Techniques Project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f9328bec",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9a46040a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "from itertools import combinations\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "84068127",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.metrics import accuracy_score,classification_report,confusion_matrix\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f60f241",
   "metadata": {},
   "source": [
    "###### Reading Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d553ca86",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>849</td>\n",
       "      <td>CA-2017-107503</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GA-14725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lorain</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>44052</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10003878</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Linden 10\" Round Wall Clock, Black</td>\n",
       "      <td>48.896</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>8.5568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10001215</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2\" Diameter Brentwood Wall ...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199.2606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>6683</td>\n",
       "      <td>CA-2017-154466</td>\n",
       "      <td>First Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53132</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002012</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Easy Flow II Sheet Lifters</td>\n",
       "      <td>3.600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8070</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-ST-10002743</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>SAFCO Boltless Steel Shelving</td>\n",
       "      <td>454.560</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-107.9580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8071</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-FU-10002116</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Carpeted, Granite-Look or Clear Contempo...</td>\n",
       "      <td>141.420</td>\n",
       "      <td>5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-187.3815</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "0  01/01/2020     849  CA-2017-107503  Standard Class    GA-14725   \n",
       "1  01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "2  01/01/2020    6683  CA-2017-154466     First Class    DP-13390   \n",
       "3  01/01/2020    8070  CA-2017-151750  Standard Class    JM-15250   \n",
       "4  01/01/2020    8071  CA-2017-151750  Standard Class    JM-15250   \n",
       "\n",
       "       Segment        Country         City       State  Postal Code   Region  \\\n",
       "0     Consumer  United States       Lorain        Ohio        44052     East   \n",
       "1     Consumer  United States  Los Angeles  California        90036     West   \n",
       "2  Home Office  United States     Franklin   Wisconsin        53132  Central   \n",
       "3     Consumer  United States   Huntsville       Texas        77340  Central   \n",
       "4     Consumer  United States   Huntsville       Texas        77340  Central   \n",
       "\n",
       "        Product ID         Category Sub-Category  \\\n",
       "0  FUR-FU-10003878        Furniture  Furnishings   \n",
       "1  FUR-FU-10001215        Furniture  Furnishings   \n",
       "2  OFF-BI-10002012  Office Supplies      Binders   \n",
       "3  OFF-ST-10002743  Office Supplies      Storage   \n",
       "4  FUR-FU-10002116        Furniture  Furnishings   \n",
       "\n",
       "                                        Product Name    Sales  Quantity  \\\n",
       "0                 Linden 10\" Round Wall Clock, Black   48.896         4   \n",
       "1  Howard Miller 11-1/2\" Diameter Brentwood Wall ...  474.430        11   \n",
       "2            Wilson Jones Easy Flow II Sheet Lifters    3.600         2   \n",
       "3                      SAFCO Boltless Steel Shelving  454.560         5   \n",
       "4  Tenex Carpeted, Granite-Look or Clear Contempo...  141.420         5   \n",
       "\n",
       "   Discount    Profit  \n",
       "0       0.2    8.5568  \n",
       "1       0.0  199.2606  \n",
       "2       0.0    1.7280  \n",
       "3       0.2 -107.9580  \n",
       "4       0.6 -187.3815  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# US E-commerce records 2020\n",
    "all_data = pd.read_csv(r'F:\\lareb\\ECommerceRecords2020.csv')\n",
    "all_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7a39e55",
   "metadata": {},
   "source": [
    "###### Replacing empty cell With NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "5efc193a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8073</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-AR-10003158</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Fluorescent Highlighters by Dixon</td>\n",
       "      <td>12.736</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.2288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>02/01/2020</td>\n",
       "      <td>8363</td>\n",
       "      <td>CA-2017-147207</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TS-21655</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>El Paso</td>\n",
       "      <td>Texas</td>\n",
       "      <td>79907</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-TA-10002958</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Bevis Oval Conference Table, Walnut</td>\n",
       "      <td>913.430</td>\n",
       "      <td>5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>-169.6370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>13/01/2020</td>\n",
       "      <td>6620</td>\n",
       "      <td>US-2017-167402</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CP-12085</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Springfield</td>\n",
       "      <td>Missouri</td>\n",
       "      <td>65807</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-AR-10004010</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Hunt Boston Vacuum Mount KS Pencil Sharpener</td>\n",
       "      <td>209.940</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.5844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>14/01/2020</td>\n",
       "      <td>4913</td>\n",
       "      <td>CA-2017-127306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BH-11710</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Johnson City</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>37604</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-BI-10002003</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Ibico Presentation Index for Binding Systems</td>\n",
       "      <td>5.970</td>\n",
       "      <td>5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-4.5770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>30/01/2020</td>\n",
       "      <td>774</td>\n",
       "      <td>CA-2017-104220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BV-11245</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Des Moines</td>\n",
       "      <td>Iowa</td>\n",
       "      <td>50315</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10003910</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>DXL Angle-View Binders with Locking Rings by S...</td>\n",
       "      <td>7.710</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.4695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>13/02/2020</td>\n",
       "      <td>2731</td>\n",
       "      <td>CA-2017-104801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FH-14350</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-AC-10001838</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Razer Tiamat Over Ear 7.1 Surround Sound PC Ga...</td>\n",
       "      <td>799.960</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>343.9828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>03/03/2020</td>\n",
       "      <td>3475</td>\n",
       "      <td>CA-2017-111815</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EP-13915</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Dearborn Heights</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>48127</td>\n",
       "      <td>Central</td>\n",
       "      <td>TEC-AC-10002926</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Logitech Wireless Marathon Mouse M705</td>\n",
       "      <td>99.980</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.9914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>09/03/2020</td>\n",
       "      <td>8541</td>\n",
       "      <td>CA-2017-147354</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KB-16315</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90008</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10003910</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>DXL Angle-View Binders with Locking Rings by S...</td>\n",
       "      <td>30.840</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>9.6375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>19/03/2020</td>\n",
       "      <td>4344</td>\n",
       "      <td>CA-2017-105410</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ND-18370</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94110</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-PH-10000038</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Jawbone MINI JAMBOX Wireless Bluetooth Speaker</td>\n",
       "      <td>657.504</td>\n",
       "      <td>6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-131.5008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578</th>\n",
       "      <td>14/04/2020</td>\n",
       "      <td>931</td>\n",
       "      <td>CA-2017-144932</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AB-10165</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Toledo</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>43615</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-AR-10001468</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Sanford Prismacolor Professional Thick Lead Ar...</td>\n",
       "      <td>89.856</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>21.3408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>18/05/2020</td>\n",
       "      <td>4426</td>\n",
       "      <td>CA-2017-159464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TB-21355</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sandy Springs</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30328</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-BI-10000315</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Poly Designer Cover &amp; Back</td>\n",
       "      <td>113.940</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.6912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>08/07/2020</td>\n",
       "      <td>349</td>\n",
       "      <td>CA-2017-134306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TD-20995</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lowell</td>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>1852</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-AR-10001374</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>BIC Brite Liner Highlighters, Chisel Tip</td>\n",
       "      <td>12.960</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1472</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order Date  Row ID        Order ID Ship Mode Customer ID    Segment  \\\n",
       "6     01/01/2020    8073  CA-2017-151750       NaN    JM-15250   Consumer   \n",
       "15    02/01/2020    8363  CA-2017-147207       NaN    TS-21655   Consumer   \n",
       "35    13/01/2020    6620  US-2017-167402       NaN    CP-12085  Corporate   \n",
       "45    14/01/2020    4913  CA-2017-127306       NaN    BH-11710   Consumer   \n",
       "142   30/01/2020     774  CA-2017-104220       NaN    BV-11245  Corporate   \n",
       "196   13/02/2020    2731  CA-2017-104801       NaN    FH-14350   Consumer   \n",
       "276   03/03/2020    3475  CA-2017-111815       NaN    EP-13915   Consumer   \n",
       "314   09/03/2020    8541  CA-2017-147354       NaN    KB-16315   Consumer   \n",
       "393   19/03/2020    4344  CA-2017-105410       NaN    ND-18370   Consumer   \n",
       "578   14/04/2020     931  CA-2017-144932       NaN    AB-10165   Consumer   \n",
       "841   18/05/2020    4426  CA-2017-159464       NaN    TB-21355  Corporate   \n",
       "1236  08/07/2020     349  CA-2017-134306       NaN    TD-20995   Consumer   \n",
       "\n",
       "            Country              City          State  Postal Code   Region  \\\n",
       "6     United States        Huntsville          Texas        77340  Central   \n",
       "15    United States           El Paso          Texas        79907  Central   \n",
       "35    United States       Springfield       Missouri        65807  Central   \n",
       "45    United States      Johnson City      Tennessee        37604    South   \n",
       "142   United States        Des Moines           Iowa        50315  Central   \n",
       "196   United States           Seattle     Washington        98105     West   \n",
       "276   United States  Dearborn Heights       Michigan        48127  Central   \n",
       "314   United States       Los Angeles     California        90008     West   \n",
       "393   United States     San Francisco     California        94110     West   \n",
       "578   United States            Toledo           Ohio        43615     East   \n",
       "841   United States     Sandy Springs        Georgia        30328    South   \n",
       "1236  United States            Lowell  Massachusetts         1852     East   \n",
       "\n",
       "           Product ID         Category Sub-Category  \\\n",
       "6     OFF-AR-10003158  Office Supplies          Art   \n",
       "15    FUR-TA-10002958        Furniture       Tables   \n",
       "35    OFF-AR-10004010  Office Supplies          Art   \n",
       "45    OFF-BI-10002003  Office Supplies      Binders   \n",
       "142   OFF-BI-10003910  Office Supplies      Binders   \n",
       "196   TEC-AC-10001838       Technology  Accessories   \n",
       "276   TEC-AC-10002926       Technology  Accessories   \n",
       "314   OFF-BI-10003910  Office Supplies      Binders   \n",
       "393   TEC-PH-10000038       Technology       Phones   \n",
       "578   OFF-AR-10001468  Office Supplies          Art   \n",
       "841   OFF-BI-10000315  Office Supplies      Binders   \n",
       "1236  OFF-AR-10001374  Office Supplies          Art   \n",
       "\n",
       "                                           Product Name    Sales  Quantity  \\\n",
       "6                     Fluorescent Highlighters by Dixon   12.736         4   \n",
       "15                  Bevis Oval Conference Table, Walnut  913.430         5   \n",
       "35         Hunt Boston Vacuum Mount KS Pencil Sharpener  209.940         6   \n",
       "45         Ibico Presentation Index for Binding Systems    5.970         5   \n",
       "142   DXL Angle-View Binders with Locking Rings by S...    7.710         1   \n",
       "196   Razer Tiamat Over Ear 7.1 Surround Sound PC Ga...  799.960         4   \n",
       "276               Logitech Wireless Marathon Mouse M705   99.980         2   \n",
       "314   DXL Angle-View Binders with Locking Rings by S...   30.840         5   \n",
       "393      Jawbone MINI JAMBOX Wireless Bluetooth Speaker  657.504         6   \n",
       "578   Sanford Prismacolor Professional Thick Lead Ar...   89.856         3   \n",
       "841                          Poly Designer Cover & Back  113.940         6   \n",
       "1236           BIC Brite Liner Highlighters, Chisel Tip   12.960         2   \n",
       "\n",
       "      Discount    Profit  \n",
       "6          0.2    2.2288  \n",
       "15         0.3 -169.6370  \n",
       "35         0.0   54.5844  \n",
       "45         0.7   -4.5770  \n",
       "142        0.0    3.4695  \n",
       "196        0.0  343.9828  \n",
       "276        0.0   42.9914  \n",
       "314        0.2    9.6375  \n",
       "393        0.2 -131.5008  \n",
       "578        0.2   21.3408  \n",
       "841        0.0   54.6912  \n",
       "1236       0.0    4.1472  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = all_data.replace(' ', np.nan)    \n",
    "nan_values = df[df.isna().any(axis=1)]\n",
    "nan_values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f65d212",
   "metadata": {},
   "source": [
    "###### Creating Duplicate Table without NaN values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a411e224",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>849</td>\n",
       "      <td>CA-2017-107503</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GA-14725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lorain</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>44052</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10003878</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Linden 10\" Round Wall Clock, Black</td>\n",
       "      <td>48.896</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>8.5568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10001215</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2\" Diameter Brentwood Wall ...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199.2606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>6683</td>\n",
       "      <td>CA-2017-154466</td>\n",
       "      <td>First Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53132</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002012</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Easy Flow II Sheet Lifters</td>\n",
       "      <td>3.600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8070</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-ST-10002743</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>SAFCO Boltless Steel Shelving</td>\n",
       "      <td>454.560</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-107.9580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8071</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-FU-10002116</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Carpeted, Granite-Look or Clear Contempo...</td>\n",
       "      <td>141.420</td>\n",
       "      <td>5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-187.3815</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3307</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>908</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-PH-10004774</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Gear Head AU3700S Headset</td>\n",
       "      <td>90.930</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.7279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3308</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>909</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-BI-10003684</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.7910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3309</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1297</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10002103</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl</td>\n",
       "      <td>13.904</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.5188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3310</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1298</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10004632</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>GBC Binding covers</td>\n",
       "      <td>20.720</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>6.4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3311</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>5092</td>\n",
       "      <td>CA-2017-156720</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15580</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Loveland</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>80538</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-FA-10003472</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Bagged Rubber Bands</td>\n",
       "      <td>3.024</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-0.6048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3300 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "0     01/01/2020     849  CA-2017-107503  Standard Class    GA-14725   \n",
       "1     01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "2     01/01/2020    6683  CA-2017-154466     First Class    DP-13390   \n",
       "3     01/01/2020    8070  CA-2017-151750  Standard Class    JM-15250   \n",
       "4     01/01/2020    8071  CA-2017-151750  Standard Class    JM-15250   \n",
       "...          ...     ...             ...             ...         ...   \n",
       "3307  30/12/2020     908  CA-2017-143259  Standard Class    PO-18865   \n",
       "3308  30/12/2020     909  CA-2017-143259  Standard Class    PO-18865   \n",
       "3309  30/12/2020    1297  CA-2017-115427  Standard Class    EB-13975   \n",
       "3310  30/12/2020    1298  CA-2017-115427  Standard Class    EB-13975   \n",
       "3311  30/12/2020    5092  CA-2017-156720  Standard Class    JM-15580   \n",
       "\n",
       "          Segment        Country           City       State  Postal Code  \\\n",
       "0        Consumer  United States         Lorain        Ohio        44052   \n",
       "1        Consumer  United States    Los Angeles  California        90036   \n",
       "2     Home Office  United States       Franklin   Wisconsin        53132   \n",
       "3        Consumer  United States     Huntsville       Texas        77340   \n",
       "4        Consumer  United States     Huntsville       Texas        77340   \n",
       "...           ...            ...            ...         ...          ...   \n",
       "3307     Consumer  United States  New York City    New York        10009   \n",
       "3308     Consumer  United States  New York City    New York        10009   \n",
       "3309    Corporate  United States      Fairfield  California        94533   \n",
       "3310    Corporate  United States      Fairfield  California        94533   \n",
       "3311     Consumer  United States       Loveland    Colorado        80538   \n",
       "\n",
       "       Region       Product ID         Category Sub-Category  \\\n",
       "0        East  FUR-FU-10003878        Furniture  Furnishings   \n",
       "1        West  FUR-FU-10001215        Furniture  Furnishings   \n",
       "2     Central  OFF-BI-10002012  Office Supplies      Binders   \n",
       "3     Central  OFF-ST-10002743  Office Supplies      Storage   \n",
       "4     Central  FUR-FU-10002116        Furniture  Furnishings   \n",
       "...       ...              ...              ...          ...   \n",
       "3307     East  TEC-PH-10004774       Technology       Phones   \n",
       "3308     East  OFF-BI-10003684  Office Supplies      Binders   \n",
       "3309     West  OFF-BI-10002103  Office Supplies      Binders   \n",
       "3310     West  OFF-BI-10004632  Office Supplies      Binders   \n",
       "3311     West  OFF-FA-10003472  Office Supplies    Fasteners   \n",
       "\n",
       "                                           Product Name    Sales  Quantity  \\\n",
       "0                    Linden 10\" Round Wall Clock, Black   48.896         4   \n",
       "1     Howard Miller 11-1/2\" Diameter Brentwood Wall ...  474.430        11   \n",
       "2               Wilson Jones Easy Flow II Sheet Lifters    3.600         2   \n",
       "3                         SAFCO Boltless Steel Shelving  454.560         5   \n",
       "4     Tenex Carpeted, Granite-Look or Clear Contempo...  141.420         5   \n",
       "...                                                 ...      ...       ...   \n",
       "3307                          Gear Head AU3700S Headset   90.930         7   \n",
       "3308               Wilson Jones Legal Size Ring Binders   52.776         3   \n",
       "3309    Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl   13.904         2   \n",
       "3310                                 GBC Binding covers   20.720         2   \n",
       "3311                                Bagged Rubber Bands    3.024         3   \n",
       "\n",
       "      Discount    Profit  \n",
       "0          0.2    8.5568  \n",
       "1          0.0  199.2606  \n",
       "2          0.0    1.7280  \n",
       "3          0.2 -107.9580  \n",
       "4          0.6 -187.3815  \n",
       "...        ...       ...  \n",
       "3307       0.0    2.7279  \n",
       "3308       0.2   19.7910  \n",
       "3309       0.2    4.5188  \n",
       "3310       0.2    6.4750  \n",
       "3311       0.2   -0.6048  \n",
       "\n",
       "[3300 rows x 19 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "withoutNaN=df.dropna()\n",
    "withoutNaN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bca8dcf",
   "metadata": {},
   "source": [
    "###### Adjusting missing values of Ship Mode Column with its respective values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "ce30f9b1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CA-2017-151750 8073\n",
      "CA-2017-147207 8363\n",
      "US-2017-167402 6620\n",
      "CA-2017-127306 4913\n",
      "CA-2017-104220 774\n",
      "CA-2017-104801 2731\n",
      "CA-2017-111815 3475\n",
      "CA-2017-147354 8541\n",
      "CA-2017-105410 4344\n",
      "CA-2017-144932 931\n",
      "CA-2017-159464 4426\n",
      "CA-2017-134306 349\n"
     ]
    }
   ],
   "source": [
    "for ndex, row in nan_values.iterrows():\n",
    "    print(row['Order ID'],row['Row ID'])\n",
    "    ww=withoutNaN[withoutNaN['Order ID'].str.contains(row['Order ID'])]['Ship Mode'].iloc[0]\n",
    "    \n",
    "#     print( (df[12:]['Row ID']==row['Row ID'])&(df[12:]['Order ID']==row['Order ID']) )\n",
    "    df.loc[(df['Row ID']==row['Row ID'])&(df['Order ID']==row['Order ID']),'Ship Mode']=ww\n",
    "    \n",
    "# missing=nan_values['Order ID'].astype(pd.StringDtype())\n",
    "# missing\n",
    "\n",
    "# df[df['Order ID'].str.contains(missing)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "158d5fc9",
   "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>Order Date</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profit</th>\n",
       "      <th>json</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>13/02/2020</td>\n",
       "      <td>CA-2017-104801</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>FH-14350</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>6.63</td>\n",
       "      <td>1.7901</td>\n",
       "      <td>{'Row ID': 2730, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>13/02/2020</td>\n",
       "      <td>CA-2017-104801</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>FH-14350</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>799.96</td>\n",
       "      <td>343.9828</td>\n",
       "      <td>{'Row ID': 2731, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>13/02/2020</td>\n",
       "      <td>CA-2017-104801</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>FH-14350</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>107.53</td>\n",
       "      <td>21.5060</td>\n",
       "      <td>{'Row ID': 2732, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Order Date        Order ID       Ship Mode Customer ID   Segment  \\\n",
       "195  13/02/2020  CA-2017-104801  Standard Class    FH-14350  Consumer   \n",
       "196  13/02/2020  CA-2017-104801  Standard Class    FH-14350  Consumer   \n",
       "197  13/02/2020  CA-2017-104801  Standard Class    FH-14350  Consumer   \n",
       "\n",
       "           Country     City       State  Postal Code Region   Sales    Profit  \\\n",
       "195  United States  Seattle  Washington        98105   West    6.63    1.7901   \n",
       "196  United States  Seattle  Washington        98105   West  799.96  343.9828   \n",
       "197  United States  Seattle  Washington        98105   West  107.53   21.5060   \n",
       "\n",
       "                                                  json  \n",
       "195  {'Row ID': 2730, 'Category': 'Office Supplies'...  \n",
       "196  {'Row ID': 2731, 'Category': 'Technology', 'Su...  \n",
       "197  {'Row ID': 2732, 'Category': 'Furniture', 'Sub...  "
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Order ID'].str.contains('CA-2017-104801')]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "832cd177",
   "metadata": {},
   "source": [
    "###### Changing dataType of columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "981ef841",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Order ID'] = df['Order ID'].astype(pd.StringDtype())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "4e782f7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Row ID'] = df['Row ID'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "id": "8a74e972",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Order Date       object\n",
       "Row ID            int64\n",
       "Order ID         object\n",
       "Ship Mode        object\n",
       "Customer ID      object\n",
       "Segment          object\n",
       "Country          object\n",
       "City             object\n",
       "State            object\n",
       "Postal Code       int64\n",
       "Region           object\n",
       "Product ID       object\n",
       "Category         object\n",
       "Sub-Category     object\n",
       "Product Name     object\n",
       "Sales           float64\n",
       "Quantity          int64\n",
       "Discount        float64\n",
       "Profit          float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87888dee",
   "metadata": {},
   "source": [
    "###### Replacing inverted Commas to in words value, to stop error generation which consider it as a end of the string. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "e36b3bb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        9\n",
       "1       20\n",
       "2       -1\n",
       "3       -1\n",
       "4       -1\n",
       "        ..\n",
       "3307    -1\n",
       "3308    -1\n",
       "3309    -1\n",
       "3310    -1\n",
       "3311    -1\n",
       "Name: Product Name, Length: 3312, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " df[\"Product Name\"].str.find('\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "4c66f64f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Product Name\"]=df[\"Product Name\"].str.replace('\"',' inches')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba3de8d8",
   "metadata": {},
   "source": [
    "###### Creating Copy of Clean DataSet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2bcdf4f1",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>849</td>\n",
       "      <td>CA-2017-107503</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GA-14725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lorain</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>44052</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10003878</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Linden 10 inches Round Wall Clock, Black</td>\n",
       "      <td>48.896</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>8.5568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10001215</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2 inches Diameter Brentwood...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199.2606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>6683</td>\n",
       "      <td>CA-2017-154466</td>\n",
       "      <td>First Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53132</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002012</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Easy Flow II Sheet Lifters</td>\n",
       "      <td>3.600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8070</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-ST-10002743</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>SAFCO Boltless Steel Shelving</td>\n",
       "      <td>454.560</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-107.9580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8071</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-FU-10002116</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Carpeted, Granite-Look or Clear Contempo...</td>\n",
       "      <td>141.420</td>\n",
       "      <td>5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-187.3815</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3307</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>908</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-PH-10004774</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Gear Head AU3700S Headset</td>\n",
       "      <td>90.930</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.7279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3308</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>909</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-BI-10003684</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.7910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3309</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1297</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10002103</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl</td>\n",
       "      <td>13.904</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.5188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3310</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1298</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10004632</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>GBC Binding covers</td>\n",
       "      <td>20.720</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>6.4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3311</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>5092</td>\n",
       "      <td>CA-2017-156720</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15580</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Loveland</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>80538</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-FA-10003472</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Bagged Rubber Bands</td>\n",
       "      <td>3.024</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-0.6048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3312 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "0     01/01/2020     849  CA-2017-107503  Standard Class    GA-14725   \n",
       "1     01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "2     01/01/2020    6683  CA-2017-154466     First Class    DP-13390   \n",
       "3     01/01/2020    8070  CA-2017-151750  Standard Class    JM-15250   \n",
       "4     01/01/2020    8071  CA-2017-151750  Standard Class    JM-15250   \n",
       "...          ...     ...             ...             ...         ...   \n",
       "3307  30/12/2020     908  CA-2017-143259  Standard Class    PO-18865   \n",
       "3308  30/12/2020     909  CA-2017-143259  Standard Class    PO-18865   \n",
       "3309  30/12/2020    1297  CA-2017-115427  Standard Class    EB-13975   \n",
       "3310  30/12/2020    1298  CA-2017-115427  Standard Class    EB-13975   \n",
       "3311  30/12/2020    5092  CA-2017-156720  Standard Class    JM-15580   \n",
       "\n",
       "          Segment        Country           City       State  Postal Code  \\\n",
       "0        Consumer  United States         Lorain        Ohio        44052   \n",
       "1        Consumer  United States    Los Angeles  California        90036   \n",
       "2     Home Office  United States       Franklin   Wisconsin        53132   \n",
       "3        Consumer  United States     Huntsville       Texas        77340   \n",
       "4        Consumer  United States     Huntsville       Texas        77340   \n",
       "...           ...            ...            ...         ...          ...   \n",
       "3307     Consumer  United States  New York City    New York        10009   \n",
       "3308     Consumer  United States  New York City    New York        10009   \n",
       "3309    Corporate  United States      Fairfield  California        94533   \n",
       "3310    Corporate  United States      Fairfield  California        94533   \n",
       "3311     Consumer  United States       Loveland    Colorado        80538   \n",
       "\n",
       "       Region       Product ID         Category Sub-Category  \\\n",
       "0        East  FUR-FU-10003878        Furniture  Furnishings   \n",
       "1        West  FUR-FU-10001215        Furniture  Furnishings   \n",
       "2     Central  OFF-BI-10002012  Office Supplies      Binders   \n",
       "3     Central  OFF-ST-10002743  Office Supplies      Storage   \n",
       "4     Central  FUR-FU-10002116        Furniture  Furnishings   \n",
       "...       ...              ...              ...          ...   \n",
       "3307     East  TEC-PH-10004774       Technology       Phones   \n",
       "3308     East  OFF-BI-10003684  Office Supplies      Binders   \n",
       "3309     West  OFF-BI-10002103  Office Supplies      Binders   \n",
       "3310     West  OFF-BI-10004632  Office Supplies      Binders   \n",
       "3311     West  OFF-FA-10003472  Office Supplies    Fasteners   \n",
       "\n",
       "                                           Product Name    Sales  Quantity  \\\n",
       "0              Linden 10 inches Round Wall Clock, Black   48.896         4   \n",
       "1     Howard Miller 11-1/2 inches Diameter Brentwood...  474.430        11   \n",
       "2               Wilson Jones Easy Flow II Sheet Lifters    3.600         2   \n",
       "3                         SAFCO Boltless Steel Shelving  454.560         5   \n",
       "4     Tenex Carpeted, Granite-Look or Clear Contempo...  141.420         5   \n",
       "...                                                 ...      ...       ...   \n",
       "3307                          Gear Head AU3700S Headset   90.930         7   \n",
       "3308               Wilson Jones Legal Size Ring Binders   52.776         3   \n",
       "3309    Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl   13.904         2   \n",
       "3310                                 GBC Binding covers   20.720         2   \n",
       "3311                                Bagged Rubber Bands    3.024         3   \n",
       "\n",
       "      Discount    Profit  \n",
       "0          0.2    8.5568  \n",
       "1          0.0  199.2606  \n",
       "2          0.0    1.7280  \n",
       "3          0.2 -107.9580  \n",
       "4          0.6 -187.3815  \n",
       "...        ...       ...  \n",
       "3307       0.0    2.7279  \n",
       "3308       0.2   19.7910  \n",
       "3309       0.2    4.5188  \n",
       "3310       0.2    6.4750  \n",
       "3311       0.2   -0.6048  \n",
       "\n",
       "[3312 rows x 19 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original=df\n",
    "df_original"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b488e9ae",
   "metadata": {},
   "source": [
    "###### Summerizing DataSet "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "f2c52edc",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['Row ID','Category','Sub-Category','Product ID', 'Product Name', 'Sales', 'Quantity', 'Discount', 'Profit']\n",
    "df['json'] = df[columns].to_dict(orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "aa9fd1dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Row ID': 849,\n",
       " 'Category': 'Furniture',\n",
       " 'Sub-Category': 'Furnishings',\n",
       " 'Product ID': 'FUR-FU-10003878',\n",
       " 'Product Name': 'Linden 10 inches Round Wall Clock, Black',\n",
       " 'Sales': 48.896,\n",
       " 'Quantity': 4,\n",
       " 'Discount': 0.2,\n",
       " 'Profit': 8.5568}"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0]['json']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "150adb00",
   "metadata": {},
   "outputs": [],
   "source": [
    "dropColumns = ['Row ID','Category','Sub-Category','Product ID', 'Product Name', 'Quantity', 'Discount']\n",
    "df = df.drop(columns=dropColumns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cc2cb4db",
   "metadata": {},
   "outputs": [],
   "source": [
    "aggregation_functions = {\n",
    "   'Sales': 'sum',\n",
    "   'Profit': 'sum',\n",
    "   'Order Date': 'first',\n",
    "   'Ship Mode': 'first',\n",
    "   'Customer ID': 'first',\n",
    "   'Segment': 'first',\n",
    "   'Country': 'first',\n",
    "   'City': 'first',\n",
    "   'State': 'first',\n",
    "   'Postal Code': 'first',\n",
    "   'Region': 'first'\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df04c533",
   "metadata": {},
   "source": [
    "##### Generate aggregated copy of dataset for Profit and Sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "13afdccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "aggDf = df.groupby(df['Order ID']).aggregate(aggregation_functions)\n",
    "# aggDf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c955f59e",
   "metadata": {},
   "source": [
    "##### Generate Copy of dataset merged on each Order ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "67c0e753",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new = df.groupby(df['Order ID'])['json'].apply(list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "67a6ad0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_new.columns =['Order ID', 'Json']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "76db04af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "4937b543",
   "metadata": {},
   "outputs": [],
   "source": [
    "dd=pd.merge(aggDf,df_new,on='Order ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "ff5fa4d4",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>json</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Order ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA-2017-100013</th>\n",
       "      <td>29.690</td>\n",
       "      <td>12.2162</td>\n",
       "      <td>06/11/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>ZC-21910</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90045</td>\n",
       "      <td>West</td>\n",
       "      <td>[{'Row ID': 1229, 'Category': 'Office Supplies...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100055</th>\n",
       "      <td>152.590</td>\n",
       "      <td>46.1733</td>\n",
       "      <td>28/05/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MD-17860</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Laurel</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>20707</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 9132, 'Category': 'Furniture', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100097</th>\n",
       "      <td>1115.250</td>\n",
       "      <td>302.4705</td>\n",
       "      <td>26/11/2020</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>MN-17935</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 7320, 'Category': 'Technology', 'S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100111</th>\n",
       "      <td>7359.918</td>\n",
       "      <td>1571.7964</td>\n",
       "      <td>20/09/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SV-20365</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10035</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 6091, 'Category': 'Furniture', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100160</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>CB-12025</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19134</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 4152, 'Category': 'Office Supplies...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-168802</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>03/11/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JO-15145</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98103</td>\n",
       "      <td>West</td>\n",
       "      <td>[{'Row ID': 8294, 'Category': 'Office Supplies...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169320</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>23/07/2020</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>LH-16900</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Elkhart</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>46514</td>\n",
       "      <td>Central</td>\n",
       "      <td>[{'Row ID': 4373, 'Category': 'Office Supplies...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169488</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>AA-10375</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Providence</td>\n",
       "      <td>Rhode Island</td>\n",
       "      <td>2908</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 9539, 'Category': 'Office Supplies...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169502</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MG-17650</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53209</td>\n",
       "      <td>Central</td>\n",
       "      <td>[{'Row ID': 4598, 'Category': 'Office Supplies...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169551</th>\n",
       "      <td>1344.838</td>\n",
       "      <td>-62.2895</td>\n",
       "      <td>07/07/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>RL-19615</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19120</td>\n",
       "      <td>East</td>\n",
       "      <td>[{'Row ID': 5930, 'Category': 'Furniture', 'Su...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Sales     Profit  Order Date       Ship Mode Customer ID  \\\n",
       "Order ID                                                                      \n",
       "CA-2017-100013    29.690    12.2162  06/11/2020  Standard Class    ZC-21910   \n",
       "CA-2017-100055   152.590    46.1733  28/05/2020  Standard Class    MD-17860   \n",
       "CA-2017-100097  1115.250   302.4705  26/11/2020    Second Class    MN-17935   \n",
       "CA-2017-100111  7359.918  1571.7964  20/09/2020  Standard Class    SV-20365   \n",
       "CA-2017-100160    49.688    16.9641  07/09/2020  Standard Class    CB-12025   \n",
       "...                  ...        ...         ...             ...         ...   \n",
       "US-2017-168802    18.368     5.9696  03/11/2020  Standard Class    JO-15145   \n",
       "US-2017-169320   171.430    16.6721  23/07/2020    Second Class    LH-16900   \n",
       "US-2017-169488    56.860    26.5552  07/09/2020     First Class    AA-10375   \n",
       "US-2017-169502   113.410    32.4527  28/08/2020  Standard Class    MG-17650   \n",
       "US-2017-169551  1344.838   -62.2895  07/07/2020     First Class    RL-19615   \n",
       "\n",
       "                    Segment        Country           City         State  \\\n",
       "Order ID                                                                  \n",
       "CA-2017-100013     Consumer  United States    Los Angeles    California   \n",
       "CA-2017-100055    Corporate  United States         Laurel      Maryland   \n",
       "CA-2017-100097     Consumer  United States  New York City      New York   \n",
       "CA-2017-100111     Consumer  United States  New York City      New York   \n",
       "CA-2017-100160     Consumer  United States   Philadelphia  Pennsylvania   \n",
       "...                     ...            ...            ...           ...   \n",
       "US-2017-168802    Corporate  United States        Seattle    Washington   \n",
       "US-2017-169320     Consumer  United States        Elkhart       Indiana   \n",
       "US-2017-169488     Consumer  United States     Providence  Rhode Island   \n",
       "US-2017-169502  Home Office  United States      Milwaukee     Wisconsin   \n",
       "US-2017-169551     Consumer  United States   Philadelphia  Pennsylvania   \n",
       "\n",
       "                Postal Code   Region  \\\n",
       "Order ID                               \n",
       "CA-2017-100013        90045     West   \n",
       "CA-2017-100055        20707     East   \n",
       "CA-2017-100097        10009     East   \n",
       "CA-2017-100111        10035     East   \n",
       "CA-2017-100160        19134     East   \n",
       "...                     ...      ...   \n",
       "US-2017-168802        98103     West   \n",
       "US-2017-169320        46514  Central   \n",
       "US-2017-169488         2908     East   \n",
       "US-2017-169502        53209  Central   \n",
       "US-2017-169551        19120     East   \n",
       "\n",
       "                                                             json  \n",
       "Order ID                                                           \n",
       "CA-2017-100013  [{'Row ID': 1229, 'Category': 'Office Supplies...  \n",
       "CA-2017-100055  [{'Row ID': 9132, 'Category': 'Furniture', 'Su...  \n",
       "CA-2017-100097  [{'Row ID': 7320, 'Category': 'Technology', 'S...  \n",
       "CA-2017-100111  [{'Row ID': 6091, 'Category': 'Furniture', 'Su...  \n",
       "CA-2017-100160  [{'Row ID': 4152, 'Category': 'Office Supplies...  \n",
       "...                                                           ...  \n",
       "US-2017-168802  [{'Row ID': 8294, 'Category': 'Office Supplies...  \n",
       "US-2017-169320  [{'Row ID': 4373, 'Category': 'Office Supplies...  \n",
       "US-2017-169488  [{'Row ID': 9539, 'Category': 'Office Supplies...  \n",
       "US-2017-169502  [{'Row ID': 4598, 'Category': 'Office Supplies...  \n",
       "US-2017-169551  [{'Row ID': 5930, 'Category': 'Furniture', 'Su...  \n",
       "\n",
       "[1687 rows x 12 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a1b892d",
   "metadata": {},
   "source": [
    "##### save aggregated Data to Csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "f3245237",
   "metadata": {},
   "outputs": [],
   "source": [
    "dd.to_csv(r'F:\\lareb\\USDataAggregated2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "e65e0392",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sales          float64\n",
       "Profit         float64\n",
       "Order Date      object\n",
       "Ship Mode       object\n",
       "Customer ID     object\n",
       "Segment         object\n",
       "Country         object\n",
       "City            object\n",
       "State           object\n",
       "Postal Code      int64\n",
       "Region          object\n",
       "json            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ab94327",
   "metadata": {},
   "source": [
    "##### Converting 'Postal Code' data type to avoid calculation on address column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "c799b2ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "dd['Postal Code'] = dd['Postal Code'].astype(pd.StringDtype())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b29ce46",
   "metadata": {},
   "source": [
    "##### Adding Month Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "f4b0f54a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dd['Month'] = dd['Order Date'].str[3:5]\n",
    "dd['Month'] = dd['Month'].astype('int32')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e3efc38",
   "metadata": {},
   "source": [
    "##### Generating Random colors for the Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "51b37e21",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_colors = list(plt.cm.colors.cnames.keys())\n",
    "random.seed(100)\n",
    "c = random.choices(all_colors, k=350)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fad58a4",
   "metadata": {},
   "source": [
    "# EXPLORATORY DATA ANALYSIS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62d49198",
   "metadata": {},
   "source": [
    "### 1. Month Wise Profit And Sales Report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "83fed4f8",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>43971.3740</td>\n",
       "      <td>7140.4391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20301.1334</td>\n",
       "      <td>1613.8720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>58872.3528</td>\n",
       "      <td>14751.8915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36521.5361</td>\n",
       "      <td>933.2900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>44261.1102</td>\n",
       "      <td>6342.5828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>52981.7257</td>\n",
       "      <td>8223.3357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>45264.4160</td>\n",
       "      <td>6952.6212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>63120.8880</td>\n",
       "      <td>9040.9557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>87866.6520</td>\n",
       "      <td>10991.5556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>77776.9232</td>\n",
       "      <td>9275.2755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>118447.8250</td>\n",
       "      <td>9690.1037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>83829.3188</td>\n",
       "      <td>8483.3468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Sales      Profit\n",
       "Month                         \n",
       "1       43971.3740   7140.4391\n",
       "2       20301.1334   1613.8720\n",
       "3       58872.3528  14751.8915\n",
       "4       36521.5361    933.2900\n",
       "5       44261.1102   6342.5828\n",
       "6       52981.7257   8223.3357\n",
       "7       45264.4160   6952.6212\n",
       "8       63120.8880   9040.9557\n",
       "9       87866.6520  10991.5556\n",
       "10      77776.9232   9275.2755\n",
       "11     118447.8250   9690.1037\n",
       "12      83829.3188   8483.3468"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.sort_values('Month', ascending=True).groupby(['Month']).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b35df70",
   "metadata": {},
   "source": [
    "### 2. Month Wise Sales Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "99cc4b29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul','Aug', 'Sep', 'Oct', 'Nov', 'Dec']\n",
    "\n",
    "\n",
    "plt.bar(months,dd.groupby(['Month']).sum()['Sales'], color=c)\n",
    "plt.xticks(months)\n",
    "plt.title(\"Month Wise Sales\", fontsize=16)\n",
    "plt.ylabel('Sales in USD ($)')\n",
    "plt.xlabel('Month')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0418c5e",
   "metadata": {},
   "source": [
    "### 3. Month Wise Profit Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "d683f652",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul','Aug', 'Sep', 'Oct', 'Nov', 'Dec']\n",
    "\n",
    "plt.bar(months,dd.groupby(['Month']).sum()['Profit'], color=c)\n",
    "plt.xticks(months)\n",
    "plt.title(\"Month Wise Profit\", fontsize=16)\n",
    "plt.ylabel('Profit in USD ($)')\n",
    "plt.xlabel('Month')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "6a497d4c",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['Month'] not found in axis\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-270-5205bdea8825>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdd\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Month'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4306\u001b[0m                 \u001b[0mweight\u001b[0m  \u001b[1;36m1.0\u001b[0m     \u001b[1;36m0.8\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4307\u001b[0m         \"\"\"\n\u001b[1;32m-> 4308\u001b[1;33m         return super().drop(\n\u001b[0m\u001b[0;32m   4309\u001b[0m             \u001b[0mlabels\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4310\u001b[0m             \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4151\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4152\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4153\u001b[1;33m                 \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   4154\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4155\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[1;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[0;32m   4186\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4187\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4188\u001b[1;33m                 \u001b[0mnew_axis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   4189\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4190\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, errors)\u001b[0m\n\u001b[0;32m   5589\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0many\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5590\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m\"ignore\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5591\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5592\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5593\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Month'] not found in axis\""
     ]
    }
   ],
   "source": [
    "dd=dd.drop('Month',axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16f5bc7e",
   "metadata": {},
   "source": [
    "### 4. Region Wise Sales and Profit Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "id": "15e5fc0f",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Central</th>\n",
       "      <td>147098.1282</td>\n",
       "      <td>7550.8442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East</th>\n",
       "      <td>213082.9040</td>\n",
       "      <td>33230.5614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South</th>\n",
       "      <td>122905.8575</td>\n",
       "      <td>8848.9079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West</th>\n",
       "      <td>250128.3655</td>\n",
       "      <td>43808.9561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Sales      Profit\n",
       "Region                          \n",
       "Central  147098.1282   7550.8442\n",
       "East     213082.9040  33230.5614\n",
       "South    122905.8575   8848.9079\n",
       "West     250128.3655  43808.9561"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.groupby(['Region']).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9ff4d56",
   "metadata": {},
   "source": [
    "### 5. State Wise Sales and Profit Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "5bbc3e38",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>State</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>1828.2500</td>\n",
       "      <td>496.3771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>11133.5370</td>\n",
       "      <td>-1276.0025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>2707.6400</td>\n",
       "      <td>959.4027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>146388.3445</td>\n",
       "      <td>29366.4589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>10299.8130</td>\n",
       "      <td>-4435.8483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>5307.2100</td>\n",
       "      <td>1479.7616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>13754.9830</td>\n",
       "      <td>6053.2049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>77.7600</td>\n",
       "      <td>35.0640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>26444.7155</td>\n",
       "      <td>244.1266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>19160.0200</td>\n",
       "      <td>6447.9819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>1233.5480</td>\n",
       "      <td>199.0086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>24351.6110</td>\n",
       "      <td>-6745.5600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>18516.4500</td>\n",
       "      <td>5139.5257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>716.4100</td>\n",
       "      <td>275.8638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>733.1500</td>\n",
       "      <td>263.3644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>15534.8400</td>\n",
       "      <td>4751.7214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>5501.5500</td>\n",
       "      <td>1212.9041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>9451.6000</td>\n",
       "      <td>2780.6070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>8143.0760</td>\n",
       "      <td>1710.5869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>25833.6490</td>\n",
       "      <td>8487.7618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>6728.2500</td>\n",
       "      <td>2459.8789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>2997.2400</td>\n",
       "      <td>1028.5620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>9350.8000</td>\n",
       "      <td>1733.4305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>4229.2800</td>\n",
       "      <td>1465.9255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>3579.3500</td>\n",
       "      <td>921.0303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>3138.1580</td>\n",
       "      <td>305.1947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>1509.4300</td>\n",
       "      <td>480.2140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>9483.5500</td>\n",
       "      <td>2266.0707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>2818.5580</td>\n",
       "      <td>827.3904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>93922.9950</td>\n",
       "      <td>24357.0717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>23456.8290</td>\n",
       "      <td>-5088.5334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>919.9100</td>\n",
       "      <td>230.1497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>23264.8500</td>\n",
       "      <td>-1736.5270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>6225.9100</td>\n",
       "      <td>1754.7516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>2886.5930</td>\n",
       "      <td>-377.1257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>42688.3060</td>\n",
       "      <td>-5112.8034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>3427.1100</td>\n",
       "      <td>467.4135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>1560.7500</td>\n",
       "      <td>294.6375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>1153.4100</td>\n",
       "      <td>346.0717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>16113.8230</td>\n",
       "      <td>-3304.2866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>43421.7582</td>\n",
       "      <td>-8838.5049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>2460.6380</td>\n",
       "      <td>477.1747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>842.2100</td>\n",
       "      <td>263.9759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>7600.2000</td>\n",
       "      <td>1806.0146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>65539.8960</td>\n",
       "      <td>17256.7798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>1209.8240</td>\n",
       "      <td>185.9216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>5567.4700</td>\n",
       "      <td>1523.0807</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Sales      Profit\n",
       "State                                        \n",
       "Alabama                 1828.2500    496.3771\n",
       "Arizona                11133.5370  -1276.0025\n",
       "Arkansas                2707.6400    959.4027\n",
       "California            146388.3445  29366.4589\n",
       "Colorado               10299.8130  -4435.8483\n",
       "Connecticut             5307.2100   1479.7616\n",
       "Delaware               13754.9830   6053.2049\n",
       "District of Columbia      77.7600     35.0640\n",
       "Florida                26444.7155    244.1266\n",
       "Georgia                19160.0200   6447.9819\n",
       "Idaho                   1233.5480    199.0086\n",
       "Illinois               24351.6110  -6745.5600\n",
       "Indiana                18516.4500   5139.5257\n",
       "Iowa                     716.4100    275.8638\n",
       "Kansas                   733.1500    263.3644\n",
       "Kentucky               15534.8400   4751.7214\n",
       "Louisiana               5501.5500   1212.9041\n",
       "Maryland                9451.6000   2780.6070\n",
       "Massachusetts           8143.0760   1710.5869\n",
       "Michigan               25833.6490   8487.7618\n",
       "Minnesota               6728.2500   2459.8789\n",
       "Mississippi             2997.2400   1028.5620\n",
       "Missouri                9350.8000   1733.4305\n",
       "Montana                 4229.2800   1465.9255\n",
       "Nebraska                3579.3500    921.0303\n",
       "Nevada                  3138.1580    305.1947\n",
       "New Hampshire           1509.4300    480.2140\n",
       "New Jersey              9483.5500   2266.0707\n",
       "New Mexico              2818.5580    827.3904\n",
       "New York               93922.9950  24357.0717\n",
       "North Carolina         23456.8290  -5088.5334\n",
       "North Dakota             919.9100    230.1497\n",
       "Ohio                   23264.8500  -1736.5270\n",
       "Oklahoma                6225.9100   1754.7516\n",
       "Oregon                  2886.5930   -377.1257\n",
       "Pennsylvania           42688.3060  -5112.8034\n",
       "Rhode Island            3427.1100    467.4135\n",
       "South Carolina          1560.7500    294.6375\n",
       "South Dakota            1153.4100    346.0717\n",
       "Tennessee              16113.8230  -3304.2866\n",
       "Texas                  43421.7582  -8838.5049\n",
       "Utah                    2460.6380    477.1747\n",
       "Vermont                  842.2100    263.9759\n",
       "Virginia                7600.2000   1806.0146\n",
       "Washington             65539.8960  17256.7798\n",
       "West Virginia           1209.8240    185.9216\n",
       "Wisconsin               5567.4700   1523.0807"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd.groupby(['State']).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "id": "b4889266",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "keys = [state for state, df in dd.groupby(['State'])]\n",
    "\n",
    "plt.bar(keys,dd.groupby(['State']).sum()['Sales'], color=c, width=.5)\n",
    "plt.rcParams[\"figure.figsize\"] = (20, 10)\n",
    "# plt.figure(figsize=(10,10),dpi= 80)\n",
    "plt.ylabel('Sales in USD ($)')\n",
    "plt.title(\"Sales per State\", fontsize=16)\n",
    "# plt.xlabel('States')\n",
    "# plt.figure(figsize = (12,6))\n",
    "plt.xticks(keys, rotation=60)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1a4bc76",
   "metadata": {},
   "source": [
    "### 6. Top 10 Products By Sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "id": "761ae50c",
   "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>Sales</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Product Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Canon imageCLASS 2200 Advanced Copier</th>\n",
       "      <td>35699.898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Martin Yale Chadless Opener Electric Letter Opener</th>\n",
       "      <td>11825.902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GBC DocuBind TL300 Electric Binding System</th>\n",
       "      <td>10943.278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hewlett Packard LaserJet 3310 Copier</th>\n",
       "      <td>9239.846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samsung Galaxy Mega 6.3</th>\n",
       "      <td>9239.780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cubify CubeX 3D Printer Triple Head Print</th>\n",
       "      <td>7999.980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fellowes PB500 Electric Punch Plastic Comb Binding Machine with Manual Bind</th>\n",
       "      <td>7371.742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HON 5400 Series Task Chairs for Big and Tall</th>\n",
       "      <td>7220.094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GBC DocuBind P400 Electric Binding System</th>\n",
       "      <td>7077.148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lexmark MX611dhe Monochrome Laser Printer</th>\n",
       "      <td>5609.967</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                        Sales\n",
       "Product Name                                                 \n",
       "Canon imageCLASS 2200 Advanced Copier               35699.898\n",
       "Martin Yale Chadless Opener Electric Letter Opener  11825.902\n",
       "GBC DocuBind TL300 Electric Binding System          10943.278\n",
       "Hewlett Packard LaserJet 3310 Copier                 9239.846\n",
       "Samsung Galaxy Mega 6.3                              9239.780\n",
       "Cubify CubeX 3D Printer Triple Head Print            7999.980\n",
       "Fellowes PB500 Electric Punch Plastic Comb Bind...   7371.742\n",
       "HON 5400 Series Task Chairs for Big and Tall         7220.094\n",
       "GBC DocuBind P400 Electric Binding System            7077.148\n",
       "Lexmark MX611dhe Monochrome Laser Printer            5609.967"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grouping products by sales\n",
    "prod_sales = pd.DataFrame(df_original.groupby('Product Name').sum()['Sales'])\n",
    "\n",
    "# Sorting the dataframe in descending order\n",
    "prod_sales.sort_values(by=['Sales'], inplace=True, ascending=False)\n",
    "\n",
    "# Top 10 products by sales\n",
    "prod_sales[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c59c97f",
   "metadata": {},
   "source": [
    "### 7. Top Most Sold Products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "551dcf46",
   "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>Quantity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Product Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Staples</th>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Easy-staple paper</th>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Staples in misc. colors</th>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Staple envelope</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Storex Dura Pro Binders</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Memorex Mini Travel Drive 16 GB USB 2.0 Flash Drive</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eldon Wave Desk Accessories</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lesro Sheffield Collection Coffee Table, End Table, Center Table, Corner Table</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adjustable Depth Letter/Legal Cart</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Logitech Desktop MK120 Mouse and keyboard Combo</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Quantity\n",
       "Product Name                                                \n",
       "Staples                                                   68\n",
       "Easy-staple paper                                         58\n",
       "Staples in misc. colors                                   52\n",
       "Staple envelope                                           39\n",
       "Storex Dura Pro Binders                                   37\n",
       "Memorex Mini Travel Drive 16 GB USB 2.0 Flash D...        34\n",
       "Eldon Wave Desk Accessories                               34\n",
       "Lesro Sheffield Collection Coffee Table, End Ta...        30\n",
       "Adjustable Depth Letter/Legal Cart                        29\n",
       "Logitech Desktop MK120 Mouse and keyboard Combo           29"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grouping products by Quantity\n",
    "best_selling_prods = pd.DataFrame(df_original.groupby('Product Name').sum()['Quantity'])\n",
    "\n",
    "# Sorting the dataframe in descending order\n",
    "best_selling_prods.sort_values(by=['Quantity'], inplace=True, ascending=False)\n",
    "\n",
    "# Most selling products\n",
    "best_selling_prods[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55c69ecb",
   "metadata": {},
   "source": [
    "### 8. Profit Generated By Each Category along with its Sub-Category "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "77541b3f",
   "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></th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Technology</th>\n",
       "      <th>Copiers</th>\n",
       "      <td>25031.7902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories</th>\n",
       "      <td>15672.3570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phones</th>\n",
       "      <td>12849.3250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Machines</th>\n",
       "      <td>-2869.2156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">Office Supplies</th>\n",
       "      <th>Paper</th>\n",
       "      <td>12040.8434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Appliances</th>\n",
       "      <td>7865.2683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Binders</th>\n",
       "      <td>7669.7418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Storage</th>\n",
       "      <td>7402.8007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Art</th>\n",
       "      <td>2221.9631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Labels</th>\n",
       "      <td>1744.6093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Envelopes</th>\n",
       "      <td>1441.7590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fasteners</th>\n",
       "      <td>304.9489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Supplies</th>\n",
       "      <td>-955.3128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Furniture</th>\n",
       "      <th>Chairs</th>\n",
       "      <td>7643.5493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Furnishings</th>\n",
       "      <td>4099.1628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bookcases</th>\n",
       "      <td>-583.6261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tables</th>\n",
       "      <td>-8140.6947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Profit\n",
       "Category        Sub-Category            \n",
       "Technology      Copiers       25031.7902\n",
       "                Accessories   15672.3570\n",
       "                Phones        12849.3250\n",
       "                Machines      -2869.2156\n",
       "Office Supplies Paper         12040.8434\n",
       "                Appliances     7865.2683\n",
       "                Binders        7669.7418\n",
       "                Storage        7402.8007\n",
       "                Art            2221.9631\n",
       "                Labels         1744.6093\n",
       "                Envelopes      1441.7590\n",
       "                Fasteners       304.9489\n",
       "                Supplies       -955.3128\n",
       "Furniture       Chairs         7643.5493\n",
       "                Furnishings    4099.1628\n",
       "                Bookcases      -583.6261\n",
       "                Tables        -8140.6947"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grouping products by Category and Sub-Category\n",
    "cat_subcat = pd.DataFrame(df_original.groupby(['Category', 'Sub-Category']).sum()['Profit'])\n",
    "\n",
    "# Sorting the values\n",
    "cat_subcat.sort_values(['Category','Profit'], ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b1427f0",
   "metadata": {},
   "source": [
    "### 9. Top 50 Products Sold By Quantity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "3be41131",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'SAFCO Boltless Steel Shelving|Tenex Carpeted, Granite-Look or Clear Contemporary Contour Shape Chair Mats|Office Star - Contemporary Task Swivel Chair|Fluorescent Highlighters by Dixon|GBC Instant Report Kit|Pressboard Covers with Storage Hooks, 9 1/2 inches x 11 inches, Light Blue|Fellowes Superior 10 Outlet Split Surge Protector'"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['Grouped'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "a3f8dd9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Toshiba IPT2010-SD IP\\xa0Telephone', 'KI Adjustable-Height Table') 2\n",
      "('Eldon Expressions Punched Metal & Wood Desk Accessories, Black & Cherry', 'GBC DocuBind TL300 Electric Binding System') 2\n",
      "('SAFCO Optional Arm Kit for Workspace Cribbage Stacking Chair', 'Belkin Premiere Surge Master II 8-outlet surge protector') 2\n",
      "('OIC #2 Pencils, Medium Soft', 'Avery 505') 2\n",
      "('Staples', 'KI Adjustable-Height Table') 2\n",
      "('Wilson Jones Turn Tabs Binder Tool for Ring Binders', 'Adjustable Depth Letter/Legal Cart') 2\n",
      "('Maxell\\xa0iVDR EX 500GB Cartridge', 'Adjustable Depth Letter/Legal Cart') 2\n",
      "('Newell 344', 'Memorex Micro Travel Drive 16 GB') 2\n",
      "('Memorex Micro Travel Drive 16 GB', 'Wirebound Four 2-3/4 x 5 Forms per Page, 400 Sets per Book') 2\n",
      "('Memorex Micro Travel Drive 16 GB', 'Elite 5 inches Scissors') 2\n"
     ]
    }
   ],
   "source": [
    "count = Counter()\n",
    "\n",
    "for row in df2['Grouped']:\n",
    "    row_list = row.split('|')\n",
    "    count.update(Counter(combinations(row_list, 2)))\n",
    "\n",
    "for key,value in count.most_common(10):\n",
    "    print(key, value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "3c7a88b5",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>json</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8075</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10000343</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Pressboard Covers with Storage Hooks, 9 1/2 in...</td>\n",
       "      <td>13.748</td>\n",
       "      <td>14</td>\n",
       "      <td>0.80</td>\n",
       "      <td>-22.6842</td>\n",
       "      <td>{'Row ID': 8075, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1151</th>\n",
       "      <td>26/06/2020</td>\n",
       "      <td>5386</td>\n",
       "      <td>CA-2017-161410</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>CC-12220</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19143</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-PH-10000673</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Plantronics Voyager Pro HD - Bluetooth Headset</td>\n",
       "      <td>545.916</td>\n",
       "      <td>14</td>\n",
       "      <td>0.40</td>\n",
       "      <td>72.7888</td>\n",
       "      <td>{'Row ID': 5386, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608</th>\n",
       "      <td>27/08/2020</td>\n",
       "      <td>8936</td>\n",
       "      <td>CA-2017-130036</td>\n",
       "      <td>Same Day</td>\n",
       "      <td>BP-11185</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19120</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-AC-10001908</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Logitech Wireless Headset h800</td>\n",
       "      <td>1119.888</td>\n",
       "      <td>14</td>\n",
       "      <td>0.20</td>\n",
       "      <td>209.9790</td>\n",
       "      <td>{'Row ID': 8936, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2197</th>\n",
       "      <td>12/10/2020</td>\n",
       "      <td>1046</td>\n",
       "      <td>CA-2017-152702</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SN-20710</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Rockford</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>61107</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-CH-10002304</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Global Stack Chair without Arms, Black</td>\n",
       "      <td>254.604</td>\n",
       "      <td>14</td>\n",
       "      <td>0.30</td>\n",
       "      <td>-18.1860</td>\n",
       "      <td>{'Row ID': 1046, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2373</th>\n",
       "      <td>30/10/2020</td>\n",
       "      <td>1712</td>\n",
       "      <td>CA-2017-123491</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JK-15205</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94122</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-AP-10002684</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Appliances</td>\n",
       "      <td>Acco 7-Outlet Masterpiece Power Center, Wihtou...</td>\n",
       "      <td>1702.120</td>\n",
       "      <td>14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>510.6360</td>\n",
       "      <td>{'Row ID': 1712, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2529</th>\n",
       "      <td>10/11/2020</td>\n",
       "      <td>1364</td>\n",
       "      <td>US-2017-155425</td>\n",
       "      <td>First Class</td>\n",
       "      <td>AB-10600</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Tucson</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>85705</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10001036</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Cardinal EasyOpen D-Ring Binders</td>\n",
       "      <td>38.388</td>\n",
       "      <td>14</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-25.5920</td>\n",
       "      <td>{'Row ID': 1364, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2778</th>\n",
       "      <td>24/11/2020</td>\n",
       "      <td>9942</td>\n",
       "      <td>CA-2017-164028</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JL-15835</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94122</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-AC-10001772</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Memorex Mini Travel Drive 16 GB USB 2.0 Flash ...</td>\n",
       "      <td>223.580</td>\n",
       "      <td>14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>87.1962</td>\n",
       "      <td>{'Row ID': 9942, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3098</th>\n",
       "      <td>14/12/2020</td>\n",
       "      <td>2948</td>\n",
       "      <td>CA-2017-169859</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MP-18175</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>92024</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10000174</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Clip &amp; Carry Folder Binder Tool f...</td>\n",
       "      <td>64.960</td>\n",
       "      <td>14</td>\n",
       "      <td>0.20</td>\n",
       "      <td>22.7360</td>\n",
       "      <td>{'Row ID': 2948, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>31/03/2020</td>\n",
       "      <td>3243</td>\n",
       "      <td>CA-2017-114524</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>EG-13900</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>60623</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002799</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>SlimView Poly Binder, 3/8 inches</td>\n",
       "      <td>13.468</td>\n",
       "      <td>13</td>\n",
       "      <td>0.80</td>\n",
       "      <td>-22.8956</td>\n",
       "      <td>{'Row ID': 3243, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>01/04/2020</td>\n",
       "      <td>2618</td>\n",
       "      <td>CA-2017-147942</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MS-17365</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94110</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10001294</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Fellowes Binding Cases</td>\n",
       "      <td>121.680</td>\n",
       "      <td>13</td>\n",
       "      <td>0.20</td>\n",
       "      <td>38.0250</td>\n",
       "      <td>{'Row ID': 2618, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1574</th>\n",
       "      <td>23/08/2020</td>\n",
       "      <td>4298</td>\n",
       "      <td>CA-2017-129021</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>PO-18850</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Tallahassee</td>\n",
       "      <td>Florida</td>\n",
       "      <td>32303</td>\n",
       "      <td>South</td>\n",
       "      <td>TEC-PH-10001459</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Samsung Galaxy Mega 6.3</td>\n",
       "      <td>4367.896</td>\n",
       "      <td>13</td>\n",
       "      <td>0.20</td>\n",
       "      <td>327.5922</td>\n",
       "      <td>{'Row ID': 4298, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099</th>\n",
       "      <td>01/10/2020</td>\n",
       "      <td>2215</td>\n",
       "      <td>CA-2017-129378</td>\n",
       "      <td>First Class</td>\n",
       "      <td>NS-18505</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>California</td>\n",
       "      <td>95123</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10001922</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Storex Dura Pro Binders</td>\n",
       "      <td>61.776</td>\n",
       "      <td>13</td>\n",
       "      <td>0.20</td>\n",
       "      <td>20.8494</td>\n",
       "      <td>{'Row ID': 2215, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2244</th>\n",
       "      <td>16/10/2020</td>\n",
       "      <td>1597</td>\n",
       "      <td>CA-2017-132234</td>\n",
       "      <td>First Class</td>\n",
       "      <td>MY-17380</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10011</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10001290</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Executive Impressions Supervisor Wall Clock</td>\n",
       "      <td>547.300</td>\n",
       "      <td>13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>175.1360</td>\n",
       "      <td>{'Row ID': 1597, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2992</th>\n",
       "      <td>08/12/2020</td>\n",
       "      <td>413</td>\n",
       "      <td>CA-2017-117457</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>KH-16510</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94110</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-BO-10001972</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Bookcases</td>\n",
       "      <td>O'Sullivan 4-Shelf Bookcase in Odessa Pine</td>\n",
       "      <td>1336.829</td>\n",
       "      <td>13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>31.4548</td>\n",
       "      <td>{'Row ID': 413, 'Category': 'Furniture', 'Sub-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3151</th>\n",
       "      <td>18/12/2020</td>\n",
       "      <td>1251</td>\n",
       "      <td>CA-2017-115602</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DJ-13630</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-AP-10000891</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Appliances</td>\n",
       "      <td>Kensington 7 Outlet MasterPiece HOMEOFFICE Pow...</td>\n",
       "      <td>1704.560</td>\n",
       "      <td>13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>511.3680</td>\n",
       "      <td>{'Row ID': 1251, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3252</th>\n",
       "      <td>25/12/2020</td>\n",
       "      <td>2427</td>\n",
       "      <td>US-2017-147669</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SV-20935</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>45014</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-FA-10002975</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Staples</td>\n",
       "      <td>39.312</td>\n",
       "      <td>13</td>\n",
       "      <td>0.20</td>\n",
       "      <td>12.7764</td>\n",
       "      <td>{'Row ID': 2427, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857</th>\n",
       "      <td>19/05/2020</td>\n",
       "      <td>3625</td>\n",
       "      <td>CA-2017-113530</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>BC-11125</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94109</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-CH-10002647</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Situations Contoured Folding Chairs, 4/Set</td>\n",
       "      <td>681.408</td>\n",
       "      <td>12</td>\n",
       "      <td>0.20</td>\n",
       "      <td>42.5880</td>\n",
       "      <td>{'Row ID': 3625, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1143</th>\n",
       "      <td>26/06/2020</td>\n",
       "      <td>887</td>\n",
       "      <td>CA-2017-115364</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>OT-18730</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>92105</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-ST-10002486</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Shelf Savers Cubes and Bins</td>\n",
       "      <td>83.760</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.6752</td>\n",
       "      <td>{'Row ID': 887, 'Category': 'Office Supplies',...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2203</th>\n",
       "      <td>12/10/2020</td>\n",
       "      <td>5941</td>\n",
       "      <td>CA-2017-112431</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>RW-19690</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90049</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-AC-10001465</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>SanDisk Cruzer 64 GB USB Flash Drive</td>\n",
       "      <td>435.840</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>130.7520</td>\n",
       "      <td>{'Row ID': 5941, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2435</th>\n",
       "      <td>03/11/2020</td>\n",
       "      <td>7998</td>\n",
       "      <td>US-2017-105998</td>\n",
       "      <td>First Class</td>\n",
       "      <td>CR-12580</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>California</td>\n",
       "      <td>92037</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-TA-10001095</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Chromcraft Round Conference Tables</td>\n",
       "      <td>1673.184</td>\n",
       "      <td>12</td>\n",
       "      <td>0.20</td>\n",
       "      <td>20.9148</td>\n",
       "      <td>{'Row ID': 7998, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2760</th>\n",
       "      <td>24/11/2020</td>\n",
       "      <td>3591</td>\n",
       "      <td>CA-2017-146535</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>FM-14290</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Richmond</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>40475</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-ST-10001526</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Iceberg Mobile Mega Data/Printer Cart</td>\n",
       "      <td>1443.960</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>375.4296</td>\n",
       "      <td>{'Row ID': 3591, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2823</th>\n",
       "      <td>28/11/2020</td>\n",
       "      <td>950</td>\n",
       "      <td>US-2017-110576</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>RB-19795</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19120</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-TA-10004154</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Tables</td>\n",
       "      <td>Riverside Furniture Oval Coffee Table, Oval En...</td>\n",
       "      <td>2065.320</td>\n",
       "      <td>12</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-619.5960</td>\n",
       "      <td>{'Row ID': 950, 'Category': 'Furniture', 'Sub-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2878</th>\n",
       "      <td>01/12/2020</td>\n",
       "      <td>8871</td>\n",
       "      <td>CA-2017-101805</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SH-19975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10000023</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Eldon Wave Desk Accessories</td>\n",
       "      <td>70.680</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.0992</td>\n",
       "      <td>{'Row ID': 8871, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10001215</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2 inches Diameter Brentwood...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>199.2606</td>\n",
       "      <td>{'Row ID': 4010, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>07/01/2020</td>\n",
       "      <td>7372</td>\n",
       "      <td>US-2017-123862</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>JF-15190</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Long Beach</td>\n",
       "      <td>California</td>\n",
       "      <td>90805</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-ST-10000760</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>Eldon Fold 'N Roll Cart System</td>\n",
       "      <td>153.780</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>44.5962</td>\n",
       "      <td>{'Row ID': 7372, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>17/04/2020</td>\n",
       "      <td>6861</td>\n",
       "      <td>CA-2017-128965</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PS-18760</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90008</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-AC-10001383</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Logitech Wireless Touch Keyboard K400</td>\n",
       "      <td>274.890</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>46.7313</td>\n",
       "      <td>{'Row ID': 6861, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>06/05/2020</td>\n",
       "      <td>6635</td>\n",
       "      <td>CA-2017-144498</td>\n",
       "      <td>Same Day</td>\n",
       "      <td>MB-18085</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>North Carolina</td>\n",
       "      <td>28205</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-BI-10003982</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Century Plastic Molded Ring Binders</td>\n",
       "      <td>68.541</td>\n",
       "      <td>11</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-52.5481</td>\n",
       "      <td>{'Row ID': 6635, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>11/08/2020</td>\n",
       "      <td>6693</td>\n",
       "      <td>CA-2017-160899</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>DR-12940</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lake Charles</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>70601</td>\n",
       "      <td>South</td>\n",
       "      <td>OFF-BI-10000632</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Satellite Sectional Post Binders</td>\n",
       "      <td>477.510</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>219.6546</td>\n",
       "      <td>{'Row ID': 6693, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1818</th>\n",
       "      <td>11/09/2020</td>\n",
       "      <td>6234</td>\n",
       "      <td>US-2017-142188</td>\n",
       "      <td>Same Day</td>\n",
       "      <td>JF-15415</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98105</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-PA-10004101</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Xerox 1894</td>\n",
       "      <td>71.280</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>34.2144</td>\n",
       "      <td>{'Row ID': 6234, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1955</th>\n",
       "      <td>20/09/2020</td>\n",
       "      <td>6100</td>\n",
       "      <td>CA-2017-100111</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SV-20365</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10035</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-CH-10004086</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Chairs</td>\n",
       "      <td>Hon 4070 Series Pagoda Armless Upholstered Sta...</td>\n",
       "      <td>2888.127</td>\n",
       "      <td>11</td>\n",
       "      <td>0.10</td>\n",
       "      <td>609.7157</td>\n",
       "      <td>{'Row ID': 6100, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2102</th>\n",
       "      <td>01/10/2020</td>\n",
       "      <td>3296</td>\n",
       "      <td>CA-2017-113418</td>\n",
       "      <td>First Class</td>\n",
       "      <td>CM-12655</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10035</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-MA-10002428</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Machines</td>\n",
       "      <td>Fellowes Powershred HS-440 4-Sheet High Securi...</td>\n",
       "      <td>1704.890</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>767.2005</td>\n",
       "      <td>{'Row ID': 3296, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2106</th>\n",
       "      <td>02/10/2020</td>\n",
       "      <td>751</td>\n",
       "      <td>CA-2017-126074</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>RF-19735</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Trenton</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>48183</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-FU-10003577</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Nu-Dell Leatherette Frames</td>\n",
       "      <td>157.740</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>56.7864</td>\n",
       "      <td>{'Row ID': 751, 'Category': 'Furniture', 'Sub-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2128</th>\n",
       "      <td>02/10/2020</td>\n",
       "      <td>7207</td>\n",
       "      <td>CA-2017-137414</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>CM-12115</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94109</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-MA-10002930</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Machines</td>\n",
       "      <td>Ricoh - Ink Collector Unit for GX3000 Series P...</td>\n",
       "      <td>369.160</td>\n",
       "      <td>11</td>\n",
       "      <td>0.20</td>\n",
       "      <td>32.3015</td>\n",
       "      <td>{'Row ID': 7207, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2317</th>\n",
       "      <td>23/10/2020</td>\n",
       "      <td>2895</td>\n",
       "      <td>CA-2017-139913</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JC-16105</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Rochester</td>\n",
       "      <td>New York</td>\n",
       "      <td>14609</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10000771</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Eldon 200 Class Desk Accessories, Smoke</td>\n",
       "      <td>69.080</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>29.0136</td>\n",
       "      <td>{'Row ID': 2895, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2598</th>\n",
       "      <td>13/11/2020</td>\n",
       "      <td>4867</td>\n",
       "      <td>CA-2017-122490</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>TT-21070</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98103</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10001718</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>GBC DocuBind P50 Personal Binding Machine</td>\n",
       "      <td>563.024</td>\n",
       "      <td>11</td>\n",
       "      <td>0.20</td>\n",
       "      <td>190.0206</td>\n",
       "      <td>{'Row ID': 4867, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2827</th>\n",
       "      <td>28/11/2020</td>\n",
       "      <td>2661</td>\n",
       "      <td>CA-2017-123372</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DG-13300</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10035</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-PH-10002834</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Google Nexus 5</td>\n",
       "      <td>1979.890</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>494.9725</td>\n",
       "      <td>{'Row ID': 2661, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>24/04/2020</td>\n",
       "      <td>5978</td>\n",
       "      <td>CA-2017-116953</td>\n",
       "      <td>First Class</td>\n",
       "      <td>SV-20935</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Mesa</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>85204</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-PH-10004614</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>AT&amp;T 841000 Phone</td>\n",
       "      <td>552.000</td>\n",
       "      <td>10</td>\n",
       "      <td>0.20</td>\n",
       "      <td>34.5000</td>\n",
       "      <td>{'Row ID': 5978, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>06/05/2020</td>\n",
       "      <td>4669</td>\n",
       "      <td>US-2017-133200</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>DB-13555</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fort Worth</td>\n",
       "      <td>Texas</td>\n",
       "      <td>76106</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002827</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Avery Durable Poly Binders</td>\n",
       "      <td>11.060</td>\n",
       "      <td>10</td>\n",
       "      <td>0.80</td>\n",
       "      <td>-18.8020</td>\n",
       "      <td>{'Row ID': 4669, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873</th>\n",
       "      <td>20/05/2020</td>\n",
       "      <td>4367</td>\n",
       "      <td>CA-2017-111332</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>NC-18340</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fargo</td>\n",
       "      <td>North Dakota</td>\n",
       "      <td>58103</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-AR-10000657</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Binney &amp; Smith inkTank Desk Highlighter, Chise...</td>\n",
       "      <td>21.500</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.0950</td>\n",
       "      <td>{'Row ID': 4367, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>963</th>\n",
       "      <td>03/06/2020</td>\n",
       "      <td>5926</td>\n",
       "      <td>CA-2017-150420</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GD-14590</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Bellingham</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98226</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-AC-10004975</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Plantronics Audio 995 Wireless Stereo Headset</td>\n",
       "      <td>1099.500</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>362.8350</td>\n",
       "      <td>{'Row ID': 5926, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1209</th>\n",
       "      <td>03/07/2020</td>\n",
       "      <td>3663</td>\n",
       "      <td>US-2017-129777</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>FM-14290</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Quincy</td>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>2169</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-AC-10003590</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>TRENDnet 56K USB 2.0 Phone, Internet and Fax M...</td>\n",
       "      <td>258.900</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>93.2040</td>\n",
       "      <td>{'Row ID': 3663, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1446</th>\n",
       "      <td>07/08/2020</td>\n",
       "      <td>3575</td>\n",
       "      <td>CA-2017-117023</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JW-15955</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Long Beach</td>\n",
       "      <td>New York</td>\n",
       "      <td>11561</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-AR-10004062</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Staples in misc. colors</td>\n",
       "      <td>104.800</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>26.2000</td>\n",
       "      <td>{'Row ID': 3575, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1868</th>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>6518</td>\n",
       "      <td>US-2017-116652</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>RD-19480</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94122</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-AR-10001915</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Art</td>\n",
       "      <td>Peel-Off China Markers</td>\n",
       "      <td>99.300</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41.7060</td>\n",
       "      <td>{'Row ID': 6518, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>24/09/2020</td>\n",
       "      <td>8485</td>\n",
       "      <td>CA-2017-142391</td>\n",
       "      <td>Same Day</td>\n",
       "      <td>PB-19150</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98115</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10002759</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>12-1/2 Diameter Round Wall Clock</td>\n",
       "      <td>199.800</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>71.9280</td>\n",
       "      <td>{'Row ID': 8485, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2171</th>\n",
       "      <td>07/10/2020</td>\n",
       "      <td>2407</td>\n",
       "      <td>CA-2017-108574</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MG-18145</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90045</td>\n",
       "      <td>West</td>\n",
       "      <td>TEC-PH-10000702</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Square Credit Card Reader, 4 1/2 inches x 4 1/...</td>\n",
       "      <td>79.920</td>\n",
       "      <td>10</td>\n",
       "      <td>0.20</td>\n",
       "      <td>26.9730</td>\n",
       "      <td>{'Row ID': 2407, 'Category': 'Technology', 'Su...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2262</th>\n",
       "      <td>19/10/2020</td>\n",
       "      <td>3058</td>\n",
       "      <td>CA-2017-131492</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>HH-15010</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "      <td>94110</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-LA-10001641</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Labels</td>\n",
       "      <td>Avery 518</td>\n",
       "      <td>31.500</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>15.1200</td>\n",
       "      <td>{'Row ID': 3058, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2393</th>\n",
       "      <td>01/11/2020</td>\n",
       "      <td>8226</td>\n",
       "      <td>CA-2017-104136</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>SF-20065</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Everett</td>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>2149</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-PA-10004243</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Xerox 1939</td>\n",
       "      <td>189.700</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>91.0560</td>\n",
       "      <td>{'Row ID': 8226, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2416</th>\n",
       "      <td>02/11/2020</td>\n",
       "      <td>8020</td>\n",
       "      <td>CA-2017-167227</td>\n",
       "      <td>First Class</td>\n",
       "      <td>NP-18670</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Saint Louis</td>\n",
       "      <td>Missouri</td>\n",
       "      <td>63116</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-AP-10001962</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Appliances</td>\n",
       "      <td>Black &amp; Decker Filter for Double Action Dustbu...</td>\n",
       "      <td>83.900</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.9750</td>\n",
       "      <td>{'Row ID': 8020, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2477</th>\n",
       "      <td>05/11/2020</td>\n",
       "      <td>9500</td>\n",
       "      <td>CA-2017-118213</td>\n",
       "      <td>First Class</td>\n",
       "      <td>AB-10060</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Greenwood</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>46142</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-PA-10003673</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Paper</td>\n",
       "      <td>Strathmore Photo Mount Cards</td>\n",
       "      <td>67.800</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31.1880</td>\n",
       "      <td>{'Row ID': 9500, 'Category': 'Office Supplies'...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2516</th>\n",
       "      <td>08/11/2020</td>\n",
       "      <td>8432</td>\n",
       "      <td>CA-2017-155621</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>KN-16450</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21215</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10003535</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller Distant Time Traveler Alarm Clock</td>\n",
       "      <td>274.200</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>112.4220</td>\n",
       "      <td>{'Row ID': 8432, 'Category': 'Furniture', 'Sub...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "8     01/01/2020    8075  CA-2017-151750  Standard Class    JM-15250   \n",
       "1151  26/06/2020    5386  CA-2017-161410  Standard Class    CC-12220   \n",
       "1608  27/08/2020    8936  CA-2017-130036        Same Day    BP-11185   \n",
       "2197  12/10/2020    1046  CA-2017-152702  Standard Class    SN-20710   \n",
       "2373  30/10/2020    1712  CA-2017-123491  Standard Class    JK-15205   \n",
       "2529  10/11/2020    1364  US-2017-155425     First Class    AB-10600   \n",
       "2778  24/11/2020    9942  CA-2017-164028  Standard Class    JL-15835   \n",
       "3098  14/12/2020    2948  CA-2017-169859  Standard Class    MP-18175   \n",
       "494   31/03/2020    3243  CA-2017-114524    Second Class    EG-13900   \n",
       "503   01/04/2020    2618  CA-2017-147942  Standard Class    MS-17365   \n",
       "1574  23/08/2020    4298  CA-2017-129021    Second Class    PO-18850   \n",
       "2099  01/10/2020    2215  CA-2017-129378     First Class    NS-18505   \n",
       "2244  16/10/2020    1597  CA-2017-132234     First Class    MY-17380   \n",
       "2992  08/12/2020     413  CA-2017-117457  Standard Class    KH-16510   \n",
       "3151  18/12/2020    1251  CA-2017-115602  Standard Class    DJ-13630   \n",
       "3252  25/12/2020    2427  US-2017-147669  Standard Class    SV-20935   \n",
       "857   19/05/2020    3625  CA-2017-113530    Second Class    BC-11125   \n",
       "1143  26/06/2020     887  CA-2017-115364  Standard Class    OT-18730   \n",
       "2203  12/10/2020    5941  CA-2017-112431    Second Class    RW-19690   \n",
       "2435  03/11/2020    7998  US-2017-105998     First Class    CR-12580   \n",
       "2760  24/11/2020    3591  CA-2017-146535  Standard Class    FM-14290   \n",
       "2823  28/11/2020     950  US-2017-110576  Standard Class    RB-19795   \n",
       "2878  01/12/2020    8871  CA-2017-101805  Standard Class    SH-19975   \n",
       "1     01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "24    07/01/2020    7372  US-2017-123862    Second Class    JF-15190   \n",
       "610   17/04/2020    6861  CA-2017-128965  Standard Class    PS-18760   \n",
       "747   06/05/2020    6635  CA-2017-144498        Same Day    MB-18085   \n",
       "1469  11/08/2020    6693  CA-2017-160899    Second Class    DR-12940   \n",
       "1818  11/09/2020    6234  US-2017-142188        Same Day    JF-15415   \n",
       "1955  20/09/2020    6100  CA-2017-100111  Standard Class    SV-20365   \n",
       "2102  01/10/2020    3296  CA-2017-113418     First Class    CM-12655   \n",
       "2106  02/10/2020     751  CA-2017-126074  Standard Class    RF-19735   \n",
       "2128  02/10/2020    7207  CA-2017-137414  Standard Class    CM-12115   \n",
       "2317  23/10/2020    2895  CA-2017-139913  Standard Class    JC-16105   \n",
       "2598  13/11/2020    4867  CA-2017-122490  Standard Class    TT-21070   \n",
       "2827  28/11/2020    2661  CA-2017-123372  Standard Class    DG-13300   \n",
       "658   24/04/2020    5978  CA-2017-116953     First Class    SV-20935   \n",
       "744   06/05/2020    4669  US-2017-133200  Standard Class    DB-13555   \n",
       "873   20/05/2020    4367  CA-2017-111332    Second Class    NC-18340   \n",
       "963   03/06/2020    5926  CA-2017-150420  Standard Class    GD-14590   \n",
       "1209  03/07/2020    3663  US-2017-129777  Standard Class    FM-14290   \n",
       "1446  07/08/2020    3575  CA-2017-117023  Standard Class    JW-15955   \n",
       "1868  15/09/2020    6518  US-2017-116652  Standard Class    RD-19480   \n",
       "2025  24/09/2020    8485  CA-2017-142391        Same Day    PB-19150   \n",
       "2171  07/10/2020    2407  CA-2017-108574  Standard Class    MG-18145   \n",
       "2262  19/10/2020    3058  CA-2017-131492    Second Class    HH-15010   \n",
       "2393  01/11/2020    8226  CA-2017-104136    Second Class    SF-20065   \n",
       "2416  02/11/2020    8020  CA-2017-167227     First Class    NP-18670   \n",
       "2477  05/11/2020    9500  CA-2017-118213     First Class    AB-10060   \n",
       "2516  08/11/2020    8432  CA-2017-155621  Standard Class    KN-16450   \n",
       "\n",
       "          Segment        Country           City           State  Postal Code  \\\n",
       "8        Consumer  United States     Huntsville           Texas        77340   \n",
       "1151     Consumer  United States   Philadelphia    Pennsylvania        19143   \n",
       "1608    Corporate  United States   Philadelphia    Pennsylvania        19120   \n",
       "2197  Home Office  United States       Rockford        Illinois        61107   \n",
       "2373     Consumer  United States  San Francisco      California        94122   \n",
       "2529    Corporate  United States         Tucson         Arizona        85705   \n",
       "2778     Consumer  United States  San Francisco      California        94122   \n",
       "3098  Home Office  United States      San Diego      California        92024   \n",
       "494      Consumer  United States        Chicago        Illinois        60623   \n",
       "503      Consumer  United States  San Francisco      California        94110   \n",
       "1574     Consumer  United States    Tallahassee         Florida        32303   \n",
       "2099     Consumer  United States       San Jose      California        95123   \n",
       "2244    Corporate  United States  New York City        New York        10011   \n",
       "2992     Consumer  United States  San Francisco      California        94110   \n",
       "3151     Consumer  United States  New York City        New York        10009   \n",
       "3252     Consumer  United States      Fairfield            Ohio        45014   \n",
       "857   Home Office  United States  San Francisco      California        94109   \n",
       "1143     Consumer  United States      San Diego      California        92105   \n",
       "2203     Consumer  United States    Los Angeles      California        90049   \n",
       "2435  Home Office  United States      San Diego      California        92037   \n",
       "2760  Home Office  United States       Richmond        Kentucky        40475   \n",
       "2823  Home Office  United States   Philadelphia    Pennsylvania        19120   \n",
       "2878    Corporate  United States        Seattle      Washington        98105   \n",
       "1        Consumer  United States    Los Angeles      California        90036   \n",
       "24       Consumer  United States     Long Beach      California        90805   \n",
       "610      Consumer  United States    Los Angeles      California        90008   \n",
       "747      Consumer  United States      Charlotte  North Carolina        28205   \n",
       "1469  Home Office  United States   Lake Charles       Louisiana        70601   \n",
       "1818     Consumer  United States        Seattle      Washington        98105   \n",
       "1955     Consumer  United States  New York City        New York        10035   \n",
       "2102  Home Office  United States  New York City        New York        10035   \n",
       "2106     Consumer  United States        Trenton        Michigan        48183   \n",
       "2128     Consumer  United States  San Francisco      California        94109   \n",
       "2317    Corporate  United States      Rochester        New York        14609   \n",
       "2598     Consumer  United States        Seattle      Washington        98103   \n",
       "2827    Corporate  United States  New York City        New York        10035   \n",
       "658      Consumer  United States           Mesa         Arizona        85204   \n",
       "744     Corporate  United States     Fort Worth           Texas        76106   \n",
       "873      Consumer  United States          Fargo    North Dakota        58103   \n",
       "963     Corporate  United States     Bellingham      Washington        98226   \n",
       "1209  Home Office  United States         Quincy   Massachusetts         2169   \n",
       "1446     Consumer  United States     Long Beach        New York        11561   \n",
       "1868     Consumer  United States  San Francisco      California        94122   \n",
       "2025     Consumer  United States        Seattle      Washington        98115   \n",
       "2171     Consumer  United States    Los Angeles      California        90045   \n",
       "2262    Corporate  United States  San Francisco      California        94110   \n",
       "2393     Consumer  United States        Everett   Massachusetts         2149   \n",
       "2416     Consumer  United States    Saint Louis        Missouri        63116   \n",
       "2477  Home Office  United States      Greenwood         Indiana        46142   \n",
       "2516    Corporate  United States      Baltimore        Maryland        21215   \n",
       "\n",
       "       Region       Product ID         Category Sub-Category  \\\n",
       "8     Central  OFF-BI-10000343  Office Supplies      Binders   \n",
       "1151     East  TEC-PH-10000673       Technology       Phones   \n",
       "1608     East  TEC-AC-10001908       Technology  Accessories   \n",
       "2197  Central  FUR-CH-10002304        Furniture       Chairs   \n",
       "2373     West  OFF-AP-10002684  Office Supplies   Appliances   \n",
       "2529     West  OFF-BI-10001036  Office Supplies      Binders   \n",
       "2778     West  TEC-AC-10001772       Technology  Accessories   \n",
       "3098     West  OFF-BI-10000174  Office Supplies      Binders   \n",
       "494   Central  OFF-BI-10002799  Office Supplies      Binders   \n",
       "503      West  OFF-BI-10001294  Office Supplies      Binders   \n",
       "1574    South  TEC-PH-10001459       Technology       Phones   \n",
       "2099     West  OFF-BI-10001922  Office Supplies      Binders   \n",
       "2244     East  FUR-FU-10001290        Furniture  Furnishings   \n",
       "2992     West  FUR-BO-10001972        Furniture    Bookcases   \n",
       "3151     East  OFF-AP-10000891  Office Supplies   Appliances   \n",
       "3252     East  OFF-FA-10002975  Office Supplies    Fasteners   \n",
       "857      West  FUR-CH-10002647        Furniture       Chairs   \n",
       "1143     West  OFF-ST-10002486  Office Supplies      Storage   \n",
       "2203     West  TEC-AC-10001465       Technology  Accessories   \n",
       "2435     West  FUR-TA-10001095        Furniture       Tables   \n",
       "2760    South  OFF-ST-10001526  Office Supplies      Storage   \n",
       "2823     East  FUR-TA-10004154        Furniture       Tables   \n",
       "2878     West  FUR-FU-10000023        Furniture  Furnishings   \n",
       "1        West  FUR-FU-10001215        Furniture  Furnishings   \n",
       "24       West  OFF-ST-10000760  Office Supplies      Storage   \n",
       "610      West  TEC-AC-10001383       Technology  Accessories   \n",
       "747     South  OFF-BI-10003982  Office Supplies      Binders   \n",
       "1469    South  OFF-BI-10000632  Office Supplies      Binders   \n",
       "1818     West  OFF-PA-10004101  Office Supplies        Paper   \n",
       "1955     East  FUR-CH-10004086        Furniture       Chairs   \n",
       "2102     East  TEC-MA-10002428       Technology     Machines   \n",
       "2106  Central  FUR-FU-10003577        Furniture  Furnishings   \n",
       "2128     West  TEC-MA-10002930       Technology     Machines   \n",
       "2317     East  FUR-FU-10000771        Furniture  Furnishings   \n",
       "2598     West  OFF-BI-10001718  Office Supplies      Binders   \n",
       "2827     East  TEC-PH-10002834       Technology       Phones   \n",
       "658      West  TEC-PH-10004614       Technology       Phones   \n",
       "744   Central  OFF-BI-10002827  Office Supplies      Binders   \n",
       "873   Central  OFF-AR-10000657  Office Supplies          Art   \n",
       "963      West  TEC-AC-10004975       Technology  Accessories   \n",
       "1209     East  TEC-AC-10003590       Technology  Accessories   \n",
       "1446     East  OFF-AR-10004062  Office Supplies          Art   \n",
       "1868     West  OFF-AR-10001915  Office Supplies          Art   \n",
       "2025     West  FUR-FU-10002759        Furniture  Furnishings   \n",
       "2171     West  TEC-PH-10000702       Technology       Phones   \n",
       "2262     West  OFF-LA-10001641  Office Supplies       Labels   \n",
       "2393     East  OFF-PA-10004243  Office Supplies        Paper   \n",
       "2416  Central  OFF-AP-10001962  Office Supplies   Appliances   \n",
       "2477  Central  OFF-PA-10003673  Office Supplies        Paper   \n",
       "2516     East  FUR-FU-10003535        Furniture  Furnishings   \n",
       "\n",
       "                                           Product Name     Sales  Quantity  \\\n",
       "8     Pressboard Covers with Storage Hooks, 9 1/2 in...    13.748        14   \n",
       "1151     Plantronics Voyager Pro HD - Bluetooth Headset   545.916        14   \n",
       "1608                     Logitech Wireless Headset h800  1119.888        14   \n",
       "2197             Global Stack Chair without Arms, Black   254.604        14   \n",
       "2373  Acco 7-Outlet Masterpiece Power Center, Wihtou...  1702.120        14   \n",
       "2529                   Cardinal EasyOpen D-Ring Binders    38.388        14   \n",
       "2778  Memorex Mini Travel Drive 16 GB USB 2.0 Flash ...   223.580        14   \n",
       "3098  Wilson Jones Clip & Carry Folder Binder Tool f...    64.960        14   \n",
       "494                    SlimView Poly Binder, 3/8 inches    13.468        13   \n",
       "503                              Fellowes Binding Cases   121.680        13   \n",
       "1574                            Samsung Galaxy Mega 6.3  4367.896        13   \n",
       "2099                            Storex Dura Pro Binders    61.776        13   \n",
       "2244        Executive Impressions Supervisor Wall Clock   547.300        13   \n",
       "2992         O'Sullivan 4-Shelf Bookcase in Odessa Pine  1336.829        13   \n",
       "3151  Kensington 7 Outlet MasterPiece HOMEOFFICE Pow...  1704.560        13   \n",
       "3252                                            Staples    39.312        13   \n",
       "857          Situations Contoured Folding Chairs, 4/Set   681.408        12   \n",
       "1143                  Eldon Shelf Savers Cubes and Bins    83.760        12   \n",
       "2203               SanDisk Cruzer 64 GB USB Flash Drive   435.840        12   \n",
       "2435                 Chromcraft Round Conference Tables  1673.184        12   \n",
       "2760             Iceberg Mobile Mega Data/Printer Cart   1443.960        12   \n",
       "2823  Riverside Furniture Oval Coffee Table, Oval En...  2065.320        12   \n",
       "2878                        Eldon Wave Desk Accessories    70.680        12   \n",
       "1     Howard Miller 11-1/2 inches Diameter Brentwood...   474.430        11   \n",
       "24                       Eldon Fold 'N Roll Cart System   153.780        11   \n",
       "610               Logitech Wireless Touch Keyboard K400   274.890        11   \n",
       "747    Wilson Jones Century Plastic Molded Ring Binders    68.541        11   \n",
       "1469                   Satellite Sectional Post Binders   477.510        11   \n",
       "1818                                         Xerox 1894    71.280        11   \n",
       "1955  Hon 4070 Series Pagoda Armless Upholstered Sta...  2888.127        11   \n",
       "2102  Fellowes Powershred HS-440 4-Sheet High Securi...  1704.890        11   \n",
       "2106                         Nu-Dell Leatherette Frames   157.740        11   \n",
       "2128  Ricoh - Ink Collector Unit for GX3000 Series P...   369.160        11   \n",
       "2317            Eldon 200 Class Desk Accessories, Smoke    69.080        11   \n",
       "2598          GBC DocuBind P50 Personal Binding Machine   563.024        11   \n",
       "2827                                     Google Nexus 5  1979.890        11   \n",
       "658                                   AT&T 841000 Phone   552.000        10   \n",
       "744                          Avery Durable Poly Binders    11.060        10   \n",
       "873   Binney & Smith inkTank Desk Highlighter, Chise...    21.500        10   \n",
       "963       Plantronics Audio 995 Wireless Stereo Headset  1099.500        10   \n",
       "1209  TRENDnet 56K USB 2.0 Phone, Internet and Fax M...   258.900        10   \n",
       "1446                            Staples in misc. colors   104.800        10   \n",
       "1868                             Peel-Off China Markers    99.300        10   \n",
       "2025                   12-1/2 Diameter Round Wall Clock   199.800        10   \n",
       "2171  Square Credit Card Reader, 4 1/2 inches x 4 1/...    79.920        10   \n",
       "2262                                          Avery 518    31.500        10   \n",
       "2393                                         Xerox 1939   189.700        10   \n",
       "2416  Black & Decker Filter for Double Action Dustbu...    83.900        10   \n",
       "2477                       Strathmore Photo Mount Cards    67.800        10   \n",
       "2516    Howard Miller Distant Time Traveler Alarm Clock   274.200        10   \n",
       "\n",
       "      Discount    Profit                                               json  \n",
       "8         0.80  -22.6842  {'Row ID': 8075, 'Category': 'Office Supplies'...  \n",
       "1151      0.40   72.7888  {'Row ID': 5386, 'Category': 'Technology', 'Su...  \n",
       "1608      0.20  209.9790  {'Row ID': 8936, 'Category': 'Technology', 'Su...  \n",
       "2197      0.30  -18.1860  {'Row ID': 1046, 'Category': 'Furniture', 'Sub...  \n",
       "2373      0.00  510.6360  {'Row ID': 1712, 'Category': 'Office Supplies'...  \n",
       "2529      0.70  -25.5920  {'Row ID': 1364, 'Category': 'Office Supplies'...  \n",
       "2778      0.00   87.1962  {'Row ID': 9942, 'Category': 'Technology', 'Su...  \n",
       "3098      0.20   22.7360  {'Row ID': 2948, 'Category': 'Office Supplies'...  \n",
       "494       0.80  -22.8956  {'Row ID': 3243, 'Category': 'Office Supplies'...  \n",
       "503       0.20   38.0250  {'Row ID': 2618, 'Category': 'Office Supplies'...  \n",
       "1574      0.20  327.5922  {'Row ID': 4298, 'Category': 'Technology', 'Su...  \n",
       "2099      0.20   20.8494  {'Row ID': 2215, 'Category': 'Office Supplies'...  \n",
       "2244      0.00  175.1360  {'Row ID': 1597, 'Category': 'Furniture', 'Sub...  \n",
       "2992      0.15   31.4548  {'Row ID': 413, 'Category': 'Furniture', 'Sub-...  \n",
       "3151      0.00  511.3680  {'Row ID': 1251, 'Category': 'Office Supplies'...  \n",
       "3252      0.20   12.7764  {'Row ID': 2427, 'Category': 'Office Supplies'...  \n",
       "857       0.20   42.5880  {'Row ID': 3625, 'Category': 'Furniture', 'Sub...  \n",
       "1143      0.00    1.6752  {'Row ID': 887, 'Category': 'Office Supplies',...  \n",
       "2203      0.00  130.7520  {'Row ID': 5941, 'Category': 'Technology', 'Su...  \n",
       "2435      0.20   20.9148  {'Row ID': 7998, 'Category': 'Furniture', 'Sub...  \n",
       "2760      0.00  375.4296  {'Row ID': 3591, 'Category': 'Office Supplies'...  \n",
       "2823      0.40 -619.5960  {'Row ID': 950, 'Category': 'Furniture', 'Sub-...  \n",
       "2878      0.00   31.0992  {'Row ID': 8871, 'Category': 'Furniture', 'Sub...  \n",
       "1         0.00  199.2606  {'Row ID': 4010, 'Category': 'Furniture', 'Sub...  \n",
       "24        0.00   44.5962  {'Row ID': 7372, 'Category': 'Office Supplies'...  \n",
       "610       0.00   46.7313  {'Row ID': 6861, 'Category': 'Technology', 'Su...  \n",
       "747       0.70  -52.5481  {'Row ID': 6635, 'Category': 'Office Supplies'...  \n",
       "1469      0.00  219.6546  {'Row ID': 6693, 'Category': 'Office Supplies'...  \n",
       "1818      0.00   34.2144  {'Row ID': 6234, 'Category': 'Office Supplies'...  \n",
       "1955      0.10  609.7157  {'Row ID': 6100, 'Category': 'Furniture', 'Sub...  \n",
       "2102      0.00  767.2005  {'Row ID': 3296, 'Category': 'Technology', 'Su...  \n",
       "2106      0.00   56.7864  {'Row ID': 751, 'Category': 'Furniture', 'Sub-...  \n",
       "2128      0.20   32.3015  {'Row ID': 7207, 'Category': 'Technology', 'Su...  \n",
       "2317      0.00   29.0136  {'Row ID': 2895, 'Category': 'Furniture', 'Sub...  \n",
       "2598      0.20  190.0206  {'Row ID': 4867, 'Category': 'Office Supplies'...  \n",
       "2827      0.00  494.9725  {'Row ID': 2661, 'Category': 'Technology', 'Su...  \n",
       "658       0.20   34.5000  {'Row ID': 5978, 'Category': 'Technology', 'Su...  \n",
       "744       0.80  -18.8020  {'Row ID': 4669, 'Category': 'Office Supplies'...  \n",
       "873       0.00    7.0950  {'Row ID': 4367, 'Category': 'Office Supplies'...  \n",
       "963       0.00  362.8350  {'Row ID': 5926, 'Category': 'Technology', 'Su...  \n",
       "1209      0.00   93.2040  {'Row ID': 3663, 'Category': 'Technology', 'Su...  \n",
       "1446      0.00   26.2000  {'Row ID': 3575, 'Category': 'Office Supplies'...  \n",
       "1868      0.00   41.7060  {'Row ID': 6518, 'Category': 'Office Supplies'...  \n",
       "2025      0.00   71.9280  {'Row ID': 8485, 'Category': 'Furniture', 'Sub...  \n",
       "2171      0.20   26.9730  {'Row ID': 2407, 'Category': 'Technology', 'Su...  \n",
       "2262      0.00   15.1200  {'Row ID': 3058, 'Category': 'Office Supplies'...  \n",
       "2393      0.00   91.0560  {'Row ID': 8226, 'Category': 'Office Supplies'...  \n",
       "2416      0.00   20.9750  {'Row ID': 8020, 'Category': 'Office Supplies'...  \n",
       "2477      0.00   31.1880  {'Row ID': 9500, 'Category': 'Office Supplies'...  \n",
       "2516      0.00  112.4220  {'Row ID': 8432, 'Category': 'Furniture', 'Sub...  "
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dup=df_original.nlargest(50,['Quantity'])\n",
    "df_dup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "55b51639",
   "metadata": {},
   "outputs": [
    {
     "ename": "ConversionError",
     "evalue": "Failed to convert value(s) to axis units: ['12-1/2 Diameter Round Wall Clock', 'AT&T 841000 Phone', 'Acco 7-Outlet Masterpiece Power Center, Wihtout Fax/Phone Line Protection', 'Avery 518', 'Avery Durable Poly Binders', 'Binney & Smith inkTank Desk Highlighter, Chisel Tip, Yellow, 12/Box', 'Black & Decker Filter for Double Action Dustbuster Cordless Vac BLDV7210', 'Cardinal EasyOpen D-Ring Binders', 'Chromcraft Round Conference Tables', 'Eldon 200 Class Desk Accessories, Smoke', \"Eldon Fold 'N Roll Cart System\", 'Eldon Shelf Savers Cubes and Bins', 'Eldon Wave Desk Accessories', 'Executive Impressions Supervisor Wall Clock', 'Fellowes Binding Cases', 'Fellowes Powershred HS-440 4-Sheet High Security Shredder', 'GBC DocuBind P50 Personal Binding Machine', 'Global Stack Chair without Arms, Black', 'Google Nexus 5', 'Hon 4070 Series Pagoda Armless Upholstered Stacking Chairs', 'Howard Miller 11-1/2 inches Diameter Brentwood Wall Clock', 'Howard Miller Distant Time Traveler Alarm Clock', 'Iceberg Mobile Mega Data/Printer Cart ', 'Kensington 7 Outlet MasterPiece HOMEOFFICE Power Control Center', 'Logitech Wireless Headset h800', 'Logitech Wireless Touch Keyboard K400', 'Memorex Mini Travel Drive 16 GB USB 2.0 Flash Drive', 'Nu-Dell Leatherette Frames', \"O'Sullivan 4-Shelf Bookcase in Odessa Pine\", 'Peel-Off China Markers', 'Plantronics Audio 995 Wireless Stereo Headset', 'Plantronics Voyager Pro HD - Bluetooth Headset', 'Pressboard Covers with Storage Hooks, 9 1/2 inches x 11 inches, Light Blue', 'Ricoh - Ink Collector Unit for GX3000 Series Printers', 'Riverside Furniture Oval Coffee Table, Oval End Table, End Table with Drawer', 'Samsung Galaxy Mega 6.3', 'SanDisk Cruzer 64 GB USB Flash Drive', 'Satellite Sectional Post Binders', 'Situations Contoured Folding Chairs, 4/Set', 'SlimView Poly Binder, 3/8 inches', 'Square Credit Card Reader, 4 1/2 inches x 4 1/2 inches x 1 inches, White', 'Staples', 'Staples in misc. colors', 'Storex Dura Pro Binders', 'Strathmore Photo Mount Cards', 'TRENDnet 56K USB 2.0 Phone, Internet and Fax Modem', 'Wilson Jones Century Plastic Molded Ring Binders', 'Wilson Jones Clip & Carry Folder Binder Tool for Ring Binders, Clear', 'Xerox 1894', 'Xerox 1939']",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\axis.py\u001b[0m in \u001b[0;36mconvert_units\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m   1522\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1523\u001b[1;33m             \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconverter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1524\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\category.py\u001b[0m in \u001b[0;36mconvert\u001b[1;34m(value, unit, axis)\u001b[0m\n\u001b[0;32m     48\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0munit\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 49\u001b[1;33m             raise ValueError(\n\u001b[0m\u001b[0;32m     50\u001b[0m                 \u001b[1;34m'Missing category information for StrCategoryConverter; '\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Missing category information for StrCategoryConverter; this might be caused by unintendedly mixing categorical and numeric data",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mConversionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-139-c90fca9fe6d7>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Sales in USD ($)'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'States'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mxticks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrotation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m60\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mxticks\u001b[1;34m(ticks, labels, **kwargs)\u001b[0m\n\u001b[0;32m   1652\u001b[0m                             \"without setting 'ticks'\")\n\u001b[0;32m   1653\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1654\u001b[1;33m         \u001b[0mlocs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_xticks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mticks\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1655\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1656\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m     61\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     62\u001b[0m         \u001b[1;32mdef\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 63\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mget_method\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     64\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     65\u001b[0m         \u001b[0mwrapper\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__module__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mowner\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__module__\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    449\u001b[0m                 \u001b[1;34m\"parameter will become keyword-only %(removal)s.\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    450\u001b[0m                 name=name, obj_type=f\"parameter of {func.__name__}()\")\n\u001b[1;32m--> 451\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    452\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    453\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\axis.py\u001b[0m in \u001b[0;36mset_ticks\u001b[1;34m(self, ticks, minor)\u001b[0m\n\u001b[0;32m   1809\u001b[0m         \"\"\"\n\u001b[0;32m   1810\u001b[0m         \u001b[1;31m# XXX if the user changes units, the information will be lost here\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1811\u001b[1;33m         \u001b[0mticks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert_units\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mticks\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1812\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mticks\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1813\u001b[0m             \u001b[0mxleft\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mxright\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_view_interval\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mF:\\lareb\\a\\lib\\site-packages\\matplotlib\\axis.py\u001b[0m in \u001b[0;36mconvert_units\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m   1523\u001b[0m             \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconverter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1524\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1525\u001b[1;33m             raise munits.ConversionError('Failed to convert value(s) to axis '\n\u001b[0m\u001b[0;32m   1526\u001b[0m                                          f'units: {x!r}') from e\n\u001b[0;32m   1527\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mConversionError\u001b[0m: Failed to convert value(s) to axis units: ['12-1/2 Diameter Round Wall Clock', 'AT&T 841000 Phone', 'Acco 7-Outlet Masterpiece Power Center, Wihtout Fax/Phone Line Protection', 'Avery 518', 'Avery Durable Poly Binders', 'Binney & Smith inkTank Desk Highlighter, Chisel Tip, Yellow, 12/Box', 'Black & Decker Filter for Double Action Dustbuster Cordless Vac BLDV7210', 'Cardinal EasyOpen D-Ring Binders', 'Chromcraft Round Conference Tables', 'Eldon 200 Class Desk Accessories, Smoke', \"Eldon Fold 'N Roll Cart System\", 'Eldon Shelf Savers Cubes and Bins', 'Eldon Wave Desk Accessories', 'Executive Impressions Supervisor Wall Clock', 'Fellowes Binding Cases', 'Fellowes Powershred HS-440 4-Sheet High Security Shredder', 'GBC DocuBind P50 Personal Binding Machine', 'Global Stack Chair without Arms, Black', 'Google Nexus 5', 'Hon 4070 Series Pagoda Armless Upholstered Stacking Chairs', 'Howard Miller 11-1/2 inches Diameter Brentwood Wall Clock', 'Howard Miller Distant Time Traveler Alarm Clock', 'Iceberg Mobile Mega Data/Printer Cart ', 'Kensington 7 Outlet MasterPiece HOMEOFFICE Power Control Center', 'Logitech Wireless Headset h800', 'Logitech Wireless Touch Keyboard K400', 'Memorex Mini Travel Drive 16 GB USB 2.0 Flash Drive', 'Nu-Dell Leatherette Frames', \"O'Sullivan 4-Shelf Bookcase in Odessa Pine\", 'Peel-Off China Markers', 'Plantronics Audio 995 Wireless Stereo Headset', 'Plantronics Voyager Pro HD - Bluetooth Headset', 'Pressboard Covers with Storage Hooks, 9 1/2 inches x 11 inches, Light Blue', 'Ricoh - Ink Collector Unit for GX3000 Series Printers', 'Riverside Furniture Oval Coffee Table, Oval End Table, End Table with Drawer', 'Samsung Galaxy Mega 6.3', 'SanDisk Cruzer 64 GB USB Flash Drive', 'Satellite Sectional Post Binders', 'Situations Contoured Folding Chairs, 4/Set', 'SlimView Poly Binder, 3/8 inches', 'Square Credit Card Reader, 4 1/2 inches x 4 1/2 inches x 1 inches, White', 'Staples', 'Staples in misc. colors', 'Storex Dura Pro Binders', 'Strathmore Photo Mount Cards', 'TRENDnet 56K USB 2.0 Phone, Internet and Fax Modem', 'Wilson Jones Century Plastic Molded Ring Binders', 'Wilson Jones Clip & Carry Folder Binder Tool for Ring Binders, Clear', 'Xerox 1894', 'Xerox 1939']"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "product_group = df_dup.groupby(['Product Name'])\n",
    "quantity_ordered = product_group.sum()['Quantity']\n",
    "# product_group\n",
    "keys = [pair for pair, df in product_group]\n",
    "keys\n",
    "plt.bar(keys, quantity_ordered)\n",
    "plt.figure(figsize=(16,10),dpi= 80)\n",
    "plt.ylabel('Sales in USD ($)')\n",
    "plt.xlabel('States')\n",
    "plt.xticks(keys, rotation=60)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# keys = [state for state, df in dd.groupby(['State'])]\n",
    "\n",
    "# plt.bar(keys,dd.groupby(['State']).sum()['Sales'], color=c, width=.5)\n",
    "# # plt.rcParams[\"figure.figsize\"] = (16, 10)\n",
    "# # plt.figure(figsize=(16,10),dpi= 80)\n",
    "# plt.ylabel('Sales in USD ($)')\n",
    "# plt.title(\"Sales per State\", fontsize=16)\n",
    "# plt.xlabel('States')\n",
    "# plt.xticks(keys, rotation=60)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "9e3c8658",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Product ID</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>849</td>\n",
       "      <td>CA-2017-107503</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GA-14725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lorain</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>44052</td>\n",
       "      <td>East</td>\n",
       "      <td>FUR-FU-10003878</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Linden 10 inches Round Wall Clock, Black</td>\n",
       "      <td>48.896</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>8.5568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>West</td>\n",
       "      <td>FUR-FU-10001215</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2 inches Diameter Brentwood...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199.2606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>6683</td>\n",
       "      <td>CA-2017-154466</td>\n",
       "      <td>First Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53132</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-BI-10002012</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Easy Flow II Sheet Lifters</td>\n",
       "      <td>3.600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8070</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>OFF-ST-10002743</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>SAFCO Boltless Steel Shelving</td>\n",
       "      <td>454.560</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-107.9580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8071</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>Central</td>\n",
       "      <td>FUR-FU-10002116</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Carpeted, Granite-Look or Clear Contempo...</td>\n",
       "      <td>141.420</td>\n",
       "      <td>5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-187.3815</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3307</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>908</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>TEC-PH-10004774</td>\n",
       "      <td>Technology</td>\n",
       "      <td>Phones</td>\n",
       "      <td>Gear Head AU3700S Headset</td>\n",
       "      <td>90.930</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.7279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3308</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>909</td>\n",
       "      <td>CA-2017-143259</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>PO-18865</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "      <td>OFF-BI-10003684</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Legal Size Ring Binders</td>\n",
       "      <td>52.776</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>19.7910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3309</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1297</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10002103</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl</td>\n",
       "      <td>13.904</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.5188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3310</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>1298</td>\n",
       "      <td>CA-2017-115427</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>EB-13975</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Fairfield</td>\n",
       "      <td>California</td>\n",
       "      <td>94533</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-BI-10004632</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>GBC Binding covers</td>\n",
       "      <td>20.720</td>\n",
       "      <td>2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>6.4750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3311</th>\n",
       "      <td>30/12/2020</td>\n",
       "      <td>5092</td>\n",
       "      <td>CA-2017-156720</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15580</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Loveland</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>80538</td>\n",
       "      <td>West</td>\n",
       "      <td>OFF-FA-10003472</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Fasteners</td>\n",
       "      <td>Bagged Rubber Bands</td>\n",
       "      <td>3.024</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-0.6048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3312 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "0     01/01/2020     849  CA-2017-107503  Standard Class    GA-14725   \n",
       "1     01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "2     01/01/2020    6683  CA-2017-154466     First Class    DP-13390   \n",
       "3     01/01/2020    8070  CA-2017-151750  Standard Class    JM-15250   \n",
       "4     01/01/2020    8071  CA-2017-151750  Standard Class    JM-15250   \n",
       "...          ...     ...             ...             ...         ...   \n",
       "3307  30/12/2020     908  CA-2017-143259  Standard Class    PO-18865   \n",
       "3308  30/12/2020     909  CA-2017-143259  Standard Class    PO-18865   \n",
       "3309  30/12/2020    1297  CA-2017-115427  Standard Class    EB-13975   \n",
       "3310  30/12/2020    1298  CA-2017-115427  Standard Class    EB-13975   \n",
       "3311  30/12/2020    5092  CA-2017-156720  Standard Class    JM-15580   \n",
       "\n",
       "          Segment        Country           City       State  Postal Code  \\\n",
       "0        Consumer  United States         Lorain        Ohio        44052   \n",
       "1        Consumer  United States    Los Angeles  California        90036   \n",
       "2     Home Office  United States       Franklin   Wisconsin        53132   \n",
       "3        Consumer  United States     Huntsville       Texas        77340   \n",
       "4        Consumer  United States     Huntsville       Texas        77340   \n",
       "...           ...            ...            ...         ...          ...   \n",
       "3307     Consumer  United States  New York City    New York        10009   \n",
       "3308     Consumer  United States  New York City    New York        10009   \n",
       "3309    Corporate  United States      Fairfield  California        94533   \n",
       "3310    Corporate  United States      Fairfield  California        94533   \n",
       "3311     Consumer  United States       Loveland    Colorado        80538   \n",
       "\n",
       "       Region       Product ID         Category Sub-Category  \\\n",
       "0        East  FUR-FU-10003878        Furniture  Furnishings   \n",
       "1        West  FUR-FU-10001215        Furniture  Furnishings   \n",
       "2     Central  OFF-BI-10002012  Office Supplies      Binders   \n",
       "3     Central  OFF-ST-10002743  Office Supplies      Storage   \n",
       "4     Central  FUR-FU-10002116        Furniture  Furnishings   \n",
       "...       ...              ...              ...          ...   \n",
       "3307     East  TEC-PH-10004774       Technology       Phones   \n",
       "3308     East  OFF-BI-10003684  Office Supplies      Binders   \n",
       "3309     West  OFF-BI-10002103  Office Supplies      Binders   \n",
       "3310     West  OFF-BI-10004632  Office Supplies      Binders   \n",
       "3311     West  OFF-FA-10003472  Office Supplies    Fasteners   \n",
       "\n",
       "                                           Product Name    Sales  Quantity  \\\n",
       "0              Linden 10 inches Round Wall Clock, Black   48.896         4   \n",
       "1     Howard Miller 11-1/2 inches Diameter Brentwood...  474.430        11   \n",
       "2               Wilson Jones Easy Flow II Sheet Lifters    3.600         2   \n",
       "3                         SAFCO Boltless Steel Shelving  454.560         5   \n",
       "4     Tenex Carpeted, Granite-Look or Clear Contempo...  141.420         5   \n",
       "...                                                 ...      ...       ...   \n",
       "3307                          Gear Head AU3700S Headset   90.930         7   \n",
       "3308               Wilson Jones Legal Size Ring Binders   52.776         3   \n",
       "3309    Cardinal Slant-D Ring Binder, Heavy Gauge Vinyl   13.904         2   \n",
       "3310                                 GBC Binding covers   20.720         2   \n",
       "3311                                Bagged Rubber Bands    3.024         3   \n",
       "\n",
       "      Discount    Profit  \n",
       "0          0.2    8.5568  \n",
       "1          0.0  199.2606  \n",
       "2          0.0    1.7280  \n",
       "3          0.2 -107.9580  \n",
       "4          0.6 -187.3815  \n",
       "...        ...       ...  \n",
       "3307       0.0    2.7279  \n",
       "3308       0.2   19.7910  \n",
       "3309       0.2    4.5188  \n",
       "3310       0.2    6.4750  \n",
       "3311       0.2   -0.6048  \n",
       "\n",
       "[3312 rows x 19 columns]"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#end\n",
    "# df_original\n",
    "# df_original=df_original.drop('json' ,axis=1)\n",
    "df_original"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afe49a7d",
   "metadata": {},
   "source": [
    "### 11. Purchase According to Category "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "2b3a8ffe",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\lareb\\a\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Category', ylabel='count'>"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot('Category', data = df_original)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75c9a694",
   "metadata": {},
   "source": [
    "##### Dummies for Category to categorize products and there Sales Accordingly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "6806524a",
   "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>Furniture</th>\n",
       "      <th>Office Supplies</th>\n",
       "      <th>Technology</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Furniture  Office Supplies  Technology\n",
       "0          1                0           0\n",
       "1          1                0           0\n",
       "2          0                1           0\n",
       "3          0                1           0\n",
       "4          1                0           0"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g_dummies = pd.get_dummies(df_original['Category'])\n",
    "g_dummies.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "3d7ac11c",
   "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>Order Date</th>\n",
       "      <th>Row ID</th>\n",
       "      <th>Order ID</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>...</th>\n",
       "      <th>Category</th>\n",
       "      <th>Sub-Category</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Discount</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Furniture</th>\n",
       "      <th>Office Supplies</th>\n",
       "      <th>Technology</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>849</td>\n",
       "      <td>CA-2017-107503</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>GA-14725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Lorain</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>44052</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Linden 10 inches Round Wall Clock, Black</td>\n",
       "      <td>48.896</td>\n",
       "      <td>4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>8.5568</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>4010</td>\n",
       "      <td>CA-2017-144463</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SC-20725</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90036</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Howard Miller 11-1/2 inches Diameter Brentwood...</td>\n",
       "      <td>474.430</td>\n",
       "      <td>11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199.2606</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>6683</td>\n",
       "      <td>CA-2017-154466</td>\n",
       "      <td>First Class</td>\n",
       "      <td>DP-13390</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53132</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Binders</td>\n",
       "      <td>Wilson Jones Easy Flow II Sheet Lifters</td>\n",
       "      <td>3.600</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.7280</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8070</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>...</td>\n",
       "      <td>Office Supplies</td>\n",
       "      <td>Storage</td>\n",
       "      <td>SAFCO Boltless Steel Shelving</td>\n",
       "      <td>454.560</td>\n",
       "      <td>5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>-107.9580</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>01/01/2020</td>\n",
       "      <td>8071</td>\n",
       "      <td>CA-2017-151750</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JM-15250</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Huntsville</td>\n",
       "      <td>Texas</td>\n",
       "      <td>77340</td>\n",
       "      <td>...</td>\n",
       "      <td>Furniture</td>\n",
       "      <td>Furnishings</td>\n",
       "      <td>Tenex Carpeted, Granite-Look or Clear Contempo...</td>\n",
       "      <td>141.420</td>\n",
       "      <td>5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-187.3815</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Order Date  Row ID        Order ID       Ship Mode Customer ID  \\\n",
       "0  01/01/2020     849  CA-2017-107503  Standard Class    GA-14725   \n",
       "1  01/01/2020    4010  CA-2017-144463  Standard Class    SC-20725   \n",
       "2  01/01/2020    6683  CA-2017-154466     First Class    DP-13390   \n",
       "3  01/01/2020    8070  CA-2017-151750  Standard Class    JM-15250   \n",
       "4  01/01/2020    8071  CA-2017-151750  Standard Class    JM-15250   \n",
       "\n",
       "       Segment        Country         City       State  Postal Code  ...  \\\n",
       "0     Consumer  United States       Lorain        Ohio        44052  ...   \n",
       "1     Consumer  United States  Los Angeles  California        90036  ...   \n",
       "2  Home Office  United States     Franklin   Wisconsin        53132  ...   \n",
       "3     Consumer  United States   Huntsville       Texas        77340  ...   \n",
       "4     Consumer  United States   Huntsville       Texas        77340  ...   \n",
       "\n",
       "          Category Sub-Category  \\\n",
       "0        Furniture  Furnishings   \n",
       "1        Furniture  Furnishings   \n",
       "2  Office Supplies      Binders   \n",
       "3  Office Supplies      Storage   \n",
       "4        Furniture  Furnishings   \n",
       "\n",
       "                                        Product Name    Sales Quantity  \\\n",
       "0           Linden 10 inches Round Wall Clock, Black   48.896        4   \n",
       "1  Howard Miller 11-1/2 inches Diameter Brentwood...  474.430       11   \n",
       "2            Wilson Jones Easy Flow II Sheet Lifters    3.600        2   \n",
       "3                      SAFCO Boltless Steel Shelving  454.560        5   \n",
       "4  Tenex Carpeted, Granite-Look or Clear Contempo...  141.420        5   \n",
       "\n",
       "   Discount    Profit  Furniture  Office Supplies  Technology  \n",
       "0       0.2    8.5568          1                0           0  \n",
       "1       0.0  199.2606          1                0           0  \n",
       "2       0.0    1.7280          0                1           0  \n",
       "3       0.2 -107.9580          0                1           0  \n",
       "4       0.6 -187.3815          1                0           0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_categories=df_original\n",
    "df_categories = pd.concat([df_categories, g_dummies], axis = 1)\n",
    "df_categories.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4d0121d",
   "metadata": {},
   "source": [
    "### 12. Category 'Furniture' Sold in each State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "6ab5ed4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,6))\n",
    "sns.barplot(x = 'State', y = 'Furniture Sold', data = df_categories)\n",
    "plt.xticks(rotation=70)\n",
    "plt.title(\"Furniture Sold in each State\", fontsize=16)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea57b0e8",
   "metadata": {},
   "source": [
    "### 13. Category 'Office Supplies' Sold in each State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "e5f24790",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,6))\n",
    "sns.barplot(x = 'State', y = 'Office Supplies', data = df_categories)\n",
    "plt.xticks(rotation=70)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06d09ed4",
   "metadata": {},
   "source": [
    "### 14. Category 'Technology' Sold in each State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "54475e27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,6))\n",
    "sns.barplot(x = 'State', y = 'Technology', data = df_categories)\n",
    "plt.xticks(rotation=70)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "0a076335",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\lareb\\a\\lib\\site-packages\\seaborn\\distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x232b90f2df0>,\n",
       "  <matplotlib.axis.XTick at 0x232b90f2dc0>,\n",
       "  <matplotlib.axis.XTick at 0x232b95985b0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fd43d0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fd48e0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fd4df0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fe0340>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fe0850>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fd4460>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fe0a00>,\n",
       "  <matplotlib.axis.XTick at 0x232b9fe0f10>,\n",
       "  <matplotlib.axis.XTick at 0x232b90e2940>,\n",
       "  <matplotlib.axis.XTick at 0x232b9ed6a60>,\n",
       "  <matplotlib.axis.XTick at 0x232b9ffbeb0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9ffbfa0>,\n",
       "  <matplotlib.axis.XTick at 0x232b9ff64f0>],\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xdata = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]\n",
    "plt.figure(figsize = (12,6))\n",
    "sns.distplot(df_original['Quantity'])\n",
    "plt.xticks(xdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a1d100e",
   "metadata": {},
   "source": [
    "### 15. HeatMap for Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "c75fd735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df_categories.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "452a6f57",
   "metadata": {},
   "source": [
    "### 16. Most Sales Performed using 'Ship Mode' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "718a28a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Sales'>"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pie = df_original.groupby('Ship Mode')['Sales'].sum().plot(kind= 'pie')\n",
    "pie"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4030e917",
   "metadata": {},
   "source": [
    "### 17. Most Store Customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "c72ee074",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Sales'>"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pie = df_original.groupby('Segment')['Sales'].sum().plot(kind= 'pie')\n",
    "pie"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6747b42",
   "metadata": {},
   "source": [
    "### 18. Frequently consumed Shiping Mode by Category "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "ef2ffed3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "sns.countplot(data = df_original, x='Ship Mode',hue='Category' ,palette='rocket')\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.xlabel('\\n Ship Mode', fontweight = 'bold', fontsize = 10)\n",
    "plt.ylabel('Count of Ship Mode', fontweight = 'bold', fontsize = 10)\n",
    "plt.title('Ship Mode', fontweight = 'bold', fontsize = 15)\n",
    "plt.savefig(\"Ship Mode.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d31f9bb",
   "metadata": {},
   "source": [
    "### 19. Sales Rise through-out the Year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "ace25cf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_months=df_original\n",
    "df_months['Month'] = df_months['Order Date'].str[3:5]\n",
    "df_months['Month'] = df_months['Month'].astype('int32')\n",
    "keys = [pair for pair, df in df_months.groupby(['Month'])]\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.plot(keys, df_months.groupby(['Month']).sum()['Sales'])\n",
    "plt.xticks(keys)\n",
    "plt.xlabel('Months of the Year', fontweight = 'bold', fontsize =10)\n",
    "plt.ylabel('Invoices', fontweight = 'bold', fontsize =10)\n",
    "plt.title('Sales over the Year', fontweight = 'bold', fontsize =15)\n",
    "plt.savefig(\"Sales over the Year.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c075a52",
   "metadata": {},
   "source": [
    "### 21. Most Customer Consume which Shiping Line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "b3cfeab6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(5,5))\n",
    "sns.barplot(x='Ship Mode',y='Quantity',data = df_original, estimator=sum, palette = 'rocket', ci = None)\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Product Line', fontweight = 'bold', fontsize =10)\n",
    "plt.ylabel('Quantities', fontweight = 'bold', fontsize =10)\n",
    "plt.title('Quantities by Ship Mode', fontweight = 'bold', fontsize =15)\n",
    "plt.savefig(\"Quantities by Ship Mode.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ed0397c",
   "metadata": {},
   "source": [
    "### 22. Products consumed By each State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "34075a42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsndmS11V1gap6fVV9pKo+VFVHTMvPXlWvrqpPTJdnW3jOA6vqk1X1saq6/sLyK1bVB6b7HlNVNdd2AwAAAACwenP2vD4pyR90988luWqSe1fVJZP8SZLXdvfhSV473c50362SXCrJDZI8rqoOntb1+CR3T3L49HeDGbcbAAAAAIAVmy153d1f6O73TNe/neQjSc6X5EZJnjE97BlJbjxdv1GS53b3id39qSSfTHKVqjpPksO6++3d3UmeufAcAAAAAAAOQEupeV1VF0py+STvTHLu7v5CMhLcSc41Pex8ST678LTjp2Xnm65vXr5VnLtX1dFVdfQJJ5ywra8BAAAAAIDlmT15XVVnSvKCJPfr7m/t7aFbLOu9LD/lwu4ndveVuvtKhx566I++sQAAAAAArIVZk9dVdZqMxPWzu/uF0+IvTaVAMl1+eVp+fJILLDz9/Ek+Py0//xbLAQAAAAA4QM2WvK6qSvKUJB/p7r9fuOvFSe4wXb9Dkv9YWH6rqjpdVV04Y2LGd02lRb5dVVed1nn7hecAAAAAAHAAOmTGdV89ye2SfKCqjp2WPSjJ3yY5qqrukuS/k9w8Sbr7Q1V1VJIPJzkpyb27+wfT8+6V5OlJzpDk5dMfAAAAAAAHqNmS1939lmxdrzpJrruH5zwsycO2WH50kktv39YBAAAAALDOZp+wEQAAAAAAflSS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2fuTkdVUdVlXnn2NjAAAAAAAg2c/kdVU9u6oeXVUXS/K5JJ+pqgfv4zlPraovV9UHF5YdWVWfq6pjp78bLtz3wKr6ZFV9rKquv7D8ilX1gem+x1RV/egvEwAAAACAU5P97Xl9vSQfT3KzJF9O8uYkv7uP5zw9yQ22WP6o7r7c9PeyJKmqSya5VZJLTc95XFUdPD3+8UnunuTw6W+rdQIAAAAAcADZ3+T1mZN8P8nlkzwvyZOT/NTentDdb0rytf1c/42SPLe7T+zuTyX5ZJKrVNV5khzW3W/v7k7yzCQ33s91AgAAAABwKrW/yeuPJ3lkRuL4bUl+OsmXfsyY96mq909lRc42LTtfks8uPOb4adn5puubl2+pqu5eVUdX1dEnnHDCj7l5AAAAAACs2v4mr++V5PVJ/iHJfyY5XZIn/BjxHp/kokkul+QLGQnxJNmqjnXvZfmWuvuJ3X2l7r7SoYce+mNsHgAAAAAA6+CQ/XlQd7+tqm6e5JIZZTwe9uME6+6Te2tX1ZOSvHS6eXySCyw89PxJPj8tP/8WywEAAAAAOIDtV8/rqrp8Rh3qo5Ncuao+PCWffyRTDesNN0nywen6i5PcqqpOV1UXzpiY8V3d/YUk366qq1ZVJbl9kv/4UeMCAAAAAHDqsl89r5P8Y5ITMsp4/DDJs5PcdW9PqKrnJLl2knNU1fFJHpLk2lV1uYzSH59Oco8k6e4PVdVRST6c5KQk9+7uH0yruleSpyc5Q5KXT38AAAAAABzA9jd5fdkkf5Vko1zI55Oca29P6O5bb7H4KXt5/MMW1r+4/Ogkl97P7QQAAAAA4ACwv8nr45Nca7p+mSS3zug5DQAAAAAA225/k9cPT/Lk6frfT5d33PatAQAAAACA7GfyurufWlX/leTXM+pev7S73zjrlgEAAAAAsGPtNXldVVdI8l9JLprk20meu3hfd79n3s0DAAAAAGAn2lfP63dn1Ld+bpLe4v6Dt32LAAAAAADY8faVvH5mxsSMz5h/UwAAAAAAYNhr8rq775QkVXX6JB/u7q8s3D77/JsHAAAAAMBOdNB+Pu71Sa6zcPtGST67/ZsDAAAAAAD7nrDxmkmunaSS3Lyqfm6665pJ/m/eTQMAAAAAYKfaV83r6yR5SMZkjTeb/ja8Zq6NAgAAAABgZ9tX8vqoJB+aLv8hyVszEtlfT/KWWbcMAAAAAIAda18TNn4kyUeq6sJJvtzd313OZgEAAAAAsJPtq+b1t5LcIckzptuLd3d3n2W+TQMAAAAAYKfaV9mQr2ZMzPi1jHIhAAAAAAAwu32VDbnwdPWlS9gWAAAAAABIkhy0Pw+qqh9U1c0Xbt+wqj4232YBAAAAALCT7avm9c8kuVCSSnKpqvrSdNevJbnovJsGAAAAAMBOta+a13dK8ucZ9a7/bPpLRjL7IzNuFwAAAAAAO9i+ktfvSvL4JL+b5FVJPpGRyP56kmfPu2kAAAAAAOxU+5qw8eVJXl5V707yhu7+zHI2CwAAAACAnWxfPa83vCPJn1bVhZIcPC3r7r7uLFsFAAAAAMCOtr/J639PcvFNy3p7NwUAAAAAAIaD9vNxZ0/yqCTnSXLO6e9cc20UAAAAAAA72/4mr5+U5GeTnCmjx/XGHwAAAAAAbLv9LRvyoIxk9W8sLOsf4fkAAAAAALDf9jf5/KboaQ0AAAAAwJLsV/K6u68983YAAAAAAMDJ9it5XVWV5FZJfj7J6afF3d1/MNeGAQAAAACwc+1v2ZB/SnLPjNIhNS3rJJLXAAAAAABsu/1NXt8kyb8muXWSI5LcOMmbZ9omAIB9Ot3zPzHr+k+8+eGzrh8AAIC9O2g/H3e2jGR1Jflakn9Lcru5NgoAAAAAgJ1tf3tef3F67BcySoicNsm35tooAAAAAAB2tv3tef2nSf4ro8b195J8M8n9ZtomAAAAAAB2uP3qed3d/7Jw87kzbQsAAAAAACTZz+R1Vb1ui8Xd3dfd5u0BAAAAAID9rnl97S2W9TZuBwAAAAAAnGx/k9fnXLh+tiRHZkzeCAAAAAAA225/J2zshb9vJflYkjvMtVEAAAAAAOxs+9vz+is5ZZmQj23ztgAAAAAAQJL9T16/ceH6D5J8Osn/2/atAQAAAACA7EfZkKq6bpJKcukkl5uuP7u7Pzrdf545NxAAAAAAgJ1nrz2vq+oWSZ6TkbDecJ0k16yqmyS5fpL/SfLQ2bYQAAAAAIAdZ189rx+U5HNJbpDksOnvBtOyFyW5S5Kj59xAAAAAAAB2nn0lry+R5G+6+1Xd/b/T36uS/N303Gt098tm30oAAAAAAHaUfSWvv5Xk8lss//kkX+3u92z/JgEAAAAAsNPtteZ1kv9McpequkSSdyTpJFdOcq0kz5h52wAAAAAA2KH2lbz+gyQXSfJLSa6xsPwtSR4w10YBAAAAALCz7TV53d1fS3KtqrpWRqmQJPlgd79h7g0DAAAAAGDn2lfP6yRJd78xyRtn3hYAAAAAAEiy7wkbAQAAAABg6SSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANbOIaveAA4MT3/c82db9x1/9+azrRsAAAAAWE96XgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArJ3ZktdV9dSq+nJVfXBh2dmr6tVV9Ynp8mwL9z2wqj5ZVR+rqusvLL9iVX1guu8xVVVzbTMAAAAAAOthzp7XT09yg03L/iTJa7v78CSvnW6nqi6Z5FZJLjU953FVdfD0nMcnuXuSw6e/zesEAAAAAOAAM1vyurvflORrmxbfKMkzpuvPSHLjheXP7e4Tu/tTST6Z5CpVdZ4kh3X327u7kzxz4TkAAAAAABygll3z+tzd/YUkmS7PNS0/X5LPLjzu+GnZ+abrm5dvqaruXlVHV9XRJ5xwwrZuOAAAAAAAy7MuEzZuVce697J8S939xO6+Undf6dBDD922jQMAAAAAYLmWnbz+0lQKJNPll6flxye5wMLjzp/k89Py82+xHAAAAACAA9iyk9cvTnKH6fodkvzHwvJbVdXpqurCGRMzvmsqLfLtqrpqVVWS2y88BwAAAACAA9Qhc624qp6T5NpJzlFVxyd5SJK/TXJUVd0lyX8nuXmSdPeHquqoJB9OclKSe3f3D6ZV3SvJ05OcIcnLpz8AAAAAAA5gsyWvu/vWe7jrunt4/MOSPGyL5UcnufQ2bhoAAAAAAGtuXSZsBAAAAACAk0leAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDaOWTVGwCw2Zue+eZZ13/N2//SrOsHAAAA4Cen5zUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1c8iqNwBgXbzzX94+6/p/4bZXm3X9AAAAAAcSPa8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa0fyGgAAAACAtSN5DQAAAADA2pG8BgAAAABg7Ryy6g0AAGDfznXUJ2db95dv8bOzrRsAAODHpec1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDt7IgJGx/xiCfNtu4HPOBus60bAAAAAGCn0vMaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArB3JawAAAAAA1o7kNQAAAAAAa2clyeuq+nRVfaCqjq2qo6dlZ6+qV1fVJ6bLsy08/oFV9cmq+lhVXX8V2wwAAAAAwPKssuf1dbr7ct19pen2nyR5bXcfnuS10+1U1SWT3CrJpZLcIMnjqurgVWwwAAAAAADLsU5lQ26U5BnT9WckufHC8ud294nd/akkn0xyleVvHgAAAAAAy7Kq5HUneVVVHVNVd5+Wnbu7v5Ak0+W5puXnS/LZhecePy07haq6e1UdXVVHn3DCCTNtOgAAAAAAcztkRXGv3t2fr6pzJXl1VX10L4+tLZb1Vg/s7icmeWKSnPe8593yMQAAAAAArL+V9Lzu7s9Pl19O8qKMMiBfqqrzJMl0+eXp4ccnucDC08+f5PPL21oAAAAAAJZt6cnrqjpjVZ1543qSX03ywSQvTnKH6WF3SPIf0/UXJ7lVVZ2uqi6c5PAk71ruVgMAAAAAsEyrKBty7iQvqqqN+P/a3a+oqncnOaqq7pLkv5PcPEm6+0NVdVSSDyc5Kcm9u/sHK9huAAAAAACWZOnJ6+4+Lsllt1j+1STX3cNzHpbkYTNvGgAAAAAAa2IlNa8BAAAAAGBvJK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuS1wAAAAAArJ1DVr0BwPp69dNfN+v6r3fHX551/QAAAACceul5DQAAAADA2pG8BgAAAABg7UheAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7ktcAAAAAAKwdyWsAAAAAANaO5DUAAAAAAGvnkFVvAPy4/vWf/33W9f/OPW486/oBAAAAgD3T8xoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO1IXgMAAAAAsHYkrwEAAAAAWDuHrHoDAGBuX3jeB2db93lueenZ1g0AAAA7mZ7XAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDakbwGAAAAAGDtSF4DAAAAALB2JK8BAAAAAFg7h6x6A4D989Knvmq2df/GnX91tnUDwI/qYs//xKzr//jND591/QAAwPbQ8xoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO2oeQ3A0nz6ue+bdf0XutVlZ10/AAAAsDyS1wAAkOTn/+3js637Aze72GzrBgCAA5XkNQDM4BtHfXjW9Z/1Fpecdf0AAACwampeAwAAAACwdiSvAQAAAABYO5LXAAAAAACsHclrAAAAAADWjuQ1AAAAAABrR/IaAAAAAIC1I3kNAAAAAMDaOWTVGwAAAADs2e2+d9ys63/W6S8y6/oB4Mel5zUAAAAAAGtH8hoAAAAAgLUjeQ0AAAAAwNqRvAYAAAAAYO2YsBEAAFiKX37th2db9+uue8nZ1g0AwGpIXgMAAAesX3vrh2Zd/8uvfqlZ1w8AsJMpGwIAAAAAwNqRvAYAAAAAYO0oGwIAAMCP7ZbHfXDW9T/vIpeedf0AwPqSvAaAA8h3n//RWdd/hptfYtb1AxwobnTMvAnd/7iihC4AcOBTNgQAAAAAgLWj5/UB5p8f+6+zrv8ev/c7s64fAAAAACDR8xoAAAAAgDUkeQ0AAAAAwNpRNgRgB/rYc94z6/ovfusrzLp+AACA/XHPy5591vU/4X1fm3X9sNNJXgMA/AjO8vxPzLr+b9788FnXDwAAcGqhbAgAAAAAAGtHz2sAAABgR7vzWb816/qf+o3DZl0/wIFKz2sAAAAAANaOntcAAACwn27ztY/Nuv5nn/3is64fAE5NJK8BAACAtXHH03151vU//cRzzbp+ALaP5DUAAADADnK3C867/id9Zt71AzuHmtcAAAAAAKwdPa8BAAA41bn15z886/qfc95Lzrp+AGDfJK8BAACAU7hDjp91/c/I+WddPwCnfpLX8CN64ZNfNuv6f/uuN5x1/QAAAACwL39411vOuv7/9+Tn7fMxktcAALDDXONlH5l1/W+54c/Nun727KYf+uBs637BpS4927oBALZiwkYAAAAAANaOntcAAAAAwI/lPr96mVnX/4+vev+s62e9SV4DAAAArMBdfvrEWdf/lC+ebtb1A8xN8hoAAACA2d39EofOtu4nfvSE2db947jXL5x31vU//p2fn3X9pwb3/c2rzrr+x7zkHbOu/0dx/9v95qzr//tnvWTW9f8kJK8BAAAA4ABw72sdPtu6/+mNn5ht3bAnktcAAGzpgkfN20D5zC3ma1ydWlz5Pz466/rffaNLzLp+AICd5n63uO5s6/6Ho14727pPrU41yeuqukGSRyc5OMmTu/tvV7xJAMCkn//x2dZdN7/YbOsGAABgfZ0qktdVdXCSf0pyvSTHJ3l3Vb24uz+82i0D+Mkc++x3zbr+y93mKrOuHwAAAGAuB616A/bTVZJ8sruP6+7vJ3lukhuteJsAAAAAAJhJdfeqt2GfqupmSW7Q3Xedbt8uyS909302Pe7uSe4+3bx4ko/9mCHPkeQrP+Zzf1yriLnT4u6k17qquDvpta4q7k56rauKu5Ne66ri7qTXuqq4O+m17rS4O+m1riruTnqtq4q7k17rquLupNe6qrg76bWuKu5Oeq2riruTXuuq4u6k1/qTxr1gd59z88JTRdmQJLXFslNk3bv7iUme+BMHqzq6u6/0k65n3WPutLg76bWuKu5Oeq2riruTXuuq4u6k17qquDvpta4q7k56rTst7k56rauKu5Ne66ri7qTXuqq4O+m1riruTnqtq4q7k17rquLupNe6qrg76bXOFffUUjbk+CQXWLh9/iSfX9G2AAAAAAAws1NL8vrdSQ6vqgtX1WmT3CrJi1e8TQAAAAAAzORUUTaku0+qqvskeWWSg5M8tbs/NGPIn7j0yKkk5k6Lu5Ne66ri7qTXuqq4O+m1riruTnqtq4q7k17rquLupNe60+LupNe6qrg76bWuKu5Oeq2riruTXuuq4u6k17qquDvpta4q7k56rauKu5Ne6yxxTxUTNgIAAAAAsLOcWsqGAAAAAACwg0heAwAAAACwdiSvAYADUlWdbotlZ1/FtgAAAPCjU/Oa2VXVw5P8VZLvJnlFkssmuV93/8sSYp8tyeFJTr+xrLvfNHdc2G5Vda7s/jn+7xVuzgGnqq6R5PDuflpVnTPJmbr7U6veLn4yVfWfSW7c3f833T5Pkpd29xVXu2UAO0tVHZ3kaUn+tbu/vurtOVBV1dm7+2ur3o4DWVWdNsnFppsf2zjGWEJc7doDVFVdOskls/v/9pmr26L5VNUFM9pcr6mqMyQ5pLu/vertOpAcqJ8nyetJVV02yS9NN9/c3e9b5fbMqarOl+SCSQ7ZWDbnjq+qju3uy1XVTZLcOMnvJ3l9d192rphT3LsmOSLJ+ZMcm+SqSd7e3b88Z9yF+CtJNi77/zvFdDA1k6r6rSSPTHLeJF/O+N9+pLsvNWPM23b3v1TV/be6v7v/fsbYZ0lyZHb9Hr8xyUO7+5szxnxIkisluXh3X6yqzpvk+d199bliboq/9O9PVV00yfHdfWJVXTvJZZI8s7u/MWPM13b3dfe1bJtj3i3Jrye5aZILJHlxkj/s7lfNFXOKe0R3P3pfy2aIu/T/6xT39EnukuRS2f1zfOcDKeZC7KU3CnZaR4BlxqyqxybZY4Oou+87R9yF+OdM8sc55Wdq9uPVqvr1nPI79NCZYv1skjsluWWSjUT2q3rmxuiK399KcpskF+nuh1bVzyT56e5+14wxP5HR7nlakpcv4f39h+6+X1W9JFt8j7r7t+aMv7AdZ0tyge5+/8xxrp3kGUk+naQyji3usITfxKW2a6vqA9n77+Jl5oi7aRtWse85Z5K7JblQdm9Lz3k885Ak1874jXpZkl9L8pbuvtlcMRdiL/VEzHRcfvckZ+/ui1bV4UmeMGdbYFP8ZR5bHJ7kb3LKfc9F5oi3EHdln6e5HbLvhxz4quqIjB+pF06L/qWqntjdj5057tI/0FX1dxkHjR9O8oONkEnm3BGcZrq8YZLndPfXxrHc7I5IcuUk7+ju61TVJZL8xdxB95RszGgczB176f/fPR1MJZmtUVBVv53k75KcK+PAsZJ0dx82V8yF2FdN8tgkP5fktEkOTvKdGWP/ZcZ7+pruvnxVXSfJrWeKteGM0+WZZ46zlacm+WCSW0y3b5fRAPvtGWPeJMnlk7wnSbr781W1lNe+iu/P5AVJrjQlE56SkdT914zf6W01JRkPTXKO6aBxYwdwWMbv5Gy6+0nTgfm/ZzRE7tHdb5sz5uQOSTYnqu+4xbLttrT/6ybPSvLRJNdP8tCMZM1HDsCYe2wUJJm7R8uvdvcfTR0Bjk9y8ySvTzJr8npF+/hlxzx6urx6xv/1edPtmyc5ZqaYi549xfz1JPfM+P34n7mDVtUTMn6br5PkyUlulmS2pGp3fzLJg6vqz5L8Rsb+/odV9dQkj56xt/BK3t/J45L8MOOz+9Ak3874nb7yjDEvluRXktw5yWOr6nlJnt7dH58p3rOmy/830/r3qKrekOS3MnIaxyb5n6p6Y3dv2flimzwy4/f4Y9M2XCzJc5LMPaJr2e3a35gu7z1dbvyfb5PkhBnjJlnp8fF/JHlzktdkV1t6bjfLOCH93u6+U1WdO+M3eVZbnYipqrlPxNw7yVWSvDNJuvsTU4e/2a3gM/W0JA9J8qiM/eydsqsNNKeVfJ6SpKquntEJbaMj5UaOZnvym9294/+SvD/JGRdunzHJ+5cQ9y1JrjvFv+D0j/6LmWN+LMnplvz+/m1GA/O9GYnscyZ55xLivnu6PHbjNSc5dglx35fkpzJ+MJLxY/XEJb3Xq/j/fiDj5Mux0+1LJHnezDE/meTnlvk6F2IfneRnp8/zwRk7oofNGW+6fF+Sg6br71rC6zw4ye+v4P09dn+WbXPMd02X75kul7IPmGIt/fuz6bU+IMnvTdffO1OsI5J8KsmJSY6brn9q+kzfZ6aY91/4+4NpP/CsjWUzvq+3TvKSJF/PSBxv/L0+4wTUAfN/3RT3vdPl+6fL0yR53YEWc4rzgYw5Y9433T53kpcsIe6HpssnJbnBdP19S3q9y97Hr+p38fVJTrNw+zQZIwXnjnvMdPn+hWVvXELc92+6PFNGT+g5Y14moyH/sSSPSfILG7/RB9r7O8XZ+E1+78Ky2b+3C7Guk+RzSb6RMZLtajPHO+30P/75JKddwut773R510xt6Mx8/LbV+ueOOcVYVbv2rfuzbIa4q9oPzP6ebhFzox1yTEbHjtrY588c95iMUacbty+28Xs5Y8x3TpfvnS4PWcb3Z4q11M/Uwr7nAwvL3nygfp6mmB/N6NRxrox82E8l+antWr+e10Nl9zNrP8hyzoqcobtfW1XV3Z9JcmRVvTnjDM1cjss4GD9xxhi76e4/mXoEf6u7f1BV30lyoyWEPr6qzprR4+7VVfX1JJ9fQtz/6+6vVtVBVXVQd79+ev3LsPT/b5Lvdff3qipVdbru/mhVXXzmmF/q7tl72O1Jd3+yqg7u7h8keVpVzdmT8xtVdaaM3vPPrqovJzlpxnhJkum7+lsZjcxl+m5VXaO735KcfAb3uzPHPKqq/jnJWafhbHfOSBAtwyq+P0nyf1V164weaL85LTvNXh7/Y+tRKuPRVfV7PfOIpgWbe86/aA/Lt9vbknwhyTkyemdt+HbGieq5Le3/ujnudPmNqaTGFzN6uh9oMZPku939w6o6qaoOyxhhNesQ0MlLquqjGb+HvzsNbf7eEuKu4jdqVb+L5834jdjoAXymzDw6ZLLxWf7CVMbj8xk9w+a2sW89YSqX9dUkF54rWFUdk5FEfUqSP+nujWPVd077+rms6v1Nxm/ywZnKL0zf2x/OGbCqfirJbTNGrn0pye9lnES9XJLnZ6b/8fTePiHJf2W0oy9cVffo7pfPEW9ySI25LG6R5MEzxll0dFU9Jbv3RF7GCI1VtWvPuOm4/Beza4TmnFa1H3hpVd2wu1+2hFgbjp7+t0/K+Cz9b2YcBbPgND2NIEiS7v54Vc19zPjGqnpQkjNU1fWS/G5Gp49lWPZn6ntVdVCST1TVfTJOJC6jl/mqPk9J8s05f/Mlr4enZRw4bTRub5xxYDW3VXygT0hybFW9NgsJzp65nl+S8yW53jR8fMOsQ2y7+ybT1SOr6vVJzpJRJ3JuK0k2Tlbx/13FwdTR0zDIf8/ur/OFe3zG9jlhKkNwbI0apF/IvAdxN8pIUPx+xgHyWTKGni7D26rqHzOG235nY2F3v2fGmPdK8owata8rI4lwxxnjpbv/33QA9a0kF0/y59396jljLlhVY+ROGcOnH9bdn6qqC2fm8gPd/dip0XOh7F5HcNv3Bd39F1PC4G+7+wHbvf69xP1Mks8kudqyYm6y9P/r5IlTSZg/y0iSnCnJnx+AMZMVNQp2WEeAVf0u/m2S907HjElyrYxRkXP7q2mf9wcZZckOS3K/JcR96fQ+PyKjbFZn3qHFN+/u47a6o7vnLA221fv7+zPGW/SYjJOn56qqh2UM5/7TmWO+PSOxeuPuPn5h+dE1SsXM5ZFJrtOjPMzGHAz/mWTO5PVDk7wyo57ru6vqIkk+MWO8ZByn3jvJfTOOU9+UUR5mVits194lyVOn71AyTkDNPrdEVrcfOCLJg6rq+9l14qt7xtKU3f2709UnVNUrkhzWM9dun6ziRMwfZ4yU+ECSe2SUX1tKSYss/zN1v4zSXPfNKAP6yxmdS2a1is9TVV1huvr6qnpERjnmxRzNtuQOTNg4md7wa2TaCXX3e5cQ88oZ9RnPmvGBPkuSh3f3O2aMueUXprufMWPMh2R1kxAcnDGkdzFRMuvEiVV1xoxk48YkLWdJ8uzu/uqccafYS///bop/rUwHU939/RnjPG2Lxd3Lmajrghk97U6T0fg5S5LHbRysH0gWGvCLupczydFhU7BvzR1rinfB7Jr5+tAkB/eSZ75e1vdninVEL3lCwap6VpKLZgx5Pbkm/5wn12rmCSH3Evfb2TXR0Wkzfi/mrI3PClTVhbK8RubKZ49f5m/UqmJW1U9nlLJIxvDmLy4h5tW7+637WjbzNpwuyel73smRz53kr5Oct7t/raoumVHGYhkdhpZu6qB01YyT8NfNaBe8du6Rg1V19+5+4qZlf9vdfzJz3Dd19zUXbldGeZZr7uVppzob7bxp9OVGW/N03b2MOtBLb9cuxD4sI3c022/EXmIvfd+zTFsdqy7j+HX63b93FnJgGW3aWUZwT7+J7+/uS8+x/h9xWzY+Uy/vmSepXLZVfJ72kDPYsG25gx2dvK6qw7r7W1V19q3u7/kmDtlRasxWfNmM2kaXnQ5en9zdv7mPp/6kcX8vowTLl7JriF73EmZHnuIflt0PLg6oz9OevjcbDrTXu2xV9ZbuvsZCEqwWLw+0JFhV7XVyne7++xljr3rm61WcZHtPd19h07L3dvflZ4z5kSSX7CUeeFTVIzNmFX9+dh89sIxRGovbceMkV+nuB820/qO6+xbT/nbx/d34vZh1vzc1gG6aU/aqn22UyLJjVtUlpiGmV9jq/plHpKysI0BVPTRj8qq3dfd39vX4nzDWyo/Lq+p82TXR0EbcOSev2tPv8SmWzRR7KaNhplgvzxjt+uCpPXBIRtvg5+eItxD3whmlMy6U3V/nb80Zd4r99u5e6kic6X3+l+5+9nT7cRnJ1bvMHPfxGd+dozL2QzfPqG3+1mSe/W6NEb13SXKp7H5Sb7bOLFX1jiS/0t3/O93eqBX/i3PFnOKspF27gn3tytuXNcombpx0eUN3v3SmOBsTmr8+Y/++OKH5y7v75+aIu0pV9ewkD1zWSZdNsR/a3X++cPvgJM/s7ttsc5x/6O77VdVLsvsxeZL59j074fO008uG/GvGTLrHZIvGXmaqYbiKD/SKG7arqg95RMYkBLP3eF5UVffIGMb23YyDi1k/T5tiH57kb3LKnllzxN743lSSn8mYoKwyRhL8d+atm3j+jKGfV5+24S1Jjujdh0dud8w9fYeSJNv9Herua0yXc9fo3aOq2nII/kwHrBuv8+IZs6m/eLr9mxk9Aea0ypmvt2yMZEx4NEe8Wyf5nYxalC9euOvMGfVO5/TBJD+dUWpnWc6e8boWz/h3xnC2penuf6+qOXu9HTFd/saMMfbmP5J8M2O/sKw5F5Yd8/4ZJ7keucV9nflmq9+wqtnjP50xEeljppOpb84YofgfM8TafFy+OP/M7MdRNcqy3DLJh7L77/Es+6CqulqSX0xyzk0ncA/LmDR5VnsaDZP5yvqdo7uPqqoHJkl3n1RVP9jXk7bBv2eUg3xJZq43vYVXVdVNk7xwiSdufzvJi6vqhxknub7Wu4aRz+n0Gccy15pu/0/GPvg3M99+91kZE4RdP6PtdZuMUc1zOv1G4jpJuvt/pxF7c1tJuzbL39eurH2ZjFEKGe2QZ0+LjqhR83uOY7h7ZJSWOG9G6aYN30ryTzPE202NuQaOzClP2M65rz1Pkg9V1buye6eS2U8mJvmZqnpgd//NdFLm+dn9fd8uG2VY/t8M696blX6eNtSY/2DzCcVtyR3s6OR1d//GdDnrj+AWVvGBXmXDdlVF4z+bsbNdtj9Mcqnu/soKYj8tIxH2qCTXyah/Osvkoxvfmxr1817c08QWVfVrSX5ljpgLnpbRyL35dPu207LrzRhzZd+h2lXWqDN62s1e1miy2Mvu9BmvfZZGQXf/RZJU1auSXKGnkh1VdWTGwcWcTuzu748RrsnUG2xZjcxlN0ZWOaHgOZJ8eDpgXayDNtsBa3ffaa51701VLdZvPSjJlTLjZ6q7vzBdfmZKal55uutd3f3lueIuOH9332AJcVYWs7vvPl1eZ1kxN1lJR4DufmpGvdOfzpgU7Q8zkvjbfmJ1hcflG26c8Xu8rBMwp82o1X5Idn8/v5VxsmJuV8pyR8N8p8ZkghuTF141yzlO/153P2YJcbZy/4x5UU6qqo2SgrOMntvUY/WuGUn7tyZ5aFWdfe4eqyva3/5sd9+8qm7U3c+oqn/NqIE9p+9U1RU2RttU1RUz/8Tiyeratcve166yfZkkN0xyue7+4RT3GUnem2Tbk9e9mgnNFz0lowTmMdl1AnNuf7GkOFu5U8Z8ZA/MyJO8vLsftd1BuvuY6fKN273ufcRd9edp43t7aMb7++SMY5lty/vt6LIhi1YxTHAVatTp2mgAXSzJJbLEWj+1xPqQNSYguHjGZCGLiZLZyg9McV+R5Ld7CbXPtoh9THdfsao+sDEMs6re3N2/NHfMTcuO7u4rzRjz2O6+3L6WHQim3s83z64eKzdO8vzu/qsVbMvpMg4krz9jjI8muexG8mCK+b7uvsSMMR+eMQHN7TOGFv9ukg939+wz19eoEXa97l7WpK4bcf+uu/94X8u2Oea1tlo+58HdKkZpTHEX6/KflNF79UlzJ5Kr6hYZk6+9ISNJ8ktJHtDd/zZz3CcmeWx3f2DOOKuOOcXdamK5byb5wJz/32no/4OS3Cpj4rn/TXLs3AmjqnpyxmiuL2X0un5LkvfM/Zu1ovIdL8+YVPB/9/ng7Y17wenE05kzEptLiV9Vz09y342TX0uId4WM3+NLZ4zEOWeSm83dJqiq38koH/WqzDCB1Lqoqk/llGXmNvTMvSlTY7LER2fU+e6MiSPv192fmjHmu7r7KlX1poxjty9mnLSd7bXWmLPqudk10dt5ktxyI2E1Y9xVtWtXta9devtyivH+JNfeONkznRR6w5yj1KvqtBmTbZ9cqiTJP8+dn6mqd3b3L+z7kadutXu5t9Mk+eeME3tPSebbF2zRs33j5OXcv8Ur+TxNsd/f3ZdZuDxTxsijX92W9Ute7zZM8MPZfRKpWYcvrOIDXVXHZDRmz5bkHUmOTnJCb3Otn00x79ILk7HUqC/0pxs9LWeM+5Ctli8h7uUzegG/M7sfXMw2KdlC7Ldm/H//Lcnrknwuyd9298VnjPnKjAbtv2QcrN42yTVnTnC+JsnTkzxnWnTrJHfqJdQonhIXf5fkXBnf2VlrUNeoE3z57v7edPsMGYmDpdetqqqzZTQKDp8xxoMzeve9KOPzdJMkR3X3X88Y86CMmom/mvH/fGVGXf7Zd5ArbIxsVWP1/XMenE8xltoruKpenTFKY2PE022T3Ka75xylsTJV9b6MkyFfnm6fM8lruvuyM8f9cJKfTfKpjM/x7CXJVhFzivufSa6WUVMwGXUF35HkYkke2t3P2sNTt3MbLpTldQR4UcYQ1A8neWNGyZDjZo65quPyF2SUZnltlnj8VmMizmdllFhIkq8kuUN3f3DmuK9PcrmMXlFLGQ0zjWy6eMb39WNLakz/TZLbJfmv7F4rePbJp6f4Z8tIni8OoT4QO0i9I2No+sax+a2S/N6cybGqumuSFyT5+Yx2wZmS/Hl3P2GumFPc02TX5/ijS/ocr6pdu6p97dLbl1PcWyf524x9fGUkAB/Y3c+dMeaTM5Kqz5gW3S7JD7r7rjPF2zj+v0VGiaoXZuYTe3XKuZxOviszz+VUS5pMcIu4H80WPdt75tG2y/48bYr9zu7+hWl/8NsZpRs/uF25A8nrJFX1sSSX6eUNE9yIu/QP9EbCokad1TN098Nr/km6/jWjTtVdkvxURmL3jd39h3PFXKUaQ+LfkuQDWait193P2OOTti/2lTPKOpw1yV9mzKL78O5+x4wxz55RqmTj7N6bkvxFzzg8sap+Jsk/ZiQQOqMUwn17CZM/VNUnk/xmzzxb/EK8lye5dXd/Y7p91oyJeGYvX1K71/c+OKOX1EO7+x9njnvFjDIpyUiULKtMysbn+fzLSApN8ZbaGKmqe2X0Trpokk8u3HXmJG/t7tvOEXeKvfRewasapVFjmOkRC9/bsyV5ZM84idQU5+RRN9PtgzJGLsw9IdoFt1re3Z85kGJOcV+S5K7d/aXp9rmTPD5jmP6buvvSM8W9ekZP6+9U1W2TXCHJo+d+vQvxfy6jruzvJzm4u88/Y6xVHZffYavlcx+/VdXbMiYxfP10+9pJ/rrnnwBuqaNhqurmSV7R3d+uqj/N+Az/1dw9oKf21mW6+/tzxtlD7LtmlAc7f0Zt8asmefucifOquneSZ2/a/9y6ux83V8wpzil6cVbVO7r7qnPGXZaq+uXuft0eRt8sfSLoZVnhvnbp7cuF2OfJ6GhRSd7Z3V+cOd77Nncy2GrZNsZbSTJ3p1lVz/Zlf542xfmzjBFW1804mdkZHcL+bDvWv6NrXi84LuPsxFIPkpN8s7tfvuSYVWOCmNtkJJOTmT8H3f07VXXLjGTuCRkHUG+dK16taIbXBSd19/33/bDt193vnq7+b0Zdp2XE/Fp21YNelgts/j9ODftlzFz8pWUkrqvqsRmf3xMzJrZ49XT7ehknR5ZhMUF+UsZrn728RXcfU1WfzdRLqap+Zs4TE1X1hiS/lfFbeGyS/6mqNy7jezx3j5kt/GuSl2dM7LpYv+/bS2gQPDjJlTf3Cs4YKTKXr0yJvsVRGsuoL36ZjcRBknT316dROXN7xdRbaeP13jLJy+YOutGIrTHR6en38fBti1lVl804CZIkb+7u9y0h9IU2EteTLye5WHd/rarm7H33+CSXnV7zH2UMd31mdk2ONouq+o2M9/iaGaP2XpfRG25OKzkuX0Yngz0440bietqON9Qo8zeruZLUe/Fn3f38qrpGxomQ/5fxuZ67cf++jE4dy6j/v9kRGUmwd3T3darqEpm/5uvduvvkybmm/c/dksyavE7y+hoTEz8343j1lkn+c0pCZo5jjKo6IqNT1Lcz5la6QpI/6e5XbXesjN/a12VMQLnZbBNBr7pdu4r9+xR3Fe3LxV7JG+Xlzjv9Hn9mxjbQD6rqot39X9M2XCQz1qDu1c3dkeTkUfjnzu5lwZbRAW2ZvxfJ+E18RJbQs32TpX6eNnn41PHgBVX10ozfjO9t18p3dPJ6ITl0QpJjq2qpwwSzmg/0EUkemORF3f2h6cO8t7NvP7GqOnyK+4IkP5fkdlNv77lqQq9qhtcNr6+qu2fMar74f13GmeKtDmy+mVEe5p97Kj2xTbFWeTD12Iwdzr6WzeHoqnpexkQ4i//f7T5oPXq6PCajhMaGN2xznD3aIjn0psw8qV9V/VbGRILnzWho/kzGTPKXmjHsWbr7W1MPqad190Nq1Lyb3ZTA/aOcclbmWXo9dPc3M34Tbj0lEA7v7qdV1Tmq6sI9Y23KJAf17mVCvpoxmeG2q1Ef+E+S3DljlMajsmuUxqy9nycHVdXZuvvr0/acPUs45uruB1TVTTNqfFeSJ3b3i/bxtJ/YFt/bC2aMAprtezs1Qu6WXQmDf6mqJ/b8k9S8eTog35hI9qZJ3jQ1br8xY9yTurur6kYZPa6fsqeewtvs1zJ++x/d3Z/f14O3yUqOy6fj1b/JqPG9+Hs898SYx029lRbLG835W5wkqTFh4mMzjs1PmzHC6js93/Dtjcbzryd5fHf/R41Jmed27iQfrap3Z0nlURZ8r7u/V1WpqtN190erarZSfpODqqq6e2NizIMz/r9zu+V0eY9Ny++csf+d43t05+5+dFVdP6Oc350yklPbnozq7odMl8uemHKl7dpV7N+nuEs9Pl7wuIz25PszjqMuPV3/qaq650yJzgdk5A+Om2JeMEvqhFZVv55TvscPnTHe72X0qP9SFso4JZm1DM1kab8Xk40Ts4t12jvJ3J/hlX2eMuY6uEKSTEnsE6vqPdmmHM2OTl5nV3LowxkJoR9mHFgtY8bgZAUf6B411t60cPu4JHMn6V+S5D7d/ZqqqoyZt9+dmXZ6vaIZXhf8znT5wIVlcx20bXZcRmmHxV53X8qoxfmkjJpH22XpB1PTqIFfTHLOqlrsFXtYRqNrGQ7LaFgvTjyw7T0uVtgD7GRbJIeevYTk0F9mDKt9TXdfvqquk9Fbdk6HTEMEb5HRO3iZnp3keRm93O+Z5A5J/mfuoDXKlVwpo2bj0zIatv+SkfScy1a9gucaffTpjBM/D1lSgmKzRyZ5W1Vt9Cq/eZKHLSNwd78g42TxMq3ie3uXJL/Q3d9JTq6T/PaMZNxsuvt3pxME18hoFDwzyQumRNGcvZm+XVUPzFT3c0pInWbGeEmS7r53TbXqpx5ps9eqT/Li6W/ZnpbRqH5Uxv/yTsluk97N5c4ZvXFfOMV7Y5bT0PzHjLrEz8/YH9w+ozbzXD5XVf+c5FeS/F2NCZlnOYG5yZbluZbk+Brl3v49yaur6uvZNdHfXF6Z5KiqekLG8ek9k7xi5pjp7gvPHWMLG9/PG2Z0Pnjf1NacL2DVszLatd+cbl8wyVN7pnl31qBdu4r9e7Ki4+OM48e7dPeHkqSqLpmRDPzLjN/oORKd/5Xx23tyHfUsIZk7/UYcmrG/e3KSm2XMgTCnI5JcvGeu+7wHS/29WGEP96V/nqrqp5OcL8kZavcJMg/L+IxtT5zewTWva0y28LCMg8b/zvjnXiDj4PVBPePkC1Oj477d/ai5Yuwh7sWS/GGSC2X3oRpz1l47rLu/tWnZ4d39iZniLdbp3e2uLGGCiVWqqjd19zW3WlZVH+rubT1hMH2On9Ez1sndFO9aGZNj3TPJ4mQs307ykrk+U6s0Ddn+y5xyYtfZJrZYiP3+JFdbSA6dMaNW45yTsB3d3VeqMfHc5bv7hzXNJj9jzJsn+bMkb5kSUxdJ8ojuvulcMRdiH9PdV6yFyRJrlCyZuxTAsUkunzH55+WnZcuYsHGxV/Cb5uwVXFXnS/L3GXMtPCG7z0Ewe23KqcHzyxmv9bXd/eElxFzqhLILcVfxvf1ARhmajclsT5/k3T1jfe8aNcTf3zPVtd5H7J/OODn+7u5+c425H67d3c+cOe7NM05SvyFLqlW/Kgu/xyfXjq+qN3f3L+3rudu4DQdnlBH51j4f/JPH2vjeLu5/3tYz1dquqkOT3CDJB7r7E9NJ45+fqSfj5thLnSx4D9twrYy5aF7RM9bfnn6n7pFRc7Qykm1P7u5Zho3XCmtBV9XTMhImF86YbPXgJG/o7ivOGPMeGbX/7z/FfkCSP+jul8wUb6Xt2lXs36e4Kzs+7j3MlbLVfdsU85gkv9Xdn5tuXzPJP815PDPFeX93X2bh8kxJXtjdv7rPJ//4MV+fMbH47GUot4i9lN+Lqrptd//Lpo52J+vuv9/OeFvEX/rnqcZIwDtmnAh/98Jd387IFW3LfmCn97x+eMasxBfu7m8nI9GacZD+iCT3mytwd/9gGoaz1OR1Ru+KJ2ScXVtW7ZszVNWjkpyvu28wNeivlmSuROPsE9ntS42Z4zcPO521gTk5Zy3UB54at+eY7tv2A+Xpc3zOqjrtnAfiC/HemOSNVfX0XtIkVZtNCZK75JRDrOYqRfAPGbP1fqCXf7axsvvvxA8yfy+0b0wHT2/K6On95Yx627Pp7udnVwmAjREpsyeuJxsnSb9QY+je5zMmdprb97u7q2pjWPHs9VWT0Su4Rv32Q6a4Z++ZSip19+eq6j8zTlL/ZnYfnjhXbcrDepSgOXuSL2bUGN+4b7bXuuDhWeKEsguW/r3N6GjwzqraOAFy4yRPnTPg1Gh/X81ch38Psb+YcTJm4/Z/Z/T6ntufZkm16qvqqO6+xZ6SNUvofPC9KfH3iaq6T5LPZZwImlWNic3vmbGPPSbJWarq77v7ETOHPqGqTptRouXhSb6QZJZ9wfS+vmvxxE93f2GKOas65WTBj62qpZyAqaqHZtSIf9uyes529w8zaok/fhnxsqJa0JO7JLlckuO6+4Sq+qnMPGqhu/+5qj6UUXbzKxkJ3Tkn9Ft1u3YV+/dkdcfHH6uqx2fUbk/GKMGP1xgpMlfHxnsm+fepw9IVk/x1Ru/guW1UGzihqs6bUc5vlhEUC4nc45K8YTo+XyzjNGtCd7Ks34uN/eiZZ1j3/ljF5+kcSV46/SXjt/9/MjqGbVsZtJ3e8/oTGZPs9KblByf5aHfPOXQuVfWwjDPwz0vynY3lPWPN642zmHOtfw8xX57RyHxwd1+2qg5J8t65zyZOsZfe06LGcPxrZySvX5ZRL/It3X2zJcS+YcbJif/KOEC/cJLfzThgv1t3/8MMMf85o47Ri7P753i2nVAtsbb3FrGfnzH85neSPDRj8tOPdPcsk4pMZ6ivOzVGlmo60LhDRs3tSnKjJE+f43O0EPOMGQdTB2W8t2dJ8uyecXjZ1Gj/qynuKzLOxt+vu/9lrpgLsX8jo2F7gYxyB4dlzKY+65D5qvrDjCFl18uo8XrnJP/aM5aEmXorPTTjff5hdvUa2vaSSlV1qYyG++eT/P6UJJldVb20u3+jqj6V3X+jZnutm+K/tbvnLP2yp7hbfW//Ze5kfY2hiRvlO97U3e+dM94U83UZxxXvyu77vFnL09TqetV/YPF4bUpCvm+OY7iqOk93f6HGMPxTmPukdVVdOaOW61kzRjydJWPyoXfMHHejV99tMhqaf5zkmCX0qLxgRg3b02T0JD1Lksd19ydnivfsJA9c9omfqcfo9TafgOnuyy4h9p0zfqOultED7c0Zv1X/MWPMzfufJEup3b4SNUZZbYxOTHJymcy54t0uY7TeQzKG4l8/yZ16CRMGr6hde8aMCdcqSzoun+Ku6vj4DBlt541ji7dk1MH+XpJDu/t/Z4p7tST/PMX59e5eRgnBP8t4b6+b5J8yfjee3N1/NkOsvZZv6iVNYF9VZ8to/yx2QJvt92JVlv152sP/9+wZv49Hdvdzt7j/R4+zw5PXH+/ui/2o921j/K0mSuyet4THkRkHqi/KzJMJVtUh3X1SVb27u69cY5LGjeHpswy72RR/c0+LpQx1nXoMXTYjQX/Z6UDjyd29VY+EOeKfLsklMl7zR+dM5E7xttwZzbkTqqpH55S1vb+Y5AxJDuvu7aztvTn2e3vUfNsYYnWaJK+c63s7Nab/MqMG5rLPUC81OTSdOHxld//KXDH2EHcjcXCTjN6bv5/k9cto2K5SVV0vo3Z7Zbzvr5453icyytB8Zc44U6yPJDmilzAcfZ1Mv40/nfknlN0c9++6+4/3tWybYz4lyWO7+9iFZUd295FzxZxibDlkee5elVX1yaygV32NicUvk933t++f83+700y9OC+XMVLjH7v7jVX1vgNtH7TCEz9LOwGzl2346Yx5Nf4wydm6e7YeeVNvwg2nz5hz4ezd/edzxZziHpHRWenbGfPsXCHJn8y5H64x18EtM+av2hgp2HN+pqrq35PcfeFkyFUyJke+3FwxpzgradeuSlWdcxkJ3D3EPkOSn+nuj80cZ3NnrEtmjEb5erK0SWU3tuV0SU7fUy33JcU8KMmZegllsqZ4d82ouX3+JMdm1HJ/+4xt+MdssfibSY6e4wTmOn2eFrbp7Bkni03YuA0+XFW3703lHKrqthk9K2fVqynivjEz/QMWNyXzTCb4rowDl+9MB1Ibw9OvmvHFnduDs6Shrpt8t8fQ4pNqlKH5cmaerLH2XG/uIlU1a+JiI0ldVWceN+c5I73J5Xv32t4vqYXa3jPH3hgy9o0a5WG+mFFDfi4PS/K/GQ2QZcwWf7KqumiSD3X3e6rq2kl+qao+1d3fmCNejzI0J1TVWZZ58JRdk57dMMlzuvtrNe98P6mqP+ruh1fVY7N1D6lZJ9KdetK8rrtfXVUXT3LxqjpNzzjXQ8aIkBNmXP+iy/WY5Xolquq1vWnypq2WzWApE8pu4XoZvUUX/doWy7bT9ZNcsUZ5hY3juN9KcuSMMTMlFldRP/dLy05cJ0l3P6B2r1X/xJ6xVn2SVNW3s+fRVX/Qo7TTdsbbajTXyZbQ4PvnjEnC3pfkTVOP6Nka87W68ixL6Vm3ha0mC37ZMgJX1ZMzEghfyuhFerMks42wTZItesT+Q1W9Jcmsyeskd+7uR1fV9TNGiNwpI5k950nkG2dM/ra0/X133zgZx1Hd/Z3ufteUwJ7bUtu1C7/Dla1Hks09987bplEEz8uow/z1meMlSWqUdX1ERpvrwlV1uSQPnWk/8P9mWOc+bZEvWLxv7jr1qyqTlYzE9ZWTvKO7r1NVl8i8+6XTZ3Qo3ChNedMkH0pyl6q6Tnffb5vjreTztDdTm3rbGtU7PXl97yQvnIZ0HZPxw3zljN6bN5k7eFWdJWPI0UYS7o0ZP46zJW16uTNBb3xQ759RUuKiVfXWjB6zs5fQSHLQpgblV7OcWc2PrjGz+JMyPlf/m/ln7l1ZvbkpgfusjKEhqaqvJLl9T7M0z2Sptb03eeI05OjPMj7XZ5quz+XsPePEGfvwgiRXqqqfzaiT/5KMnmFz1s36XpIP1KiLvNgza85k7kuq6qMZZQ9+d2oQzDpiIWNoejKSMavwpoyTEWfLaPwcndGgv82MMR+Y0Rh5Z3bvFbzt/9tVJa5r1MQ/NMk5pvd2Yz94WJLzzh2/u2et9blZVd0rY3jtRWpM8LrhzEneOnP4L2eU6Hp2Vf1CRqNk7pr8W/V+W1b93KOr6nlZcq/6KcYLMvYHy/L3GSV//jXjPb5VxoiCj2XUNb/2NsdbaYOvux+TZLGH1meqas4OLhtlzpZaS3c68XPBJId392tqTOB48BLiLv0EzIKfyniN30jytSRf6ZknKptGzG04KGMCrWXUXt34/b1hkqd19/u2M2mxB8dldEBY2j6/xnD8p2Qc//9MVV02Y4LM35059FLbtXOODtjP+IdPJwVuleTBVfXhJM/t+Uv6PSTJVTL28enuY6vqQnMEmnvE1l5s5AvOleQXM3IISXKdjNc953HFJXvMDXObjJOIf5yRL1lG8vp73f29qkpVna67Pzp14JnLzyb55Y3f/Bq11F+V0eHjA9sdbIWfpz2qql/O1PN7W9bXO7hsyIbpTb1Uxk73Q9392iXFfUGSDyZ5xrTodkku2917PBu2DTFPk+Re2ZUwf0NGjeBt721XVcdn1+RCByU5XcZ7fGKSH8xd9qDWYKjrtLM7rLvfv6/HnlpV1dsy6pm/frp97SR/3TPNVj/FWHpt74XYB/dMM7bvId7fZvSQXXr5g6p6T3dfoar+KGNEwWNrofzPTDHvsNXy7n7GVsu3Me7Zknxr6v19xiRn7nkn4Fmphf/t7yU5w9QLfO7/7bsyagd+ILsmT5z9f7tMNYZN3y8jUf257GrMfyvJk7r7H2eKu5Ke/NNJ+LNl1E3/k4W7vt3z17s++fNaoyTa9ZKcp+evK76S+rlV9bQtFnfPNFnwHno/J0vodVdV7+zuX9i07B3dfdWasZxGjRqrL+slzzEx9eT/6yTn7e5fq2li8+5+ysxxz5hdowUvltFD7OVzjcCpqrsluXvGSfmLVtXhSZ6whBEpK1dVP5cxWuT3kxzc3bNNPFe7l6U8Kcmnkjyy5y+B8LQk58s4Jr9sRtL+DT3jXEtTW/qySV6bmU+KL8R8Z0YnrBcv7IM+2AuTkc4UdyXt2hqjMI/v7hOnNt5lkjxzrlGYe9iGc2TkFG7T3bOe8NrY/2w6xnj/jCNSNkalPzbJz2X0+D44yXfm7t1eVS/NaDd/Ybp9niT/NHMuamVlsmpM8H2njOP0jaTqabp7lk5ZVfWxJFfZ6Jg6HTO/s7svMWebaxWfp9p6JNfZMzoi3L67t6WqxU7veZ0k6e7XZdcZp2W6aHffdOH2X1TVsTPHfHzGGerHTbdvNy276wyxDs44K735rPuhM8TazXSm/zEZPek36vUurafFNBznGhlf4rckWUryuka9qptmlLFYnLjkoTOGPeNG4nqK9YapQTSb7n7Z1OjZqrb3P8wZO8mnquoVGcPYXtfznwG8d5I/qqoTM0qWLGu4XpL8X1XdOsnts+ss/Wn28vifWHc/o6pOm2RjzoGPzdWQ3jD1/rp3kp/JaFifN8nFs2vG5DlirnqYek29h26TMft2Mv8xwUndff99P2z7TCen39HdSylX0t2PTvLoqvq9nnHyyy2spCf/dED+zSS3rlGz/twZn6MzVdWZet6J2U6etKm7j6yqozNGes1tJaO6lt2rfsW97n449XDf6M2+OFpvzn3urTK+vy/I6Dm6rDItT880sfl0++MZxxizJq+z+wic12b+ETj3zujR+M4k6e5PVNW5Zop1slrRZKdT7N/IqE18zYwTfa/LKB8yp7v0ptI6VbWMkbd3yUhKHdfdJ9SodTr379aLs7AvWJbu/uymTuWzdmpZcbt2cRTmUzLe77lHYaZG6c2bZPwuXzRjvq5llGf5YFX9TpKDp7bmfZO8beaY/5jxOp+fMVLi9hmTCs7tQr37hOZfyq7211yWWiZrUXdvVFY4cjrJd5Ykr5gx5MOTHFtVb8j4zl4zyV9PeZLXzBh3FZ+nzSO5OslXu/s7Wz34xyV5vVrfraprdPdbkqSqrp4xbH1OV950Zut1Uy+iOXxh5qTpHnV3V9W/T2f7Zx9Su6iqHpcxTGTjzPg9qupXuvveSwj/HxmJhGOyvCF0x9WYrfhZ0+3bZvTymNsVsytJf5kaNbqeufenbIuLZyRy753kqVMS8rkb3+PttuIEwp0y6pI9rLs/NTV+Zh2uN/XqeEbGgU0luUBV3aHnnQn6aRnfmY3RAsdn7PBnS15n1zD1384YDr/xvt4647XP7X4ZZTxe1N0fqqqLJNlqEuHt9PqquntG+ZlZJwxecMckT6iqr2YkDN6c5C09f+3EH1bVWTd6Jk3JoVt39+P2/rQfT3e/ZLpcSS/2qrpPRq3pL2VXr/rO6KE1i+5+yKbbL82839kNW9XPffncQWuUpLlLxkjB028sn6vn9YrdJsmjMzpadJJ3JLltjUm07jNX0O6+7ZQwuXWSp1VVZ+wfntPd354rbpJzdPdRVfXAaTtOqqpljPCqKcl4l4zJTx9eVbNNypzkxO7+/kbSr6oOybwnIzY8PCuY7HTyaxknCR7d3Z9fUsx/y5hzaPOy2XpAT66W5Nju/k6N+aOukPE9ns2K9nmfrapfTNJTZ4v7ZtcJ5Fmssl2b5IfTb9JNkvxDT6MwlxD3fRllsh7a3W9fQrwNv5dxIvHEjCT9K5P81dxBu/uTtWt079NqjGye2xsWjmc6I+E5a1ugl18mK0k2Jod8/8YIiZ5/ku2DMn4XfjHjpEsledDCfuABe3rudlj256m7PzPn+jdIXq/WPZM8cxpCkIyhC1sOmd9GP6iqi3b3fyXJlLCY6wB59tqT+/COqrpyd797yXGvleTSGz1yq+oZmaGu0R6cv7tvsKRYG+6cMdnBCzP+52/KzD0tqupZGWfhj83C7OJJZk9ed/d3kxyV5KgpIfXojHr1swxjq6prbrV85mTuRowPZxyUbyTfztzdfztz2Ecm+dWN4a3TUObnZN5G10W7+5ZTL/N093er5q3TuHHQVFV/2VtMPjpn7IX4b1y4fVym//WMfme6fODipmTGCW27+/ZJUlXnzei9+U8ZPevnPv65W3f/08J2fL3GkPlZktdr0JP/fhmTZm2eKGzbVdVbuvsadcqyFkvpTdmjfu7G6Kpl9n57VsZk4tdP8tCMBO8qknGzmnrw36u7t5rDIxmj2WbToxbnCzLmv7lfRs+/B1TVY2YcTbGqic2XPQLnjVX1oCRnqKrrZZR7e8mM8TasZLLTJFlSx5UkSY3Jxy6VMQHa4rD/w7JwwmtGj09y2Ro1oP8oo5fuMzPaRbOYesb+TcakmIsn9eYsH3XPjGP/82V0dnhVRoeWua2qXbsxCvMOWdIozMlFpqT9rKN5F037nxd3969k10iYZThhOhFybFU9PMkXksz+urv7PtNvxS9Ni5YxIfNPZdQVXxyh/tCMUWyz6VEe6321MGfWEuI9sruvltG5cJlW8nlaBsnrFaiqI6ahxWfq7stOvTzS3csYMvGAjN5vx2U0ui6Y+RKNq65hd52MXs+fyZj4baNhO1tPsMnHMsoPbJyBukCWVDYkYzK0n+/uZSXLM/VgnDvptdmVMiZ8WEnR/qq6VkZvu19L8u4kt5gx3OKZ2dNnnL09JqNW16ymYU6/lbGvODbJ/1TVG2cu/XCaXqjL2N0fr1Grf07fn3r0bSQOLprljVw4Z1VdZGOI79S7/ZxzB52Gy21VG3mWz9XUA+FPuvt5c6x/L3Fvm3FQ/vNJvpIxlG7uIdtJclBV1cJJzIMz6s7NZdUzjH82y0m2pbuvMV2uclTKMRk18l9TVYdW1Zln7pmbJD/b3Tevqhv1KK+00SPsgNJj3oG5e4huqap+K+OY+KIZJwuu0t1frlFa6iMZNSTnsKqJze+X5Y7A+ZOMJPkHMia4e1nGZNCzWEjgrmyy01pu7dGLZwzdPmt2n8D920nuNkO8zU6ako03yuhp/pTawzwm2+hpGYmwR2W0++6UmTtPdfdXMu/k1nuyqnbt0kdhTq5aVaeYGLO7Z5sYc9r/nFBVZ+mpTvGS3C6j/Nh9MuriXyCjDOjspt/BZfbmf25GR7eN13ebjDJZv7KE2OdJ8qEac/CcXM5ixg4er6oxWfALl5yzWNnnaW4mbFyBqjq2uy9X04RZK4h/uowDnI1awUuboXmZatRQOoW5hjUs9Hw7S0ZNsndNt38hydums7izqF1F8g/JqGl0XMYB+mwHNqvs6VdVz09y3969TtdSVNWnMhK5R2Wcnd/WWk77Ef8CSR7e3bdeQqz3dvflq+quSS7Q3Q+p+ScteWrG52qjDM1tkhzSM9Z7nXqA/WlGz51XJbl6kjt29xvmirkQ+wZJnpjxnU1GKZx7dPesSalNyaHTZxzUnNTdfzRjzDdt6mU+u6r6SsbErk9I8vru/vSS4j4i43/5hIzP8z2TfLa7/2AZ8ZdtamBePMl/Zvfk0CwTM28e/rlMtaJJ56rqXd19lWlkxu8m+WKSd83cw3AlquqRGccyz8/uDcxZG9jTSLmnbDWyqaqu2zNO6F6jhMbGsfnscz3sBLX1JKcbupdQcqdGLf7NtUd/trtn69VZVVfr5ZZZ2Ij7xoz6sXfKqO36PxllRH5+xpjHdPcVq+oDG3Gq6s3d/Uv7eu6PEesxe7u/Z5wkcoq/1HbtqtXqJsY8KslVk7w6u+9/5v7/nnOK8z9zxplirXJC5mN60ySuVXV0d19prpgLcbYcBdIzlRCZ3uczZkyc+70sd76FpX2elknP69X4SFV9OqPH3WKP3NnPoFbVvZM8u7vfP90+W1XdpWeqw7lKGzvzGpPBLGO43Cp7vm0ukr8Mq3y950jy4enM6WKiZO6h8Uly2SWNktiT45MsK2FzSI2Zp2+R5Q2fu1fG8Mv7ZlcZmll/n7r71VX1noyD1UpyxNSzZnbd/YraNflosqQTit19zKZFb50annN6dVX9YUYPi8UGwWw1r7v7HFV1qYyG9MOm9/pj3X27uWJO/jijZ+G9Mj5Tr8q8PQy3muX7ZEvomfXf099pM28P8yTLH/65yUomnUvyxBrlm/40o5fumZL82RLirsLZM4YQL44E6czYO2waHXG+rRLXSTJn4npyleyax+MKNeM8HlX1D919vz11QtjuY6l9/D6dmHGC8W+6e1vn4JnzpPePopdfy/aTNcqzXCi7T94+d7L+lhnlwe7S3V+sqp9J8oiZY35vOpn5iRpzL3wuY2LOOdwzyQczOq98Pksuj7nsdu0aHFcsfWLMyeszRuj9cIo323xkNV7cQzJ6yFbGqL2TMuYgmG3esBWPXHt9Vd0q43uUjBMU/7mMwN39xqr66Yz9bSd5d3d/ccZ4S32fV/V5WiY9r1dk+uK8MmNI/m7mPIO60et707L3bpzRPJBMwz8fmVHf9MsZJVI+0t2XWumGzWganvihjeHLVXXmjPIa75wh1iqSBhuxl3rmdIr52Oz9IG6WM/Kb4h6UMZP7p7v7tnPE2xT75hnJkbd09+9OQ4of0d0HxNCjRVV1vozfiMWG3uy1p6fYv5hTNjJnrd9eVWdfuHlQRk3xx3T3xWeMudVErj1nz9EaZbmunlFz85cyTny9o7vnHsqcGqVofqYXyuDMGGvLHlkbltUza9rndHf/7xJivS67RjltnAzp7r7RzHHf2d2/sDAy5ZAk75mrIV9V5+/u4/dw32/2NFknP7mqenGS2/Vyh4vvcR6PGY8rrtjdxyzrWGofv0+HZJyQP3KutkitcLLTaaTEr2ScvPxiRu3RO3b3ZWeM+baM5NsxWUj2dfcL5oq5KlV15YySPmdN8pcZo1//bqZ2z08luXlGkv6kjBPxL+j5J4DeiL/Udu2qjyuq6t+S/H1GuberZnRquVJ332qmeIck+euMuZw+k3FsfIGM0jQPmmM0TFX9fpIbJrl7d39qWnaRjPrxr+juR213zFVb6I28Mbn3Qdn9GG7OXt93TfLnSV6Xkdy9VsaEoE/d5jiX6O6PVtWWFRa6+z3bGW8h7gH/eZK83mGmnt6X7d6tDuf7D8SEblW9L6PXzmumBuZ1kty6u+8+c9xl1rfbHPu9Sa6w8P89KMnRPUN5mlooe1NVLzgQE5qLah91+3qmGc83xT0pI3H91jlirdIqe3hU1d9lNEY+lF0HU72MnvzLTlosxP1UxvtdGZ+rT2UcwM06GdqyTfu8t0x/b9pTEnCGuL+V0ePstN194aq6XMb7u4zRIUtXVZfOKPWzcVLkK0lu390fmjHmYuKtMib/ufXcxzM1Jr/5Rsbw/9/LKOHx4Z6pDEBVfSzJ9XtTyZuqulOSP+3ui84RdxWq6o+6++F7Olm8hN/FVQ0X/0hWOI/HOqiqv+juh8y07udnTHb6O1mY7LS7j5gj3qbYF8xINJ4mo/boWZI8rrs/OWPMU3RUmlOtcBLdjRMxm5bNflJv6vBw64x69X/c3c/ax1O2I+ZK2rWrUlXnyJgY81eyawTbET3TxNBV9agkZ07y+wudwA7LGGl8Qnffb4aY701yvd402rNGyYdXHYidC1dpOp76xY3P0HRC6m3b3XGnqp7Y3XevMb/QZt3zzS90wH+elA1Zgao6qrtvsUWyZhkTL7wyyVFVtViH8xUzxlul/+vur1bVQVV1UHe/fkpSze0fc8r6docvIW4yTkid/JnqMbR6ru/54jiupdTcXOUB8kZyuqou3d0fnCvOnuIu04oSCKsofbPhxkku3qup/7+SyUe7+8LLjJckNSY9u39Gb+S71yjhcfHufulcMTf2p1V1xl5uffqHZAxLfMO0HcdW1YXmCrbFb+LJd2U59fWemOT+3f36aXuuneRJSX5xroA9hn9eLiMhdYuMEzBPmCvegsVJ5+6e5D+7e7aSMBkJr1dX1Q27+xNJUlUPzHjdW/acPRW7R40JC4/JXk5mzug/s6Thy5t8MMlPZ/TKXZqFk5i7mXM0zJ7MlbierGyy04Xeqd9N8hfLiJnkpdPvxcuWEaxXO4nuk6rqDj1NVF+jHMHvJ5kteT31prx1kusleXnG79UyrKpduxK9/IkxfyPJxTa1o79VVffKOPl1vxlinmZzonGK+z81/2T1K1NVl8kpR5wuY9LI4zMmsN3w7YwJx7fbE5Oku68zw7r35oD/PEler8bGmf5VJGv+OKOxtZQ6nCv2jao6U0bN3GdX1ZczehjOrpdf327DcVV134zhIcnoEXbcXh7/k+g9XJ/Nig+QNzyhqk6b5OlJ/rW7vzFHkL30RF7GSa6PTJdHzxhjNwsNvFTVuTPKASRjQrIvzxz+uIxeUatIXq8kaZGspFzJ0zIaeRsJzeMzTvLNlryuqqslWeps9ZOTuvubtXutxtms+DcxSc64kbhOku5+Q1WdcY5AVXWxjBPEt86oi/y8jBO3szYSqupGSc7f3f+UkTC5W5JzJrliVX2ju/9tjrjd/bKqOjHJy6vqxknumvH7eM1e0nD1JXpsRi+382T8X5/T3ccuK/gqThZPVjWPx+IEWafPKIlw9j089tRsY7j/N6ZRIl/M2PfNZpWjyTLamQ+qqu8n+X6WdBKzqi6a5PjuPnE6gXmZJM+c6zh5crMk/1ZVt8kYfXP7JL86R6Cq+ouMtvtHkjw3yQO7eyntysnK2rXLVFV/vpe7u7v/cqbQvVVHku7+QVXN1c79/o9536lWVT0147dht9GumXdOi/tPVz+X5J1V9R9TzBtllJ7bbk+avqvPyTiO+ci+nrBNDvjPk7IhO1iNmqfn72nyxgPN1HD+bkYtpdtkDNV79lzDjRbiLr2+3ULscyV5TMawsk7y2iT3myP5V1U/yBhWW0nOkOSEjbuynIPkg5OcO7sn3pZSg3vqMXrnjIbeu5I8vbtftc0x1qKG7bJV1S0yyi28IeOz9EtJHjBXYmiK+YIkl834viwmDmYdKj7Ffn1GHfOlJi1WUa6kptnEa2Gehap635y/jbW62eqfkvF5+pMkN82o1Xia7r7nnHFXpapelOQ9GaVDkuS2GbUpbzxDrB9m1HO9S09D76vquLl7i049gm/V3Z+dbh+bsa89U5Kndfd1Z45/jST/nuRtSW7R3d+bM94qTfu/W01/p8+uBuAnZo57eJK/SXLJ7F4bee7P1tLn8djLtrxlo6PADOv+5Yw5B07Y54O3N+5dk7wgI2HytIzv7J9392wjNXbiMdz0m3iljBMDr8yYWPbi3X3DmeNeLOO38bNJbtzds0ywN+17jsuuCfw2kijL6FSysnbtFHuZc3j8wRaLz5gx4umnuvtMM8X99yQv3NyJo6pum7HP3fbj8oW29CnuSnL67j4gessuqqoPd/cllxxzryN7unvbR8VU1cUzjmFumZE4fk6S5875278TPk+S1yuwyuG9VfWGjEkiD8lIWvxPkjd29/338rRTlar62STn7k11gavqmkk+193/NXP8pde322mq6vcyhuV/KbvXKJ595uuFbTg4o9zEY5J8K+P7+6A5hj0tuydyjUmr9mjOxGqNmn7X23iNNep0vWbmBOeW9cyX0QtvVUmLWkGN1WkEynWTvLW7rzD10npOd19lxpi7Ta43LZs1YT7FODTJgzN6gFVGQ/4vD9SEY1WdLWNI/DUyXu+bMiZg2/aewVV1k4wGwS9mlD17bpIn98ylcKrq3d195YXb/9jd95muv6O7rzpT3I1jxkpyuoxepD/I8krCrFRVXT7JU5NcprsPnjnWWzKOLR6V5DeT3CmjrTRnSYuVqd0nkzooI/F4r7l+H6vqmRk1xb+acQLqzRkTQh9oIwh2M7ULDu/u10xJwEN6qqk7U7zKSG5euLv/sqoukOQ83T1HD8PFuO+Z9u0PSPK97n7s4r53m2Nt7tl+riTfzNQJYI72wKpOSKxBu/Y3M0bELH0OjxqTQB+Rkbg+Kskj52oD1ahj/sKMEwQbpauunNFB6ybd/bk54u40U+eOR3b3h1e4DUstJTiN+rxVRom7L3b31ZcV+0CjbMgK9GqH956lR/2mu2b0FHpIjQmtDiT/kORBWyw/YbrvN+cM3iuob1crnuRoBY7I6M0xe2+DzWrU6bpTkl/PmNTpN7v7PVV13iRvzzYPe9qiJ/Jjq2rWnshJrpbRg+U5Sd45xV2WgzYdmH41o1E9m2UkqfcSe+k96yZLK1dSVf+Y8Vk6MiPZeIGqenaSqye548zhP1ujPErXKPdz3+wqizObqWfhg6e/A96UfFrKfqa7X5TkRVMvtBtnnCQ+d1U9PsmLtnsUzIKzbdqO+yzcPOdMMVd9zLgSNWoz3iCjsXfdJG/Mco6nztDdr62qmo7ljqyqN2cktGdTVb+d5O8yEnCV5Z2YeOTC9ZOSfDqjcT2L7r59kkzHSzdL8k9JzpuZ2qMLQ8X3tD1/P0fcTdtwt4xyjWfPGO10/oza/HOO1HhcRseOX07yl0n+N+O9vvLenrQN/q+qbp3kDtnV1pqrp9/SS2+usLf8P2SF7dqMY7elzeGRnDw6/P4ZJ2GekeQKc5/kmpLTvzCNELlUxu/wy7v7tXPG3YGekeTtVfXFjJNNSxm5kKymlGBVHZSxbz93xgiC/5kr1k4geb0GplIPi8MT5yx9cEhVnSfj4PRAbVRfqLcohdLdR8+5s92iF8Cm8LP29Ft6jeIV+2xGD4tV+MeMicgetDg0sbs/X1V/OkO8Bye58uaeyEnmTF7/dMZENLfOmBTsPzN6yH5oxpgbXlFVr8xIdiZjuNWskw5V1dUzDs4vmLFf3DiQmm2o+KpG4FTVS6a4Z87yaqx+Irvq2L4u46TPezNmjT/FxCLb7J4Zs9WfL6PG9quS3HvmmBvDmP8wp6wpPssM46uyylEaU6+ZZ2fU/jx7RhmnP8n4H8/hnVV1t+5+0uLCqrpH5qmZuONU1cZ+59cz3tPnJrn7EntIfW9qaH6iqu6TUR/zXEuI+/CME+HLqouZZPmTSU3D738pyc8n+UrG8dSbZwy5Did+7p2R+HtnknT3J6Z235x+YeoB/d4p5tenk7dzu1PGPvdh3f2p/9/enYdLVlXnH/++3YAgIIrNz0gMs6jMMkS6EQdwiIqKOLaIBlFREhtQiXGItJpEI0NAUIQICk7IIApRCCqDMigy0ypiBBERFRQUwaDdvL8/9ilu9eV2t93UObtu1ft5nvvcW6du19rdFFV11ll7LUkbAp9tI5Dtm5v/V691y23AhkCV89o+nc7wkHQIsAdl6N2Wtv/QSeCG7fMon1WjHScAe1GGXt+/jN8dtCOA51JaGmH7mmYHw8BJ2pnyeWZ3SsHQycCBtmvlL0ZC2oZUJOlFlKqHdSltJtYHfmh78xZjvhz4F8o2vf0kbQQcYvulbcXsmqT/tb3J8t43gLhTbScTpcri3W6559s46Kui2Rx4AiWp2p94a72KZtJ6HgX8zVQfKgcY4zrbW/bdngFc03+sTZIeRnnzPYSyTfColuI8sC2yqULrtR+4k9LTr7VtkZKup1RvXsFE/2dqVPa3bUltSnrarATXg/vYfh74ou0b2opZS9P+5hM8+Dl1RbVFtUDS7Sxll0bFnQUD1yScvkx5z7myObwdpZXH7rZ/VWlpI0NlBsDngdNt/7ZC/B0oxQCPpFSsrgV8xPZ3Wo57cY1txJLWolSV907eL6S8z7dyci3pDuAnlNfG823/tI04U8Rde/LzSdKGtm/qIPZiraskrQRc2WaVocqshznA95ok9jrAuW2071jKGlr/fNzE+RxlcGInM29qqHVe2xej0xkeKr3F76PsBulPVI1Fq6xRJ+m8WoUck1+Pm2MDbyUo6RbgZ5SE9Sn5fDg4SV5X1Jzc7kLp5/pkSc8E5tp+U+WlTWuSvgCcN0V11D7Ac2y/soM1bEOpWH0FcBPlROzoFuNVq37rkioMXJhiDRfQYd/4pgJhKxavRL7O9j+1Ea8v7sMo1W9zKdWjZwInuKWeb5L+m3KR59pJx7cHDrbd2rbI3oeZth5/GDUVUbe56cGs0ofzMR0mE1rtY6t60+p78a+wvV2bMYaBSu//XrXsVnS7S6OKvi3FAN9vqrQiVpikIyk7nr7M4hfkBz5DY1Lc0ykVYb3WWXsBW9veo8WYm1OS5U8FHg/8yPZebcVrYl4MPM/275vbTwJO7aJiV9JHgLuA1wJvBfYDfmC7td2vkvakfFbclvLf9mXAe22f2lbMJu4FdDxXSdJ5lHYolzExqMy2X9xizE4Hj9Y+r9WYzfCIdkn6OOUC8Vl0+H7XxD4NOJyy62dHyoWY7W2/asBx1vcIDuUdBkleVyTpctvbN0nsJ9u+X9JlbmF4lcaoJ7LKcLszKJNde1Vu2wOrUAYu/LKluJtSKgrnUvr0fhF4h+2lDvgYUOyxqX6brKlEXqN3UtJBvF71zBsoVSUHS7q25Sqa/krkb7n0fG2NpBOBLYCzKZORF7QZr4m5YEknkpOrz1uI/WFgJqVfef8HqSuX+IemOUmXA3Ns/6m5vQplkGJrPTE1dR/bL9j+cguxqkyr74s/n7Kj6gwWf051Xk3ala52aUQMWu0CAEmfmjqsX99y3Kttb7OsYwOM9wjKrIOnU9qHzKIkAaccmjzAuC8A/olyQf4JwEnAnravbjNuE3sG5X2nP/H3SbdwAi7pcbZ/3vz8RMr7rChVs5vYPmvQMSfFr/H5uH83mSiflee2vIu508Gjtc5rozuqN/egc7Xe75rYsyitBJ9F+Tc+l9LCcKR22o7y8ynJ64okfYPSB+dDlA9wv6b0tp3TQqx/oQzK2pry5jc5uVltYFlbmkr2XjKs9eqoZpvTt4F9bP9vc+xGt9g3ty/2WFW/Sfo8pa/eIsoHubWAw20f0kHs6ygnIScC77H9vTY+nKvidPHmufxABUv/XbT05ldzW2SzVX0y19rW1oUlJC0GvnWuedyp+th+2R31sVWH0+r7Yk61Hd1dvB90retdGhGDNq4FAJIuBQ6yfVFzeyfgUNuzW4p3LXBR8/WtXqK1C5J2pySw1wT2sP3jDmOvA2C71UFdkn4EPHfyDipJr6d8Xt245fidfD6eIu42LL7b9UtdXDzVxODRdwDr2m51lliF89rejJQpjcqu3mEg6X+pMPcgRtMoP58ysLGCXlIKeDHwR0qv1T0pPa/f2lLYtShXmp4EXANcAlwMXDqqlWC2zwemSkq15aWUisLzJZ1DSdB0Mt3C9iLKxYlz+qrfLpA0qtVvm9n+fbM18mvAOylJ7NaT18AHKJUzFzUfzDeiDKQbtCOoNF3c9oy2Hnspvqeph6Htw0SlSSvc8dCqIXG7pBfZPhNA0ospA7Ta8G5KH9t3dPl+owrT6ntsb9hFnNom7dJ4fxe7NCJaUGVI8RDsinwzcJJK72soMyZaq4LuJTElrd7FxctJ/64CHgHcCLxVUqv/vpJE6Sf+j01sSVoEHGX7Ay2FPRD4uqTn95Lzkv6Z8h641HkXA9LV5+Ml7XZVF5/n1P3gUaDKee2hzfc9KK+RveGbc4GfdriOcfCrUUw0TkXSqpRiks0p828AaLPyWpVaCUraaYoitAcda8HIPp9SeV2B6vZ2XYWy1WgOMLv5usv2Zm3FHDeSVqdU1M+l9DQ/ETjD9rktxx2b6jdJ3we2oSTEjrZ9YVtVo7XUbKNRQ81tkU3sf6dUzjxP0mbAbNvHtxWzNkkbA5+jDAwWperwtb1dI9OdFp9W/zF3PK2+WcMcymvxA4UCtk/qeh1tqrFLI6JNXba/kfRC22dJmjJh3NWuyKadB01RwAG2j2gpzmzgeEqrt/UkbQ3sa3u/luL1/l1Xo7wOm7Jj74/Q7r+vpAOB5wNvcjMYsknmHgOcY/s/W4q7K3As5TzkDZR+0Lt1deG2K5V3u1YZPFqLpG/ZftqyjsXya9o7QLm41PncgxoknQpcT7lQ/AHKxbUf2t6/xZhVWglKutL2tss6NsB4I/98SvK6gppJqaa6Yjal59xsSsP862zv3VbMcdZU/r0ceGWbLQhUoUdxTZLmUaqtr6Ek7NcDPmt75w5irwO8kQcnpQZ6xbhmG42aut4W2cQ8G/gUZZvr1pJWAq4atQsEU5G0BuWzwN211zJIqjytXtJngI0pQ6sWNYfdQSVlRKyAcSoAWBpJP7O9XkuP/V1Km4UzbT+5ObbEc6IBxFsZ+Dfg9cDPKK//f0N5v3+37T+3EbeJfRXwbNt3TDq+DnBu7+/fUuynUpIWlwCvcMuD9WrsIJD0Ekrl9RzKztOTKb3EO9n1pAqDR2uR9EPgBbZvbG5vCHzN9pPqrmz609T9n3vcZjVyLZrojX+t7a2a1+n/aTNPMil+660Emwu1c4ADgP4LlY+gFGS1Umw3Ds+ntA2pY9Wl3LdaGwElHUfZnnE3pZ/fJZQewSN1JX7YNFvkj22+2rQXpfptU2Be2a0IjGj1m+2PAh/tO3Rzk/Tswlco1R7fYCIp1YZqbTRq6nJbpKSVbC8EZtk+RdK7mjUsbLb3jjSVIVabA6v2XjNa3M7cqUqtb/ptT2lvlAqBiCFXq/2NKg+KXIJW293ZvqXvMyq0+znqI8AawIa9C7RNlfmhlMr6A1qMvfLkxDWUvtdNsmbgJN1NSR4LeBhlYOOvmxYmbZ4L9LanX97S4z+Iy+DyM/p2ux4IPEbSMbS827V5Dq1Hafe5AaU15/1txRsCB1JaUd7Y3N4AeFO95YyOXvHgktpL1FlV63oXDe+StAXwS8pzqlUdtxJchfLesxJlzkLP7ykXcFsxDs+nJK/rqJGUWo/yQebHwK3Az4G7Woo1FDTCk1YnG4JETef6E299h7tIvD3c9js7iHMA5YP5nkzRRqOD+OPgMmBb4B5Jj6apGJK0I/C7mgtrm6RPAA8Hngl8kvJh6rKqixotCyhb9m6rvZCIWKZaBQCzWcqgyEravOB2S9NOyU0bw3lMJD7bsBuwaf9FxKY1ylso29YPaDH2n1bwvhVme81l/1Yrcc9qvnfS5mZS7HsoLdA+17fb9Z+BNls1XtT3dbQ7Gjxa67zW9jmSHg88sTl0ve37lvZnYrkdRTkfWdaxUXCcpEcB/0LZ4bQGsLSe1A/ZpFaCW7bdStBlyPOFkj5t++ZmDTMoLbN+32bsxsg+n9I2pIJavV2bK++bU7YxzKFUmfyWMrTx4DZi1qQRnrQ67paUeLO9Twex/xW4xPbX2o7VxOu8jca46Nu6ti3lTX0LStJxHeBlnjSXYJT0bdfrfV8D+JLt59Re2yiQdD6lL/9lLN5vrkYlZUQMIUkzmRgUuRXdDYrsVeg+6C5gNdutFDdJmkUZHv+sJta5wP62f9NSvBtsb7q89w0o9iIm5gEsdhewqu1Wqq9rGNIdBK1TR4NH++JVOa9tdgq8hdImBeAC4Ng22+6Mi1rtJcZNrVaCkj5PGYy8iJLzW4vS+eCQluKN/PMpldcV2P4VMGdSUuqrbSelmsqDBZLuolQV/o5SlfC3lInYo2ZkJ60Gc/oSb++XdBjQ1RCC/YF3S7qPsvWp1Te+LttojKF1JL2t+fkM4GuU/573UU6uRzZ5TTOwCrhX0rrAb4BOekWOifm1FxARw832Ikq/3nM0MSjyAkmtDoqsWKF7B2XLdld+IOm1njQoV9JrKJXXrbE9s83HHzLDuIOgNeobPAq0Pni0T63z2mOAlYGPN7f3ao69ocJaRk2V9hI19J1vTcn24W3FrrhDfbNmt8+elHPMd1KS2K0krxmD51OS1xV13Nt1HuVKzE6UhNvFwKXACcB1XayhK5qYtHq5pC8ygpNWg97wmc4Tb7VO+qIVMylv8pNPtB5eYS1d+29Jj6R8gLqSUonwyaorGiG2L2x2We3QHLps0ANhImL6m2JQ5Efp7mJ8JyQtbUu4bX+wpdD/AHxJ0uspCQNTXpNXI+3XBumvmNhB8Go62kFQ0RHAcyktD7B9jaSnLfVPPARDcF67w6SKzfMkXdNyzLHQfFa8iNLK4v2119Oy/vPnfWl/HtgwWLnZubA7pcXQnyW11vZiqnYloybJ6/GxAXAacKDtUe/B+cK+n+8F+rfBmxE7KRgnkg6gXHg5s0m8fYQKiTdJf00Z1PLAa6jtbw04xsPSU651t43KgMLl1ZcsOF3Sf1O2MY90n+8uSXoF5cLABZSLI0dJOsj2aVUXFhFDo9agyAqmaq2wOrAP8GigleS17VuBp0jahdI2UcDZtr/ZRrxxVWsHQU0dDx6tfV67SNLGtn8CIGkj2v37jhXbi5p+7SOtPzkvafcxSNZDSdD/FLgG+Jak9SlV0G379FRJctu7dBC7Vel5HSNrSZNWJx+L6UPSoZQdBE+ivBFc0nxd2lbPxCnW8B/AK4EfMPHhzYPu6SfpStvbSvqM7b0G+dhR9Hpe115HDZJeDpxj+25J76UM8fig7asqL20kNFVJz+5VW0taB/jGKPSbi4jBaPpw9hK7nfXhrEnSmpT2a/sApwCHZVfK9DfFDoIzgROaCwgjRdJpwOHA0cCOlMGj29t+Vctxq5zXStoV+BRwI+W1aX1g72YHeQxA0/7y8cCp9F3sG9Xd4r1z3NrrqEHSSrYXthxju76bqwIvBRba/qc243YhyesYWVO9MI7zi+UoaabUb09JZM9uvu6yvVkHsX8EbNV2VbSkBZTKzfcBB02+f1Q/0HRJ0tq2f1t7HTX0DWp8KvAh4FDg3bafUnlpI0HSdba37Ls9A7im/1hExLhoKgvfRul5fSJwpO07664qBmHSDoKTR3gHAdD94NG+uNXOa5uLE0+g/H2vz87QwZL0qSkO2/brO19MB8YlH9O0D/x3YF3bz5O0GTDb9vEV1nKh7ad3HXfQ0jYkRk7fpNX+YWxQJq2O0wCVUbYa5b/nWs3XL+iud/uNlMElbX9wezPlJO+RLL5lENL+ZiDGNXHd6O0aeAFwjO2vSJpfcT2j5hxJ/0MZYAVlt8bXKq4nIqIKSYcAewDHUXq7/qHykmKw9qJUi24KzOtrpzGSOwi6Hjw6JOe121Eq6lcCtpbE5EGoseJs7117DW2TdB0TO4w2kXRt7y7K68RWdVbWqk9Tdi28p7l9A/BFysDX1kxqQzOD8v/vX7UZsytJXscoGvlJq+NK0nGUvoV3UyaaXwIc3nH1zr3A1ZK+yeIDU+YNMojti4CLJF1e4wptjLxbJR1LqRz6j6aqptY07pEhaRPgMbYPaoYsPZXywfxS4HNVFxcRUcfbKZ+X3gu8Z9STm+PG9lh8dqg4eLTqea2kzwAbA1fT1y4RSPJ6QCQ9DjgK2Inyb3sRpZr/51UXNli71V5ABbNsnyLpXQC2F0rqol98b0CxgIXATZRWXdNe2obESJI0E/ii7SSrR4ikc4BZwAKaXtfAAnf4QibpdVMdt31iS/FWoVRh9yaZXwh8wvaf24gX40HSw4G/A66z/WNJj6VUxJ1beWnTWjP88t22r510fHvgYNuTd1FERETEkJP09ikOPzB41PYaLcdf3/bNbcZYQtwfApt1ea41biR9Hfg88Jnm0GuAPW0/u96q4qGSdAGl3/TXmzlWOwL/MQrtO2pJ8jpGlqTzRmGqaixOpWRnc8oWujmUPnu/pQxtPLijNawGrGf7Rx3E+iSlTUkvOb4XsMj2G9qOHaNL0sbAz23fJ+kZwFbASbbvqrmu6U7SAttbLOG+xfpgR0RExPRTY/CopPNZfLArAG2f60o6FZhn+7Y244wzSVfb3mZZx2J6aQYnfpSSq1gArAO8bHKBSwtxVwbewkTh2wXAsaNQ+Ja2ITHKrpJ0JmMyuXdcNFf+F0i6C/hd87Ub8LdA68lrSS+kDLdbBdhQ0jbAB2y/qKWQO9jeuu/2eZKuaSlWjI/Tge2bNhfHA2dSqj6eX3VV09+qS7lvtc5WEREREQM1xeDRbTtsXfiOvp9XpVR0LmwrmKSzKMnyNYEfSLqMxdsltnXeM47ukPQaJuakzAVaHQAa7ZF0AHAxcBXwdCaGnf6oowTyMZTCt483t/dqjk37wrckr2OUrU154e+/Ip1Bd9OYpHmUauudgD9T3hguBU6gu4GN8ymJ8gsAbF8tacMW4y2StLHtnwBI2oiJnnMRK+r+pvfaHsARto+SdFXtRY2A70l6o+3/6j8oaR9KD7qIiIiYZmoPHrU9+TPExZIubDHkoS0+dizu9cDRwH9SchWXNMdGjqRdgO/Yvrf2Wlr0OOBI4InAtZT/nhcDv6DsFm/byBa+pW1IREwbkg6neQOotX1N0ndtP0XSVbaf3By7tq0pyZJ2pUwqvpFy1XZ9YG/b57cRL8aDpO8CR1AmYL/Q9k1La3kRfxlJjwHOAP7ERLJ6e8pOjZfY/mWttUVERMSKkXQ/pfJ4IYu37+hk8GhT9d0zA9gO+KjtJ7QZd4p1zAReZTtDqGO5SToJ2JFSYPjt5uuiDncwdKaZW7U9pfBudvN1l+3NWo57JfDySYVvp9nets24XUjldYysMZncO1Zsv632GigtS14NzJT0eGAeJaHeCtvfbOL0thxdb/u+ZfyxiGXZmzII9N+axPWGwGcrr2nas/0rYI6kZ1J63AF81fZ5FZcVERERD4HtGZWXcAXlfFaUBPpNlJ7brZD0COAfgL+mtJb7enP7IOBqIMnrh0jS+5Zyt21/sLPFdMT2awEkrQu8DPgYsC6jmZdcDXgEsFbz9Qu62Sl+EHC+pMUK3zqI27pUXsfIyuTeaIOkh1OqVZ/THPof4F9t/1+9VUVERERERDx0kr4C3Elpz7gr8CjKLrL9bV9dcWkjQ9Lbpzi8OuWixKNtr9HxklrX9PbeGdgSuINSXPht25dWXdgASToO2By4G/gu8B1Kq5TOqsslPYwRLHxL8jpGVib3xiBJWpVSqboJ5arp8bZbG5QS0aammv9DwGb0DRm0vVG1RUVERETEg0haGXgL8LTm0AXAsW0NgJN0ne0tm59nUhKN69m+u414407SmsD+lMT1KcBhtn9dd1WDJ+kO4CfAJ4Dzbf+07ooGT9I5wCxgAWV39qXAAreceJW0A3BLr0WhpNdSBrveDMy33UW/7VbV3v4S0aY7JL1G0szm6zVkcm+suBMpfauuA55HBpnE9PYpyuTphcAzgZOY2KUSEREREcPjGEqf6483X9s1x9ryQFLc9iLgpiSuB0/S2pL+lTLYbyVgW9vvHMXENYDtWZRhlKsC/ybpMkkjdf5h+++AHZjIFbydMtD9XEnvbzH0sZSZO0h6GvBhyvnd7yiDZqe9VF7HyJK0HmVy72wmJvfub/vmqguLaWlSBcJKwGVdDD6Q9E3buy7rWMTykHSF7e0mPa+/bXvn2muLiIiIiAmSrrG99bKODTDeIuCe3k1K/9576WhA5TiQdAiwByWx+DHbf6i8pNY1vdR3Ap5OaR8yi9JS43VVF9aSZgbbTpShjbtR2sE8sqVYD7weSPoYcLvt+c3tkeg+MIqN0SMAsP0z4EW11xEjo78CYaGkVoM1bUoeDsyS9CjKh0Uogx/WbTV4jIP/kzQD+LGkfwRuBf5f5TVFRERExIMtkrSx7Z8ASNoIWNRWMNsz23rseMDbgfuA9wLv6Tu3HOULBBf1fR1t++eV1zNwkuZRktU7UfIHF1Nah5xAuwMbZ0paqWlruivwpr77RiLvOxJ/iYh+4zi5NzqxtaTfNz8LWK253dYHjH2BAyiJ6iuYSF7/njKZOeKhOIBycWQe8EFgF2Akqx4iIiIiprmDgPMl3Ug5J1gf2LvukuKhsD12LXxtbwUgaXXb9yzr96epDYDTgANt39Zh3C8AFzZ9xf8IfBtA0iaU1iHTXtqGxMgZx8m9MbokvdX2UbXXERERERERdUh6GPAESvL6etv3VV5SxHKRNBs4HljD9nqStgb2tb1f5aWNBEk7Ao8Fzu1dHJC0KeXf+8qqixuAVF7HyLF9WO/nvsm9ewMnA4ct6c9FDKn7JT3S9l0ATQuRubY/XndZMR1JOnNp99tOq6WIiIiIISBpB+AW27+0fZ+kbYCXAjdLmm/7t3VXGLFcjgCeC5wJYPuaZrhgDIDt70xx7IYaa2lDktcxkiStDbwN2BM4kTK59866q4pYIW+0/UCbENt3SnojZdJ4xPKaDdxC2Vr2XSba0URERETEcDkWeBZAk+T7MPBWYBvKoL+XVVtZxAqwfcuk2VGt9W6P0ZLkdYycSZN7txyHyb0x0mZIkpseT5JmAqtUXlNMX38FPBuYC7wa+CrwBdvfr7qqiIiIiJhsZl919SuB42yfDpwu6ep6y4pYIbdImgNY0iqU2Ts/rLymmCbS8zpGjqT7KZN7FwL9T/BRntwbI6q5GLMB8AnK8/nNlO2DU/V2j/iLNb0T5wKHAB9Ib/WIiIiI4SFpAbCN7YWSrgfeZPtbvftsb1F3hRF/OUmzgCMpuwkEnAvsb/s3VRcW00KS1xERQ0zSDGBfYFcm3uQ/aTtbrGKFNEnrF1AS1xtQ+s6dYPvWmuuKiIiIiAmS3gM8H7gDWI/SCtOSNgFOtL1T1QVGRHQkyeuIiIgxIelEYAvgbOBk2wsqLykiIiIilkDSjsBjgXNt39Mc2xRYw/aVVRcX8ReQ9L6l3G3bH+xsMTFtJXkdETGEJJ1i+xWSrmPx9jcA2N6qwrJimmvaKt3T3ExbpYiIiIiIaI2kqdpdrg7sAzza9hodLymmoSSvIyKGkKTH2r5N0vpT3W/75q7XFBEREREREbEiJK0J7E9JXJ8CHGb713VXFdPBSrUXEBERD9YkrmcCx9t+Vu31RERERERERCwvSWsDbwP2BE6k9G+/s+6qYjqZUXsBERExtWYo472S1qq9loiIiIiIiIjlIekQ4HvA3cCWtucncR3LK21DIiKGmKRTgB2BrzPRqxjb86otKiIiIiIiImIZmpk79wELycydWEFpGxIRMdy+2nz1y1XHiIiIiIiIGGq20/EhHrIkryMihtsjbR/Zf0DS/rUWExERERERERHRlVwBiYgYbq+b4tjfd72IiIiIiIiIiIiupfI6ImIISZoLvBrYUNKZfXc9AvhNnVVFRERERERERHQnyeuIiOF0CXAbMAs4rO/43cC1VVYUEREREREREdEh2Zn7FRExrCStDvzR9v2SNgWeCJxt+8+VlxYRERERERER0aokryMihpikK4CdgUcB3wEuB+61vWfVhUVEREREREREtCwDGyMihpts3wvsARxl+yXAZpXXFBERERERERHRuiSvIyKGmyTNBvYEvtocy7yCiIiIiIiIiBh5SV5HRAy3A4B3AWfY/r6kjYDz6y4pIiIiIiIiIqJ96XkdEREREREREREREUMnW88jIoaQpCNsHyDpLOBBVxltv6jCsiIiIiIiIiIiOpPkdUTEcPpM8/3QqquIiIiIiIiIiKgkbUMiIoacpHUAbN9eey0REREREREREV3JwMaIiCGkYr6kO4DrgRsk3S7pfbXXFhERERERERHRhSSvIyKG0wHATsAOth9t+1HAU4CdJB1YdWURERERERERER1I25CIiCEk6Srg2bbvmHR8HeBc20+us7KIiIiIiIiIiG6k8joiYjitPDlxDQ/0vV65wnoiIiIiIiIiIjqV5HVExHD60wreFxERERERERExEtI2JCJiCElaBNwz1V3AqrZTfR0RERERERERIy3J64iIiIiIiIiIiIgYOmkbEhERERERERERERFDJ8nriIiIiIiIiIiIiBg6SV5HRERERERERERExNBJ8joiIiIiYgVJermkH0m6T9KvJZ0naUZz336S5v+Fj7OZpPmSnrECa/h7SZb0jinus6QFy/uYERERERHDYKXaC4iIiIiImI4kzQI+C9wAvBlYG3gBoOZX9gM2B+b/BQ+3GXBw8/MFA1zmXOCuAT5eRERERERnUnkdEREREbFiNgJWAX4GnGH7MNu72F4k6dOUxHWv+vkCSetIukrSH5qvb0vaXNIGwKnNYx7c/P4zJP21pNMl3SnpF5I+3KvqXg5fAA5t1jG/eeyjJd0g6XZJL2/uW0XSoZJulXSXpFMlrfPQ/4kiIiIiIlZcktcRERERESvmh8BvgOcDv5F0uaQ3NPcdA/y8+Xku8AHgfuBLwP7Ah4GtgSOA25vvAKc3v/8DSlX3s4EjgTOBd1KquR+qZwEfA9Zq1gHwLuDtwFnNWp7X/B0iIiIiIqpJ25CIiIiIiBVg+25JcyhJ378DtgP+S9Ktts+W9DvgcbZPBpC0bvN7s5loLbKl7XskXQwcACywfbKkNYCnN793cF/Y5wBHP8SlH277OElvAR7fHNut+b7vpFgREREREdUkeR0RERERsQIkrQz82Pa+ze33A+8DtgDOBjzpj8wD5lCSz2cBxwNrNvdN/t2ea4D+QYy/G8DSf9t8X8jETkw1t3cDFjXHskszIiIiIqpK8joiIiIiYsVsDnxe0snAzcDTmuPXNd/vBJC0H/A9Jqqt1wB2Bh7HRDL6zub7zpJeBXwFuLB5zJ2BW4GnAtc3jzWV5zdDJAF+Yfujy/F3OYtSOf464BuUAZIbAucux2NERERERAxUktcRERERESvml5Rk8puBRwO/BubbPqe5/0jgCZT+0sdT2n88E9gdOA1YAPxN87sXAd+kJKt3aY6/htJ/+h+BlSlJ8ZOWsp5nNl9QKraXJ3n9IWB1Sr/t3YGbgGOX489HRERERAyc7CXtUIyIiIiIiIiIiIiIqCN97CIiIiIiIiIiIiJi6CR5HRERERERERERERFDJ8nriIiIiIiIiIiIiBg6SV5HRERERERERERExNBJ8joiIiIiIiIiIiIihk6S1xERERERERERERExdJK8joiIiIiIiIiIiIih8/8BOWQDHTlKZA8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(25,10))\n",
    "sns.barplot(x='State',y='Quantity',data = df_original, estimator=sum, palette = 'rocket', ci = None)\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('State Line', fontweight = 'bold', fontsize =10)\n",
    "plt.ylabel('Quantities', fontweight = 'bold', fontsize =10)\n",
    "plt.title('Quantities by State', fontweight = 'bold', fontsize =15)\n",
    "plt.savefig(\"Quantities by State.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6352d26",
   "metadata": {},
   "source": [
    "### 23. Profit Generated By each State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "b9fd9ebc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(25,8))\n",
    "sns.barplot(x='State',y='Profit',data = df_original, estimator=sum, palette = 'rocket', ci = None)\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('State Line', fontweight = 'bold', fontsize =10)\n",
    "plt.ylabel('Profit', fontweight = 'bold', fontsize =10)\n",
    "plt.title('Profit by State', fontweight = 'bold', fontsize =15)\n",
    "plt.savefig(\"Profit by State.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13fc3ebd",
   "metadata": {},
   "source": [
    "### 24. State Sales Across Months"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "30fd75f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x4320 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,60))\n",
    "sns.barplot(y='State',x='Sales',data = df_months, estimator=sum,hue = df_months['Month'], palette = 'rocket', ci = None)\n",
    "ax.set(facecolor = 'grey')\n",
    "plt.xlabel('Sales', fontweight = 'bold', fontsize =10)\n",
    "plt.ylabel('State', fontweight = 'bold', fontsize =10)\n",
    "plt.title('Branch Sales Across Months', fontweight = 'bold', fontsize =15)\n",
    "plt.savefig(\"State Sales Across Months.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "113c5ec3",
   "metadata": {},
   "source": [
    "# Model Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "c2444c15",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Order ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA-2017-100013</th>\n",
       "      <td>29.690</td>\n",
       "      <td>12.2162</td>\n",
       "      <td>06/11/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>ZC-21910</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>90045</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100055</th>\n",
       "      <td>152.590</td>\n",
       "      <td>46.1733</td>\n",
       "      <td>28/05/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MD-17860</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Laurel</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>20707</td>\n",
       "      <td>East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100097</th>\n",
       "      <td>1115.250</td>\n",
       "      <td>302.4705</td>\n",
       "      <td>26/11/2020</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>MN-17935</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10009</td>\n",
       "      <td>East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100111</th>\n",
       "      <td>7359.918</td>\n",
       "      <td>1571.7964</td>\n",
       "      <td>20/09/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>SV-20365</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>New York City</td>\n",
       "      <td>New York</td>\n",
       "      <td>10035</td>\n",
       "      <td>East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100160</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>CB-12025</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19134</td>\n",
       "      <td>East</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-168802</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>03/11/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JO-15145</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98103</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169320</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>23/07/2020</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>LH-16900</td>\n",
       "      <td>Consumer</td>\n",
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       "      <td>Elkhart</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>46514</td>\n",
       "      <td>Central</td>\n",
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       "    <tr>\n",
       "      <th>US-2017-169488</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>AA-10375</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Providence</td>\n",
       "      <td>Rhode Island</td>\n",
       "      <td>2908</td>\n",
       "      <td>East</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169502</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MG-17650</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53209</td>\n",
       "      <td>Central</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169551</th>\n",
       "      <td>1344.838</td>\n",
       "      <td>-62.2895</td>\n",
       "      <td>07/07/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>RL-19615</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19120</td>\n",
       "      <td>East</td>\n",
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       "<p>1687 rows × 11 columns</p>\n",
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      "text/plain": [
       "                   Sales     Profit  Order Date       Ship Mode Customer ID  \\\n",
       "Order ID                                                                      \n",
       "CA-2017-100013    29.690    12.2162  06/11/2020  Standard Class    ZC-21910   \n",
       "CA-2017-100055   152.590    46.1733  28/05/2020  Standard Class    MD-17860   \n",
       "CA-2017-100097  1115.250   302.4705  26/11/2020    Second Class    MN-17935   \n",
       "CA-2017-100111  7359.918  1571.7964  20/09/2020  Standard Class    SV-20365   \n",
       "CA-2017-100160    49.688    16.9641  07/09/2020  Standard Class    CB-12025   \n",
       "...                  ...        ...         ...             ...         ...   \n",
       "US-2017-168802    18.368     5.9696  03/11/2020  Standard Class    JO-15145   \n",
       "US-2017-169320   171.430    16.6721  23/07/2020    Second Class    LH-16900   \n",
       "US-2017-169488    56.860    26.5552  07/09/2020     First Class    AA-10375   \n",
       "US-2017-169502   113.410    32.4527  28/08/2020  Standard Class    MG-17650   \n",
       "US-2017-169551  1344.838   -62.2895  07/07/2020     First Class    RL-19615   \n",
       "\n",
       "                    Segment        Country           City         State  \\\n",
       "Order ID                                                                  \n",
       "CA-2017-100013     Consumer  United States    Los Angeles    California   \n",
       "CA-2017-100055    Corporate  United States         Laurel      Maryland   \n",
       "CA-2017-100097     Consumer  United States  New York City      New York   \n",
       "CA-2017-100111     Consumer  United States  New York City      New York   \n",
       "CA-2017-100160     Consumer  United States   Philadelphia  Pennsylvania   \n",
       "...                     ...            ...            ...           ...   \n",
       "US-2017-168802    Corporate  United States        Seattle    Washington   \n",
       "US-2017-169320     Consumer  United States        Elkhart       Indiana   \n",
       "US-2017-169488     Consumer  United States     Providence  Rhode Island   \n",
       "US-2017-169502  Home Office  United States      Milwaukee     Wisconsin   \n",
       "US-2017-169551     Consumer  United States   Philadelphia  Pennsylvania   \n",
       "\n",
       "                Postal Code   Region  \n",
       "Order ID                              \n",
       "CA-2017-100013        90045     West  \n",
       "CA-2017-100055        20707     East  \n",
       "CA-2017-100097        10009     East  \n",
       "CA-2017-100111        10035     East  \n",
       "CA-2017-100160        19134     East  \n",
       "...                     ...      ...  \n",
       "US-2017-168802        98103     West  \n",
       "US-2017-169320        46514  Central  \n",
       "US-2017-169488         2908     East  \n",
       "US-2017-169502        53209  Central  \n",
       "US-2017-169551        19120     East  \n",
       "\n",
       "[1687 rows x 11 columns]"
      ]
     },
     "execution_count": 198,
     "metadata": {},
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   "source": [
    "aggDf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "fc5b1163",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=aggDf"
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  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "67c5bce2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Order ID']=data.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "7fc9d778",
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   "outputs": [
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       "      <td>CB-12025</td>\n",
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       "      <td>Milwaukee</td>\n",
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      "text/plain": [
       "                   Sales     Profit  Order Date       Ship Mode Customer ID  \\\n",
       "Order ID                                                                      \n",
       "CA-2017-100013    29.690    12.2162  06/11/2020  Standard Class    ZC-21910   \n",
       "CA-2017-100055   152.590    46.1733  28/05/2020  Standard Class    MD-17860   \n",
       "CA-2017-100097  1115.250   302.4705  26/11/2020    Second Class    MN-17935   \n",
       "CA-2017-100111  7359.918  1571.7964  20/09/2020  Standard Class    SV-20365   \n",
       "CA-2017-100160    49.688    16.9641  07/09/2020  Standard Class    CB-12025   \n",
       "...                  ...        ...         ...             ...         ...   \n",
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       "\n",
       "                    Segment        Country           City         State  \\\n",
       "Order ID                                                                  \n",
       "CA-2017-100013     Consumer  United States    Los Angeles    California   \n",
       "CA-2017-100055    Corporate  United States         Laurel      Maryland   \n",
       "CA-2017-100097     Consumer  United States  New York City      New York   \n",
       "CA-2017-100111     Consumer  United States  New York City      New York   \n",
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       "...                     ...            ...            ...           ...   \n",
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       "US-2017-169502  Home Office  United States      Milwaukee     Wisconsin   \n",
       "US-2017-169551     Consumer  United States   Philadelphia  Pennsylvania   \n",
       "\n",
       "                Postal Code   Region        Order ID  \n",
       "Order ID                                              \n",
       "CA-2017-100013        90045     West  CA-2017-100013  \n",
       "CA-2017-100055        20707     East  CA-2017-100055  \n",
       "CA-2017-100097        10009     East  CA-2017-100097  \n",
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       "CA-2017-100160        19134     East  CA-2017-100160  \n",
       "...                     ...      ...             ...  \n",
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       "US-2017-169502        53209  Central  US-2017-169502  \n",
       "US-2017-169551        19120     East  US-2017-169551  \n",
       "\n",
       "[1687 rows x 12 columns]"
      ]
     },
     "execution_count": 209,
     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "d3bdd8df",
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   "outputs": [
    {
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>CB-12025</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19134</td>\n",
       "      <td>East</td>\n",
       "      <td>CA-2017-100160</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1682</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>03/11/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>JO-15145</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>United States</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "      <td>98103</td>\n",
       "      <td>West</td>\n",
       "      <td>US-2017-168802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1683</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>23/07/2020</td>\n",
       "      <td>Second Class</td>\n",
       "      <td>LH-16900</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Elkhart</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>46514</td>\n",
       "      <td>Central</td>\n",
       "      <td>US-2017-169320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1684</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>AA-10375</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Providence</td>\n",
       "      <td>Rhode Island</td>\n",
       "      <td>2908</td>\n",
       "      <td>East</td>\n",
       "      <td>US-2017-169488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>Standard Class</td>\n",
       "      <td>MG-17650</td>\n",
       "      <td>Home Office</td>\n",
       "      <td>United States</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>53209</td>\n",
       "      <td>Central</td>\n",
       "      <td>US-2017-169502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1686</th>\n",
       "      <td>1344.838</td>\n",
       "      <td>-62.2895</td>\n",
       "      <td>07/07/2020</td>\n",
       "      <td>First Class</td>\n",
       "      <td>RL-19615</td>\n",
       "      <td>Consumer</td>\n",
       "      <td>United States</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>19120</td>\n",
       "      <td>East</td>\n",
       "      <td>US-2017-169551</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Sales     Profit  Order Date       Ship Mode Customer ID  \\\n",
       "0       29.690    12.2162  06/11/2020  Standard Class    ZC-21910   \n",
       "1      152.590    46.1733  28/05/2020  Standard Class    MD-17860   \n",
       "2     1115.250   302.4705  26/11/2020    Second Class    MN-17935   \n",
       "3     7359.918  1571.7964  20/09/2020  Standard Class    SV-20365   \n",
       "4       49.688    16.9641  07/09/2020  Standard Class    CB-12025   \n",
       "...        ...        ...         ...             ...         ...   \n",
       "1682    18.368     5.9696  03/11/2020  Standard Class    JO-15145   \n",
       "1683   171.430    16.6721  23/07/2020    Second Class    LH-16900   \n",
       "1684    56.860    26.5552  07/09/2020     First Class    AA-10375   \n",
       "1685   113.410    32.4527  28/08/2020  Standard Class    MG-17650   \n",
       "1686  1344.838   -62.2895  07/07/2020     First Class    RL-19615   \n",
       "\n",
       "          Segment        Country           City         State  Postal Code  \\\n",
       "0        Consumer  United States    Los Angeles    California        90045   \n",
       "1       Corporate  United States         Laurel      Maryland        20707   \n",
       "2        Consumer  United States  New York City      New York        10009   \n",
       "3        Consumer  United States  New York City      New York        10035   \n",
       "4        Consumer  United States   Philadelphia  Pennsylvania        19134   \n",
       "...           ...            ...            ...           ...          ...   \n",
       "1682    Corporate  United States        Seattle    Washington        98103   \n",
       "1683     Consumer  United States        Elkhart       Indiana        46514   \n",
       "1684     Consumer  United States     Providence  Rhode Island         2908   \n",
       "1685  Home Office  United States      Milwaukee     Wisconsin        53209   \n",
       "1686     Consumer  United States   Philadelphia  Pennsylvania        19120   \n",
       "\n",
       "       Region        Order ID  \n",
       "0        West  CA-2017-100013  \n",
       "1        East  CA-2017-100055  \n",
       "2        East  CA-2017-100097  \n",
       "3        East  CA-2017-100111  \n",
       "4        East  CA-2017-100160  \n",
       "...       ...             ...  \n",
       "1682     West  US-2017-168802  \n",
       "1683  Central  US-2017-169320  \n",
       "1684     East  US-2017-169488  \n",
       "1685  Central  US-2017-169502  \n",
       "1686     East  US-2017-169551  \n",
       "\n",
       "[1687 rows x 12 columns]"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "034585c6",
   "metadata": {},
   "source": [
    "##### Transforming Catagorical data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "ecf21e86",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_1=list(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "31eb0ffc",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_cate=[]\n",
    "for i in list_1:\n",
    "    if data[i].dtype=='object':\n",
    "        list_cate.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "1998eded",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Order Date',\n",
       " 'Ship Mode',\n",
       " 'Customer ID',\n",
       " 'Segment',\n",
       " 'Country',\n",
       " 'City',\n",
       " 'State',\n",
       " 'Region',\n",
       " 'Order ID']"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_cate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "53f24567",
   "metadata": {},
   "outputs": [],
   "source": [
    "le=LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "628b8fb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in list_cate:\n",
    "    data[i]=le.fit_transform(data[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "c8cd82b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sales</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Order Date</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
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       "    <tr>\n",
       "      <th>Order ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA-2017-100013</th>\n",
       "      <td>29.690</td>\n",
       "      <td>12.2162</td>\n",
       "      <td>62</td>\n",
       "      <td>3</td>\n",
       "      <td>691</td>\n",
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       "      <td>0</td>\n",
       "      <td>174</td>\n",
       "      <td>3</td>\n",
       "      <td>90045</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100055</th>\n",
       "      <td>152.590</td>\n",
       "      <td>46.1733</td>\n",
       "      <td>290</td>\n",
       "      <td>3</td>\n",
       "      <td>435</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>164</td>\n",
       "      <td>17</td>\n",
       "      <td>20707</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100097</th>\n",
       "      <td>1115.250</td>\n",
       "      <td>302.4705</td>\n",
       "      <td>274</td>\n",
       "      <td>2</td>\n",
       "      <td>464</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>10009</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100111</th>\n",
       "      <td>7359.918</td>\n",
       "      <td>1571.7964</td>\n",
       "      <td>206</td>\n",
       "      <td>3</td>\n",
       "      <td>627</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>10035</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100160</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>19134</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-168802</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>31</td>\n",
       "      <td>3</td>\n",
       "      <td>351</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>300</td>\n",
       "      <td>44</td>\n",
       "      <td>98103</td>\n",
       "      <td>3</td>\n",
       "      <td>1682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169320</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>237</td>\n",
       "      <td>2</td>\n",
       "      <td>405</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>85</td>\n",
       "      <td>12</td>\n",
       "      <td>46514</td>\n",
       "      <td>0</td>\n",
       "      <td>1683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169488</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>261</td>\n",
       "      <td>36</td>\n",
       "      <td>2908</td>\n",
       "      <td>1</td>\n",
       "      <td>1684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169502</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>292</td>\n",
       "      <td>3</td>\n",
       "      <td>440</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>46</td>\n",
       "      <td>53209</td>\n",
       "      <td>0</td>\n",
       "      <td>1685</td>\n",
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       "    <tr>\n",
       "      <th>US-2017-169551</th>\n",
       "      <td>1344.838</td>\n",
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       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>19120</td>\n",
       "      <td>1</td>\n",
       "      <td>1686</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Sales     Profit  Order Date  Ship Mode  Customer ID  \\\n",
       "Order ID                                                                  \n",
       "CA-2017-100013    29.690    12.2162          62          3          691   \n",
       "CA-2017-100055   152.590    46.1733         290          3          435   \n",
       "CA-2017-100097  1115.250   302.4705         274          2          464   \n",
       "CA-2017-100111  7359.918  1571.7964         206          3          627   \n",
       "CA-2017-100160    49.688    16.9641          70          3          114   \n",
       "...                  ...        ...         ...        ...          ...   \n",
       "US-2017-168802    18.368     5.9696          31          3          351   \n",
       "US-2017-169320   171.430    16.6721         237          2          405   \n",
       "US-2017-169488    56.860    26.5552          70          0            1   \n",
       "US-2017-169502   113.410    32.4527         292          3          440   \n",
       "US-2017-169551  1344.838   -62.2895          68          0          562   \n",
       "\n",
       "                Segment  Country  City  State  Postal Code  Region  Order ID  \n",
       "Order ID                                                                      \n",
       "CA-2017-100013        0        0   174      3        90045       3         0  \n",
       "CA-2017-100055        1        0   164     17        20707       1         1  \n",
       "CA-2017-100097        0        0   216     29        10009       1         2  \n",
       "CA-2017-100111        0        0   216     29        10035       1         3  \n",
       "CA-2017-100160        0        0   249     35        19134       1         4  \n",
       "...                 ...      ...   ...    ...          ...     ...       ...  \n",
       "US-2017-168802        1        0   300     44        98103       3      1682  \n",
       "US-2017-169320        0        0    85     12        46514       0      1683  \n",
       "US-2017-169488        0        0   261     36         2908       1      1684  \n",
       "US-2017-169502        2        0   196     46        53209       0      1685  \n",
       "US-2017-169551        0        0   249     35        19120       1      1686  \n",
       "\n",
       "[1687 rows x 12 columns]"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "0c9986e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA-2017-100013</th>\n",
       "      <td>29.690</td>\n",
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       "      <td>62</td>\n",
       "      <td>3</td>\n",
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       "      <td>152.590</td>\n",
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       "      <td>290</td>\n",
       "      <td>3</td>\n",
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       "      <td>164</td>\n",
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       "    <tr>\n",
       "      <th>CA-2017-100097</th>\n",
       "      <td>1115.250</td>\n",
       "      <td>302.4705</td>\n",
       "      <td>274</td>\n",
       "      <td>2</td>\n",
       "      <td>464</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100111</th>\n",
       "      <td>7359.918</td>\n",
       "      <td>1571.7964</td>\n",
       "      <td>206</td>\n",
       "      <td>3</td>\n",
       "      <td>627</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100160</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>4</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-168802</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>31</td>\n",
       "      <td>3</td>\n",
       "      <td>351</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>300</td>\n",
       "      <td>44</td>\n",
       "      <td>3</td>\n",
       "      <td>1682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169320</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>237</td>\n",
       "      <td>2</td>\n",
       "      <td>405</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>85</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169488</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>261</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>1684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169502</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>292</td>\n",
       "      <td>3</td>\n",
       "      <td>440</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>1685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169551</th>\n",
       "      <td>1344.838</td>\n",
       "      <td>-62.2895</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>1686</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Sales     Profit  Order Date  Ship Mode  Customer ID  \\\n",
       "Order ID                                                                  \n",
       "CA-2017-100013    29.690    12.2162          62          3          691   \n",
       "CA-2017-100055   152.590    46.1733         290          3          435   \n",
       "CA-2017-100097  1115.250   302.4705         274          2          464   \n",
       "CA-2017-100111  7359.918  1571.7964         206          3          627   \n",
       "CA-2017-100160    49.688    16.9641          70          3          114   \n",
       "...                  ...        ...         ...        ...          ...   \n",
       "US-2017-168802    18.368     5.9696          31          3          351   \n",
       "US-2017-169320   171.430    16.6721         237          2          405   \n",
       "US-2017-169488    56.860    26.5552          70          0            1   \n",
       "US-2017-169502   113.410    32.4527         292          3          440   \n",
       "US-2017-169551  1344.838   -62.2895          68          0          562   \n",
       "\n",
       "                Segment  Country  City  State  Region  Order ID  \n",
       "Order ID                                                         \n",
       "CA-2017-100013        0        0   174      3       3         0  \n",
       "CA-2017-100055        1        0   164     17       1         1  \n",
       "CA-2017-100097        0        0   216     29       1         2  \n",
       "CA-2017-100111        0        0   216     29       1         3  \n",
       "CA-2017-100160        0        0   249     35       1         4  \n",
       "...                 ...      ...   ...    ...     ...       ...  \n",
       "US-2017-168802        1        0   300     44       3      1682  \n",
       "US-2017-169320        0        0    85     12       0      1683  \n",
       "US-2017-169488        0        0   261     36       1      1684  \n",
       "US-2017-169502        2        0   196     46       0      1685  \n",
       "US-2017-169551        0        0   249     35       1      1686  \n",
       "\n",
       "[1687 rows x 11 columns]"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop('Postal Code' ,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "a90d4100",
   "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>Sales</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Ship Mode</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Segment</th>\n",
       "      <th>Country</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Region</th>\n",
       "      <th>Order ID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Order ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CA-2017-100013</th>\n",
       "      <td>29.690</td>\n",
       "      <td>12.2162</td>\n",
       "      <td>3</td>\n",
       "      <td>691</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>174</td>\n",
       "      <td>3</td>\n",
       "      <td>90045</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100055</th>\n",
       "      <td>152.590</td>\n",
       "      <td>46.1733</td>\n",
       "      <td>3</td>\n",
       "      <td>435</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>164</td>\n",
       "      <td>17</td>\n",
       "      <td>20707</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100097</th>\n",
       "      <td>1115.250</td>\n",
       "      <td>302.4705</td>\n",
       "      <td>2</td>\n",
       "      <td>464</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>10009</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100111</th>\n",
       "      <td>7359.918</td>\n",
       "      <td>1571.7964</td>\n",
       "      <td>3</td>\n",
       "      <td>627</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>29</td>\n",
       "      <td>10035</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CA-2017-100160</th>\n",
       "      <td>49.688</td>\n",
       "      <td>16.9641</td>\n",
       "      <td>3</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>19134</td>\n",
       "      <td>1</td>\n",
       "      <td>4</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-168802</th>\n",
       "      <td>18.368</td>\n",
       "      <td>5.9696</td>\n",
       "      <td>3</td>\n",
       "      <td>351</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>300</td>\n",
       "      <td>44</td>\n",
       "      <td>98103</td>\n",
       "      <td>3</td>\n",
       "      <td>1682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169320</th>\n",
       "      <td>171.430</td>\n",
       "      <td>16.6721</td>\n",
       "      <td>2</td>\n",
       "      <td>405</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>85</td>\n",
       "      <td>12</td>\n",
       "      <td>46514</td>\n",
       "      <td>0</td>\n",
       "      <td>1683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169488</th>\n",
       "      <td>56.860</td>\n",
       "      <td>26.5552</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>261</td>\n",
       "      <td>36</td>\n",
       "      <td>2908</td>\n",
       "      <td>1</td>\n",
       "      <td>1684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169502</th>\n",
       "      <td>113.410</td>\n",
       "      <td>32.4527</td>\n",
       "      <td>3</td>\n",
       "      <td>440</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>196</td>\n",
       "      <td>46</td>\n",
       "      <td>53209</td>\n",
       "      <td>0</td>\n",
       "      <td>1685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US-2017-169551</th>\n",
       "      <td>1344.838</td>\n",
       "      <td>-62.2895</td>\n",
       "      <td>0</td>\n",
       "      <td>562</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>249</td>\n",
       "      <td>35</td>\n",
       "      <td>19120</td>\n",
       "      <td>1</td>\n",
       "      <td>1686</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1687 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Sales     Profit  Ship Mode  Customer ID  Segment  Country  \\\n",
       "Order ID                                                                        \n",
       "CA-2017-100013    29.690    12.2162          3          691        0        0   \n",
       "CA-2017-100055   152.590    46.1733          3          435        1        0   \n",
       "CA-2017-100097  1115.250   302.4705          2          464        0        0   \n",
       "CA-2017-100111  7359.918  1571.7964          3          627        0        0   \n",
       "CA-2017-100160    49.688    16.9641          3          114        0        0   \n",
       "...                  ...        ...        ...          ...      ...      ...   \n",
       "US-2017-168802    18.368     5.9696          3          351        1        0   \n",
       "US-2017-169320   171.430    16.6721          2          405        0        0   \n",
       "US-2017-169488    56.860    26.5552          0            1        0        0   \n",
       "US-2017-169502   113.410    32.4527          3          440        2        0   \n",
       "US-2017-169551  1344.838   -62.2895          0          562        0        0   \n",
       "\n",
       "                City  State  Postal Code  Region  Order ID  \n",
       "Order ID                                                    \n",
       "CA-2017-100013   174      3        90045       3         0  \n",
       "CA-2017-100055   164     17        20707       1         1  \n",
       "CA-2017-100097   216     29        10009       1         2  \n",
       "CA-2017-100111   216     29        10035       1         3  \n",
       "CA-2017-100160   249     35        19134       1         4  \n",
       "...              ...    ...          ...     ...       ...  \n",
       "US-2017-168802   300     44        98103       3      1682  \n",
       "US-2017-169320    85     12        46514       0      1683  \n",
       "US-2017-169488   261     36         2908       1      1684  \n",
       "US-2017-169502   196     46        53209       0      1685  \n",
       "US-2017-169551   249     35        19120       1      1686  \n",
       "\n",
       "[1687 rows x 11 columns]"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop('Order Date' ,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "0b191da8",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=data['Segment']\n",
    "x=data.drop('Segment',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "fe890687",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,random_state=0,test_size=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b192567",
   "metadata": {},
   "source": [
    "# MODELS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b81fee0",
   "metadata": {},
   "source": [
    "#### 1. KNeighborsClassifier\n",
    "\n",
    "    By default, the KNeighborsClassifier looks for the 5 nearest neighbors. We must explicitly tell the classifier to use Euclidean distance for determining the proximity between neighboring points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "a2eb2cc2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(n_neighbors=7)"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn=KNeighborsClassifier(n_neighbors=7)\n",
    "\n",
    "knn.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "78fa05bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report is:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.51      0.82      0.63       167\n",
      "           1       0.44      0.24      0.31        99\n",
      "           2       0.12      0.03      0.05        72\n",
      "\n",
      "    accuracy                           0.48       338\n",
      "   macro avg       0.36      0.36      0.33       338\n",
      "weighted avg       0.41      0.48      0.41       338\n",
      "\n",
      "Confusion Matrix:\n",
      " [[137  20  10]\n",
      " [ 71  24   4]\n",
      " [ 59  11   2]]\n",
      "Training Score:\n",
      " 57.82060785767234\n"
     ]
    }
   ],
   "source": [
    "y_pred=knn.predict(x_test)\n",
    "\n",
    "print(\"Classification Report is:\\n\",classification_report(y_test,y_pred))\n",
    "print(\"Confusion Matrix:\\n\",confusion_matrix(y_test,y_pred))\n",
    "print(\"Training Score:\\n\",knn.score(x_train,y_train)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ecfc1e3",
   "metadata": {},
   "source": [
    "#### 2. SVC\n",
    "\n",
    "In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "e902b05b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svc = SVC()\n",
    "svc.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "8b83b404",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report is:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.49      1.00      0.66       167\n",
      "           1       0.00      0.00      0.00        99\n",
      "           2       0.00      0.00      0.00        72\n",
      "\n",
      "    accuracy                           0.49       338\n",
      "   macro avg       0.16      0.33      0.22       338\n",
      "weighted avg       0.24      0.49      0.33       338\n",
      "\n",
      "Confusion Matrix:\n",
      " [[167   0   0]\n",
      " [ 99   0   0]\n",
      " [ 72   0   0]]\n",
      "Training Score:\n",
      " 52.55744996293551\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "y_pred=svc.predict(x_test)\n",
    "\n",
    "print(\"Classification Report is:\\n\",classification_report(y_test,y_pred))\n",
    "print(\"Confusion Matrix:\\n\",confusion_matrix(y_test,y_pred))\n",
    "print(\"Training Score:\\n\",svc.score(x_train,y_train)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe295c5e",
   "metadata": {},
   "source": [
    "#### 3. Naive Bayes\n",
    "\n",
    "It is a classification technique based on Bayes' Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "c20863cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GaussianNB()"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gnb = GaussianNB()\n",
    "gnb.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "ce286015",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report is:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.50      0.98      0.66       167\n",
      "           1       0.00      0.00      0.00        99\n",
      "           2       0.40      0.06      0.10        72\n",
      "\n",
      "    accuracy                           0.49       338\n",
      "   macro avg       0.30      0.34      0.25       338\n",
      "weighted avg       0.33      0.49      0.35       338\n",
      "\n",
      "Confusion Matrix:\n",
      " [[163   0   4]\n",
      " [ 97   0   2]\n",
      " [ 68   0   4]]\n",
      "Training Score:\n",
      " 52.26093402520385\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "F:\\lareb\\a\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1245: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "y_pred=gnb.predict(x_test) \n",
    "\n",
    "print(\"Classification Report is:\\n\",classification_report(y_test,y_pred))\n",
    "print(\"Confusion Matrix:\\n\",confusion_matrix(y_test,y_pred))\n",
    "print(\"Training Score:\\n\",gnb.score(x_train,y_train)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf90ee43",
   "metadata": {},
   "source": [
    "#### 4. DECISION TREE CLASSIFIER\n",
    "\n",
    "Decision trees use multiple algorithms to decide to split a node into two or more sub-nodes. The creation of sub-nodes increases the homogeneity of resultant sub-nodes. ... The decision tree splits the nodes on all available variables and then selects the split which results in most homogeneous sub-nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "id": "9faa5395",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(criterion='entropy', max_depth=6, random_state=123)"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dtree = DecisionTreeClassifier(max_depth=6, random_state=123,criterion='entropy')\n",
    "\n",
    "dtree.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "465b7678",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report is:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.52      0.90      0.66       167\n",
      "           1       0.54      0.15      0.24        99\n",
      "           2       0.37      0.10      0.15        72\n",
      "\n",
      "    accuracy                           0.51       338\n",
      "   macro avg       0.47      0.38      0.35       338\n",
      "weighted avg       0.49      0.51      0.43       338\n",
      "\n",
      "Confusion Matrix:\n",
      " [[150   8   9]\n",
      " [ 81  15   3]\n",
      " [ 60   5   7]]\n",
      "Training Score:\n",
      " 60.489251297257226\n"
     ]
    }
   ],
   "source": [
    "y_pred=dtree.predict(x_test)\n",
    "\n",
    "print(\"Classification Report is:\\n\",classification_report(y_test,y_pred))\n",
    "print(\"Confusion Matrix:\\n\",confusion_matrix(y_test,y_pred))\n",
    "print(\"Training Score:\\n\",dtree.score(x_train,y_train)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a81d725",
   "metadata": {},
   "source": [
    "#### 5.Random Forest Classifier\n",
    "\n",
    "A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "0e4eed0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier()"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfc=RandomForestClassifier()\n",
    "rfc.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "417126ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report is:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.53      0.87      0.66       167\n",
      "           1       0.48      0.27      0.35        99\n",
      "           2       0.14      0.01      0.03        72\n",
      "\n",
      "    accuracy                           0.51       338\n",
      "   macro avg       0.39      0.39      0.34       338\n",
      "weighted avg       0.43      0.51      0.43       338\n",
      "\n",
      "Confusion Matrix:\n",
      " [[146  17   4]\n",
      " [ 70  27   2]\n",
      " [ 59  12   1]]\n",
      "Training Score:\n",
      " 100.0\n"
     ]
    }
   ],
   "source": [
    "y_pred=rfc.predict(x_test)\n",
    "\n",
    "print(\"Classification Report is:\\n\",classification_report(y_test,y_pred))\n",
    "print(\"Confusion Matrix:\\n\",confusion_matrix(y_test,y_pred))\n",
    "print(\"Training Score:\\n\",rfc.score(x_train,y_train)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0ab5213",
   "metadata": {},
   "source": [
    "### CONCLUSION :\n",
    "##### ACCURACIES OF DIFFERENT MODELS ARE:\n",
    "\n",
    "KNeighbors Classifier= 57.82 %\n",
    "\n",
    "SVC= 52.55 %\n",
    "\n",
    "Naiye Bayes=  52.26 %\n",
    "\n",
    "Decision Tree Classifier= 60.48 %\n",
    "\n",
    "Random Forest Classifier= 100 %\n",
    "\n",
    "We got a good accuracy of about 100 % using Random Forest Classifier and Decision Tree Classifier is quite well for the given dataset.\n",
    "\n",
    "The accuracy of other models can be increased further by HyperTuning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1bc263d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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