Product sales data analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "787649f3",
   "metadata": {},
   "source": [
    "### Importing the libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "796c87a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4a225bf",
   "metadata": {},
   "source": [
    "### Importing the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a57f00a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(113036, 18)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"FreeCodeCamp-Pandas-Real-Life-Example-master//data//sales_data.csv\")\n",
    "df = pd.DataFrame(data)\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "05d02cdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 113036 entries, 0 to 113035\n",
      "Data columns (total 18 columns):\n",
      " #   Column            Non-Null Count   Dtype \n",
      "---  ------            --------------   ----- \n",
      " 0   Date              113036 non-null  object\n",
      " 1   Day               113036 non-null  int64 \n",
      " 2   Month             113036 non-null  object\n",
      " 3   Year              113036 non-null  int64 \n",
      " 4   Customer_Age      113036 non-null  int64 \n",
      " 5   Age_Group         113036 non-null  object\n",
      " 6   Customer_Gender   113036 non-null  object\n",
      " 7   Country           113036 non-null  object\n",
      " 8   State             113036 non-null  object\n",
      " 9   Product_Category  113036 non-null  object\n",
      " 10  Sub_Category      113036 non-null  object\n",
      " 11  Product           113036 non-null  object\n",
      " 12  Order_Quantity    113036 non-null  int64 \n",
      " 13  Unit_Cost         113036 non-null  int64 \n",
      " 14  Unit_Price        113036 non-null  int64 \n",
      " 15  Profit            113036 non-null  int64 \n",
      " 16  Cost              113036 non-null  int64 \n",
      " 17  Revenue           113036 non-null  int64 \n",
      "dtypes: int64(9), object(9)\n",
      "memory usage: 15.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1e1bdcaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2013</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2015</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2014</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1366</td>\n",
       "      <td>1035</td>\n",
       "      <td>2401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2016</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>20</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1188</td>\n",
       "      <td>900</td>\n",
       "      <td>2088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2014</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>238</td>\n",
       "      <td>180</td>\n",
       "      <td>418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Day     Month  Year  Customer_Age       Age_Group  \\\n",
       "0  2013-11-26   26  November  2013            19     Youth (<25)   \n",
       "1  2015-11-26   26  November  2015            19     Youth (<25)   \n",
       "2  2014-03-23   23     March  2014            49  Adults (35-64)   \n",
       "3  2016-03-23   23     March  2016            49  Adults (35-64)   \n",
       "4  2014-05-15   15       May  2014            47  Adults (35-64)   \n",
       "\n",
       "  Customer_Gender    Country             State Product_Category Sub_Category  \\\n",
       "0               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "1               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "2               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "3               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "4               F  Australia   New South Wales      Accessories   Bike Racks   \n",
       "\n",
       "               Product  Order_Quantity  Unit_Cost  Unit_Price  Profit  Cost  \\\n",
       "0  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "1  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "2  Hitch Rack - 4-Bike              23         45         120    1366  1035   \n",
       "3  Hitch Rack - 4-Bike              20         45         120    1188   900   \n",
       "4  Hitch Rack - 4-Bike               4         45         120     238   180   \n",
       "\n",
       "   Revenue  \n",
       "0      950  \n",
       "1      950  \n",
       "2     2401  \n",
       "3     2088  \n",
       "4      418  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7f90bc09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Day', 'Month', 'Year', 'Customer_Age', 'Age_Group',\n",
       "       'Customer_Gender', 'Country', 'State', 'Product_Category',\n",
       "       'Sub_Category', 'Product', 'Order_Quantity', 'Unit_Cost', 'Unit_Price',\n",
       "       'Profit', 'Cost', 'Revenue'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f3a3655",
   "metadata": {},
   "source": [
    "### Date column is not required if day,month and year are already present"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f02f03cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2013</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2015</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2014</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1366</td>\n",
       "      <td>1035</td>\n",
       "      <td>2401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2016</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>20</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1188</td>\n",
       "      <td>900</td>\n",
       "      <td>2088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2014</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>238</td>\n",
       "      <td>180</td>\n",
       "      <td>418</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "         Date  Day     Month  Year  Customer_Age       Age_Group  \\\n",
       "0  2013-11-26   26  November  2013            19     Youth (<25)   \n",
       "1  2015-11-26   26  November  2015            19     Youth (<25)   \n",
       "2  2014-03-23   23     March  2014            49  Adults (35-64)   \n",
       "3  2016-03-23   23     March  2016            49  Adults (35-64)   \n",
       "4  2014-05-15   15       May  2014            47  Adults (35-64)   \n",
       "\n",
       "  Customer_Gender    Country             State Product_Category Sub_Category  \\\n",
       "0               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "1               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "2               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "3               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "4               F  Australia   New South Wales      Accessories   Bike Racks   \n",
       "\n",
       "               Product  Order_Quantity  Unit_Cost  Unit_Price  Profit  Cost  \\\n",
       "0  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "1  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "2  Hitch Rack - 4-Bike              23         45         120    1366  1035   \n",
       "3  Hitch Rack - 4-Bike              20         45         120    1188   900   \n",
       "4  Hitch Rack - 4-Bike               4         45         120     238   180   \n",
       "\n",
       "   Revenue  \n",
       "0      950  \n",
       "1      950  \n",
       "2     2401  \n",
       "3     2088  \n",
       "4      418  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df.drop(\"Date\",axis=1,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32b253f8",
   "metadata": {},
   "source": [
    "### Which product category got the maximum revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2661bf73",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Category\"] = df[\"Product_Category\"] + \",\" +df[\"Sub_Category\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ad85d1a6",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
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       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2013</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2015</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2014</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1366</td>\n",
       "      <td>1035</td>\n",
       "      <td>2401</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2016</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>20</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1188</td>\n",
       "      <td>900</td>\n",
       "      <td>2088</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2014</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>238</td>\n",
       "      <td>180</td>\n",
       "      <td>418</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Day     Month  Year  Customer_Age       Age_Group  \\\n",
       "0  2013-11-26   26  November  2013            19     Youth (<25)   \n",
       "1  2015-11-26   26  November  2015            19     Youth (<25)   \n",
       "2  2014-03-23   23     March  2014            49  Adults (35-64)   \n",
       "3  2016-03-23   23     March  2016            49  Adults (35-64)   \n",
       "4  2014-05-15   15       May  2014            47  Adults (35-64)   \n",
       "\n",
       "  Customer_Gender    Country             State Product_Category Sub_Category  \\\n",
       "0               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "1               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "2               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "3               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "4               F  Australia   New South Wales      Accessories   Bike Racks   \n",
       "\n",
       "               Product  Order_Quantity  Unit_Cost  Unit_Price  Profit  Cost  \\\n",
       "0  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "1  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "2  Hitch Rack - 4-Bike              23         45         120    1366  1035   \n",
       "3  Hitch Rack - 4-Bike              20         45         120    1188   900   \n",
       "4  Hitch Rack - 4-Bike               4         45         120     238   180   \n",
       "\n",
       "   Revenue                Category  \n",
       "0      950  Accessories,Bike Racks  \n",
       "1      950  Accessories,Bike Racks  \n",
       "2     2401  Accessories,Bike Racks  \n",
       "3     2088  Accessories,Bike Racks  \n",
       "4      418  Accessories,Bike Racks  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cc58cbfd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Category</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>Accessories,Bike Racks</th>\n",
       "      <td>16.212838</td>\n",
       "      <td>2014.537162</td>\n",
       "      <td>37.712838</td>\n",
       "      <td>8.008446</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>514.282095</td>\n",
       "      <td>360.380068</td>\n",
       "      <td>874.662162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Bike Stands</th>\n",
       "      <td>15.872807</td>\n",
       "      <td>2014.478070</td>\n",
       "      <td>36.622807</td>\n",
       "      <td>5.289474</td>\n",
       "      <td>58.877193</td>\n",
       "      <td>158.657895</td>\n",
       "      <td>442.839912</td>\n",
       "      <td>311.710526</td>\n",
       "      <td>754.550439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Bottles and Cages</th>\n",
       "      <td>15.428445</td>\n",
       "      <td>2014.587680</td>\n",
       "      <td>35.943185</td>\n",
       "      <td>15.225876</td>\n",
       "      <td>2.474175</td>\n",
       "      <td>6.434870</td>\n",
       "      <td>51.058075</td>\n",
       "      <td>37.703200</td>\n",
       "      <td>88.761275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Cleaners</th>\n",
       "      <td>15.845727</td>\n",
       "      <td>2014.574917</td>\n",
       "      <td>36.381798</td>\n",
       "      <td>15.301887</td>\n",
       "      <td>3.004440</td>\n",
       "      <td>8.001110</td>\n",
       "      <td>64.312431</td>\n",
       "      <td>46.021088</td>\n",
       "      <td>110.333518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Fenders</th>\n",
       "      <td>15.585317</td>\n",
       "      <td>2014.562004</td>\n",
       "      <td>36.763393</td>\n",
       "      <td>15.411210</td>\n",
       "      <td>7.995040</td>\n",
       "      <td>21.986111</td>\n",
       "      <td>185.742560</td>\n",
       "      <td>123.218998</td>\n",
       "      <td>308.961558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Helmets</th>\n",
       "      <td>15.771837</td>\n",
       "      <td>2014.564731</td>\n",
       "      <td>36.311235</td>\n",
       "      <td>14.937161</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>278.022948</td>\n",
       "      <td>194.183089</td>\n",
       "      <td>472.206037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Hydration Packs</th>\n",
       "      <td>15.685157</td>\n",
       "      <td>2014.542729</td>\n",
       "      <td>36.898051</td>\n",
       "      <td>14.928036</td>\n",
       "      <td>20.988006</td>\n",
       "      <td>54.970015</td>\n",
       "      <td>429.286357</td>\n",
       "      <td>313.146927</td>\n",
       "      <td>742.433283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accessories,Tires and Tubes</th>\n",
       "      <td>15.753942</td>\n",
       "      <td>2014.570180</td>\n",
       "      <td>35.904399</td>\n",
       "      <td>15.177177</td>\n",
       "      <td>3.751402</td>\n",
       "      <td>9.977148</td>\n",
       "      <td>80.534780</td>\n",
       "      <td>57.371981</td>\n",
       "      <td>137.906761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bikes,Mountain Bikes</th>\n",
       "      <td>15.652812</td>\n",
       "      <td>2014.042128</td>\n",
       "      <td>35.766885</td>\n",
       "      <td>1.354416</td>\n",
       "      <td>1080.580754</td>\n",
       "      <td>1973.944884</td>\n",
       "      <td>921.669641</td>\n",
       "      <td>1464.091145</td>\n",
       "      <td>2385.760786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bikes,Road Bikes</th>\n",
       "      <td>15.734028</td>\n",
       "      <td>2013.508712</td>\n",
       "      <td>34.872822</td>\n",
       "      <td>1.472152</td>\n",
       "      <td>1179.812956</td>\n",
       "      <td>1898.903202</td>\n",
       "      <td>750.474684</td>\n",
       "      <td>1733.744304</td>\n",
       "      <td>2484.218987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bikes,Touring Bikes</th>\n",
       "      <td>15.534884</td>\n",
       "      <td>2014.553813</td>\n",
       "      <td>36.072472</td>\n",
       "      <td>1.256896</td>\n",
       "      <td>1078.388318</td>\n",
       "      <td>1734.935100</td>\n",
       "      <td>616.532720</td>\n",
       "      <td>1356.303137</td>\n",
       "      <td>1972.835857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Caps</th>\n",
       "      <td>15.609454</td>\n",
       "      <td>2014.593850</td>\n",
       "      <td>35.355668</td>\n",
       "      <td>15.435521</td>\n",
       "      <td>6.997705</td>\n",
       "      <td>8.998164</td>\n",
       "      <td>17.879991</td>\n",
       "      <td>108.044057</td>\n",
       "      <td>125.924048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Gloves</th>\n",
       "      <td>15.877885</td>\n",
       "      <td>2014.567386</td>\n",
       "      <td>36.228593</td>\n",
       "      <td>14.883842</td>\n",
       "      <td>8.998511</td>\n",
       "      <td>23.997022</td>\n",
       "      <td>190.489203</td>\n",
       "      <td>133.940804</td>\n",
       "      <td>324.430007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Jerseys</th>\n",
       "      <td>15.422962</td>\n",
       "      <td>2014.549418</td>\n",
       "      <td>36.102829</td>\n",
       "      <td>14.663062</td>\n",
       "      <td>39.855574</td>\n",
       "      <td>51.855574</td>\n",
       "      <td>100.427288</td>\n",
       "      <td>584.055574</td>\n",
       "      <td>684.482862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Shorts</th>\n",
       "      <td>15.487179</td>\n",
       "      <td>2014.515050</td>\n",
       "      <td>37.651059</td>\n",
       "      <td>15.143813</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>576.556299</td>\n",
       "      <td>393.739130</td>\n",
       "      <td>970.295429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Socks</th>\n",
       "      <td>16.089127</td>\n",
       "      <td>2014.557932</td>\n",
       "      <td>35.689840</td>\n",
       "      <td>15.755793</td>\n",
       "      <td>3.081996</td>\n",
       "      <td>9.217469</td>\n",
       "      <td>83.040107</td>\n",
       "      <td>48.128342</td>\n",
       "      <td>131.168449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clothing,Vests</th>\n",
       "      <td>15.363071</td>\n",
       "      <td>2014.574689</td>\n",
       "      <td>36.890041</td>\n",
       "      <td>15.068465</td>\n",
       "      <td>27.024896</td>\n",
       "      <td>68.813278</td>\n",
       "      <td>538.164938</td>\n",
       "      <td>446.340249</td>\n",
       "      <td>984.505187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Day         Year  Customer_Age  \\\n",
       "Category                                                              \n",
       "Accessories,Bike Racks         16.212838  2014.537162     37.712838   \n",
       "Accessories,Bike Stands        15.872807  2014.478070     36.622807   \n",
       "Accessories,Bottles and Cages  15.428445  2014.587680     35.943185   \n",
       "Accessories,Cleaners           15.845727  2014.574917     36.381798   \n",
       "Accessories,Fenders            15.585317  2014.562004     36.763393   \n",
       "Accessories,Helmets            15.771837  2014.564731     36.311235   \n",
       "Accessories,Hydration Packs    15.685157  2014.542729     36.898051   \n",
       "Accessories,Tires and Tubes    15.753942  2014.570180     35.904399   \n",
       "Bikes,Mountain Bikes           15.652812  2014.042128     35.766885   \n",
       "Bikes,Road Bikes               15.734028  2013.508712     34.872822   \n",
       "Bikes,Touring Bikes            15.534884  2014.553813     36.072472   \n",
       "Clothing,Caps                  15.609454  2014.593850     35.355668   \n",
       "Clothing,Gloves                15.877885  2014.567386     36.228593   \n",
       "Clothing,Jerseys               15.422962  2014.549418     36.102829   \n",
       "Clothing,Shorts                15.487179  2014.515050     37.651059   \n",
       "Clothing,Socks                 16.089127  2014.557932     35.689840   \n",
       "Clothing,Vests                 15.363071  2014.574689     36.890041   \n",
       "\n",
       "                               Order_Quantity    Unit_Cost   Unit_Price  \\\n",
       "Category                                                                  \n",
       "Accessories,Bike Racks               8.008446    45.000000   120.000000   \n",
       "Accessories,Bike Stands              5.289474    58.877193   158.657895   \n",
       "Accessories,Bottles and Cages       15.225876     2.474175     6.434870   \n",
       "Accessories,Cleaners                15.301887     3.004440     8.001110   \n",
       "Accessories,Fenders                 15.411210     7.995040    21.986111   \n",
       "Accessories,Helmets                 14.937161    13.000000    35.000000   \n",
       "Accessories,Hydration Packs         14.928036    20.988006    54.970015   \n",
       "Accessories,Tires and Tubes         15.177177     3.751402     9.977148   \n",
       "Bikes,Mountain Bikes                 1.354416  1080.580754  1973.944884   \n",
       "Bikes,Road Bikes                     1.472152  1179.812956  1898.903202   \n",
       "Bikes,Touring Bikes                  1.256896  1078.388318  1734.935100   \n",
       "Clothing,Caps                       15.435521     6.997705     8.998164   \n",
       "Clothing,Gloves                     14.883842     8.998511    23.997022   \n",
       "Clothing,Jerseys                    14.663062    39.855574    51.855574   \n",
       "Clothing,Shorts                     15.143813    26.000000    70.000000   \n",
       "Clothing,Socks                      15.755793     3.081996     9.217469   \n",
       "Clothing,Vests                      15.068465    27.024896    68.813278   \n",
       "\n",
       "                                   Profit         Cost      Revenue  \n",
       "Category                                                             \n",
       "Accessories,Bike Racks         514.282095   360.380068   874.662162  \n",
       "Accessories,Bike Stands        442.839912   311.710526   754.550439  \n",
       "Accessories,Bottles and Cages   51.058075    37.703200    88.761275  \n",
       "Accessories,Cleaners            64.312431    46.021088   110.333518  \n",
       "Accessories,Fenders            185.742560   123.218998   308.961558  \n",
       "Accessories,Helmets            278.022948   194.183089   472.206037  \n",
       "Accessories,Hydration Packs    429.286357   313.146927   742.433283  \n",
       "Accessories,Tires and Tubes     80.534780    57.371981   137.906761  \n",
       "Bikes,Mountain Bikes           921.669641  1464.091145  2385.760786  \n",
       "Bikes,Road Bikes               750.474684  1733.744304  2484.218987  \n",
       "Bikes,Touring Bikes            616.532720  1356.303137  1972.835857  \n",
       "Clothing,Caps                   17.879991   108.044057   125.924048  \n",
       "Clothing,Gloves                190.489203   133.940804   324.430007  \n",
       "Clothing,Jerseys               100.427288   584.055574   684.482862  \n",
       "Clothing,Shorts                576.556299   393.739130   970.295429  \n",
       "Clothing,Socks                  83.040107    48.128342   131.168449  \n",
       "Clothing,Vests                 538.164938   446.340249   984.505187  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category = df.groupby(\"Category\").mean()\n",
    "category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ebfc7cc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BEAxGX8pC0ge7htaUhO0TRzjnZGAjYGFJdwMHABtJWp3kzroD+AiA7ZslnQr8BXgW2NP2c1nOXqTg+mTgONs39/3fBUEQBEXo1w21duX+XMDbgGuBYZWF7e17DP94hOd/Dfhaj/GzgbP7nGcQBEEwCvTrhvpE9VjSAqQ01iAIgmAWoO0O7ieA5UpOJAiCIBi/9Buz+A05bZakYFYBTh2tSQVBEATji35jFt+u3H8WuNP23aMwnyAIgmAc0m/M4tLRnkgQBEEwfum3kOCWkm6T9KikxyQ9Lumx0Z5cEARBMD7o1w31TeA9tm8ZzckEQRAE45N+s6HuD0URBEEw69KvZTFF0i+AM4GnO4O2fzUakwqCIAjGF/0qi/mAJ4GNK2MGQlkEQRDMAvSbDbXLaE8kCIIgGL/0mw21kqSLOv20Ja0q6YujO7UgCIJgvNBvgPtYYH/gvwC2byCVCw+CIAhmAfpVFnPbvqpr7NnSkwmCIAjGJ/0qi39KWp6htqpbkdqiBkEQBLMA/WZD7QkcA6ws6R7g78AOozarIAiCYFzRr7K40/bbJc0DTLL9+GhOKgiCIBhf9OuG+rukY4B1gX+P4nyCIAiCcUi/ymJl4EKSO+rvkg6XtMHoTSsIgiAYT/SlLGw/aftU21sCa5B2dEfZ8iAIglmEvtuqSnqzpCOBa4C5gG1GbVZBEATBuKLftqp3ANeRWqnua/uJ0ZxUEARBML7oNxtqVdvR7CgIgmAWpV831MujNlQQBMGsS9SGCoIgCGqJ2lBBEARBLVEbKgiCIKglakMFQRAEtfTbKe924IXaUKQWq9sBd47i3IIgCIJxwohuKEnzSdo/l/d4B0lJ7AxMIzblBUEQzDLUWRYnAQ8DfwZ2B74ACHif7amjO7UgCIJgvFCnLF5p+3UAkn5ECmovbfupUZ9ZEARBMG6oy4b6b+eO7eeAu/tVFJKOk/RAZyNfHltI0gWSbst/F8zjkvR9SdMk3SBpzco5O+fn3yZp52b/XhAEQVCCOmWxmqTH8u1xYNXOfUl15T9+Aryra2w/4CLbKwIX5WOATYAV820P4ChIygU4AHgDsA5wQEfBBEEQBDOOEZWF7cm258u3l9qerXJ/vppzLwMe6hreHDgh3z8B2KIyfqITVwALSFoceCdwge2HbD8MXMCLFVAQBEEwyvRdorwQi9nubOa7D1gs318CuKvyvLvz2HDjQRAEwQxkRiuLF7Bt8o7wEkjaQ9IUSVMefPDBUmKDIAgC+t/BXYr7JS1u+97sZnogj98DLFV53pJ57B5go67xS3oJtn0MaZc5a621VjElFARBMBYsu9/vWp13xyHvLjyTxIxWFmeRNvUdkv/+ujK+l6RTSMHsR7NCOQ/4eiWovTGp+m0QBEEx2l6YYfQuzuONUVMWkk4mWQULS7qblNV0CHCqpN1IpUI6u8DPBjYl7Qx/EtgFwPZDkg4Grs7PO8h2d9A8CIIgGGVGTVnY3n6Yh97W47kmFSvsJec44LiCUwuCIAgaMmYB7iAIgmDiEMoiCIIgqCWURRAEQVBLKIsgCIKgllAWQRAEQS0zep/FhGC8bYYJgiAYa8KyCIIgCGoJZREEQRDUEsoiCIIgqCWURRAEQVBLKIsgCIKgllAWQRAEQS2hLIIgCIJaQlkEQRAEtYSyCIIgCGqJHdyjSOwED4JgZiGURTDhiZaYQTD6hBsqCIIgqCWURRAEQVBLKIsgCIKgllAWQRAEQS0R4A6CYMISyQ0zjrAsgiAIglpCWQRBEAS1hLIIgiAIagllEQRBENQSyiIIgiCoJZRFEARBUEsoiyAIgqCWUBZBEARBLaEsgiAIglpCWQRBEAS1hLIIgiAIahkTZSHpDkk3SpoqaUoeW0jSBZJuy38XzOOS9H1J0yTdIGnNsZhzEATBrMxYWhZvsb267bXy8X7ARbZXBC7KxwCbACvm2x7AUTN8pkEQBLM448kNtTlwQr5/ArBFZfxEJ64AFpC0+BjMLwiCYJZlrJSFgfMlXSNpjzy2mO178/37gMXy/SWAuyrn3p3HpkPSHpKmSJry4IMPjta8gyAIZknGqp/FBrbvkbQocIGkv1YftG1JbiLQ9jHAMQBrrbVWo3ODIAiCkRkTy8L2PfnvA8AZwDrA/R33Uv77QH76PcBSldOXzGNBEATBDGKGWxaS5gEm2X48398YOAg4C9gZOCT//XU+5SxgL0mnAG8AHq24q4IJTHQ5C4KJw1i4oRYDzpDUef2f2z5X0tXAqZJ2A+4EtsnPPxvYFJgGPAnsMuOnHARBMGszw5WF7duB1XqM/wt4W49xA3vOgKkFQRAEwzCeUmeDIAiCcUooiyAIgqCWUBZBEARBLaEsgiAIglpCWQRBEAS1hLIIgiAIagllEQRBENQSyiIIgiCoJZRFEARBUMtYVZ0NgmAWJuqCTTxCWQSNiR96EMx6hBsqCIIgqCWURRAEQVBLKIsgCIKgllAWQRAEQS2hLIIgCIJaQlkEQRAEtYSyCIIgCGoJZREEQRDUEsoiCIIgqCWURRAEQVBLKIsgCIKgllAWQRAEQS2hLIIgCIJaQlkEQRAEtUSJ8iDIROn1YFBm5u9QKIsgCPqm7cVwvF8Ig3pCWcxCzMyrniAIRpeIWQRBEAS1hGUxAQjTPwiCsSYsiyAIgqCWUBZBEARBLaEsgiAIglomjLKQ9C5Jt0qaJmm/sZ5PEATBrMSEUBaSJgNHAJsAqwDbS1plbGcVBEEw6zAhlAWwDjDN9u22nwFOATYf4zkFQRDMMsj2WM+hFklbAe+y/eF8vBPwBtt7VZ6zB7BHPnwVcOsoTWdh4J8hZ8LIKSkr5MyackrKGm9yulnG9iK9Hphp9lnYPgY4ZrRfR9IU22uFnIkhZzzOKeRMLDnjcU4l/7d+mShuqHuApSrHS+axIAiCYAYwUZTF1cCKkpaTNAewHXDWGM8pCIJglmFCuKFsPytpL+A8YDJwnO2bx2g6pVxdIWfGyCkpK+TMmnJKyhpvcvpmQgS4gyAIgrFlorihgiAIgjEklEUQBEFQSyiLCYykSZLmG+t5BBOX+A4F/RLKogZJ35Q0n6TZJV0k6UFJO46hnJ9nOfMANwF/kbRvUzldMheUtOogMsYTkraW9NJ8/4uSfiVpzRZy9s7vtST9WNK1kjZuIWceSZPy/ZUkvVfS7C3krJ8/dyTtKOlQScu0kFP8O1SS8abAxtt8xopQFvVsbPsxYDPgDmAFoM0Pq5ScVbKcLYBzgOWAnZoKkXRJvmAsBFwLHCvp0BZyiijBLKvIRR74ku3HJW0AvB34MXBUCzm75vd6Y2BB0vt8SAs5lwFzSVoCOD/L+UkLOUcBT0paDfgM8DfgxBZyinyHoKhiLqLACir4UvMptUgs8n8NQiiLejorwHcDp9l+tKWcTpryoHJmz6vSLYCzbP8XaJPSNn++YGwJnGj7DaQLa1NKKUEod5F/Lv99N3CM7d8Bc7SQo/x3U+CknK6tEZ4/rBzbT5Le6yNtbw28poWcZ53SFzcHDrd9BPDSFnJKfYeg3GdWSoGVUvCl5lPq91Hq/2pNKIt6fiPpr8DrgYskLQI81ULObwvJ+SHpSzcPcFl2QzzWQs5skhYHtgF+2+L8DqWUKZS7yN8j6YfAtsDZkuak3Xf9Gknnk5TFeXkF/XwLOZK0HrAD0OmRO7mFnMcl7U+6UPwuu7Yau7Mo9x2Ccp9ZKQVWSsH3mk8bSv0+Sv1f7bEdtxFu+QNZCJicj+cBFmspq1vOywvNcbYW52wF3EBa6QK8Eji9hZxvAH8FriP9MBYBrmz5f/yWdCG7HVgAmBO4voWcuUmr+BXz8eKkFV5TOZOANYEF8vHLgFVbyHkzqeLA5yrv9fdbyHk58Glgw3y8NPDBsfoOFf7MPkkq4XN2/s0tA/yhhZzjSa6+2/L34KXANWM4n0NK/D5K/V+D3GJTXg2SjrO9a+V4XuDXtt/W5/lbjvS47V81nM9iwNeBV9jeRKmvx3q2f9xAxmTgk7a/2+S1e8iZBKxL+jE8avu57ON9qe37WsibG3gXcKPt27Ll8zrb5zeUs1v3+yHpENuNmmZJEskaeKXtgyQtTVLwVzWRU5E3t5M7qjXZCljR9oX5/Zps+/GGMgb+DlVkFfnMhpE9m+1nG54zCVgduN32I5JeBixh+4aGcpaz/ffKsYAVbN/WUI5IbqPq72Ne2/c3lFPk/xqIGamZJuINOJih1feCwJ+AXRqcf3y+/Q54GDg93x4CfttiPueQXEfX5+PZSD/UpnKuKvT+XFfwvT6pn7E+5JwN7FA5PgL4cQs5R+Vzb6l8/le3kLMe8BfgH/l4tc53qqGc3Ul10v6Wj1cELhqr71BF3pqklfgngDVbyliMFO84Jx+vAuzWQs7pJJfPpAG/i9f2GGtjoRzXdTxvy8/sRee0kTPILWIWNdj+EvBvSUeTzMDv2D6+wfm72N6FZIKuYvv9tt9PCnC28TcvbPtUsu/caeX13Min9ORySYdL2lDSmp1bCzkXSXp/XkENynRB32wBvb6FnPcDH5K0vaQTSIHh3VrIeYPtPcmxJdsP084f/z3gncC/spzrgTe1kLMnsD45vuC0yl20hZxS3yEkfRk4geSiWxg4XtIXW4j6Can22yvy8f8C+7SQcxTwAeA2SYdIelWTkyWtLOn9wPyStqzcPgTM1WI+90g6MstekHQN+WmD+cyllLG4sFKK+0L5tiywRIv5tGZCFBIcC7rcR1cCXwKuAixpSzd0HwFL2b63cnw/yefclCeyCeo8z3WBNkGz1fPfgypjBt7aUM5HSH705yT9h+Tfte2+89Jz0PbzwEskPcZQ4O4ZGhRMyz+qDh8GzgQuB74iaSHbD/UrK/PfrLA67/UitAtwY/uuLn3a5uL8tO1nOnIkzUa7IHCp7xAkN91qtp/Ksg4BpgJfbShnYdun5u8CTsVDG79Hti8ELpQ0P7B9vn8XcCzwU9cHql9FylxaAHhPZfxxkmXXdD5fyumzR5MWPofYPr2BiI+QlOYrgGsY+m08BhzedD6DEMpieN7TddwJUL2H9CNrqiwuknQecHI+3ha4sMW8Pk0Kli4v6XJSwGyrpkJsv6XFa/eS0yZ1s1vGN4BvSPqG7f0HEHUN6bNR5e+7882kwHITvg+cASwm6Wuk97nNqvkuSW8kLTRmB/YGbmkh51JJHaX6DuDjwG9ayCnyHcr8H2nF3cnsm5N2vWaKKbAsZ0dS1th1wM+ADYCdgY1GOtf2ryX9lpSM8PU2r5/nUGSxafsw4DBJn7D9g7bzKUEEuGcg+Qu0YT68zPYZLeXMRloBCbi1j9VSLxlFgpyVIPBytg+WtBSwuFsEgXMQ7wMlZJVC0spAJ5nh97YbX+QlLQwcRtqHIJIr4pNNLZ38/uxGyrUXcJ7tY1vMZzngLirfIWB121e3kHUmsDZwAelC/w7SRfFuANuf7FPO60nK+bWkTXCLAFu5eWD6DNL/dRLwk6o1rwbd5SRdZXudJq/ddf5Irmq7kjTTp7ytgXOd9rR8kRQn+qrta9vOsSmhLGrIPu+9bT+SjxckxS0afdgF59Mru+pRUoDygQZyziEF3r9ge7WsgK6z/bqG8zmK5Jp5q+1Xd/yyttduIqekLEl7Aj/r+sy2t31kizmtSVqVGri8zY9T0ia2z+ka+6jtoxvKOcj2lyvHk0kbKndoKOca4L2278nHbwKOaPrZ53N3Hulx2yc0kFViEfQW2xc3Pa+HnO+SPAm/AJ7ojM/Ii3PXfG6wvarS5sevAt8Cvuy0mXbGMCOj6RPxRo9sn15jfcjZkpQj/SjJ3/g48FgLOb8jZVJ1sqr+xVD+9U4N5Fzd/b8AU1vM59oechrn2ZeU1ev/aPmZfRm4ETgQ+ApwPfDFFnL+RFKAneN9yVk/DeUcD+yf789Biskc2ELO2qSsqpeTNnldT4qpNf7MSt1Ie34+Dyw/oJy5Sa7CY/LxisBmLeRc3OP2+xZyTiDv08nHC9KVIdWnnOvy328AH6iOzahbxCzqmSRpQadMmE4Qtc379k3gPW7hxuhiNuDVznna2Z10IvAGUg2ik/qUU8pHXCwIXFDWZEly/kVlmW2ymEoFb99L2sG/L2lPwsqkkh1N2RX4WQ4Cv4WkcBrvlbF9taRPkhYZTwFvt/1gi/kgaUXSBWwVKtlCtpvGh95DiuOdKul50or+VNv/aCjneFLs6o35+B7gNBpWKXChmB5pE+cjFbkPS1qjhZxOVYJ3AP9P7asStCaURT3fAf4s6TSSebwV8LUWcu4voCggrQCrG3oeyGMPSWpitpcKcnaCwIsOGAQuKetc4Bf5xwUpo+TcFnKKBG9t/1PSe0kJDdeQfPF9+381fUrzYaQd05eTAt5ruk/XiKTfMH321NykBcKPJWH7vf3OqcLxwAHAd0kKbBdaXMRs30laUH0zK6AvAf+P5mVRlre9raTts9wnpeZp3Tmb6gCGUpwvBQ5y83IdpRab25AWGt922pS3OO1rsLUiYhZ9IOk1pB8CJFP0Ly1kHEYy+88Enu6Mu/kO7iNJKben5aH3k4KJ+5I2+fW9IirhI85yOkFgkTYKtVaKJWTlQPBHGApMXwD8yHZfqZiSfkC6qC5Nj+Ct7RF35VfkPM702VlzAM/m+3af6cWSRvLB23Zf6c6S3jzS47Yv7UdOl8xrbL9e0o3OMY/OWAtZy5Csi21JqcW/sP2dhjL+RPrcL7e9pqTlgZPdMFgt6XRSoL0Tc9mJZGX29dlX5HyQ5F6bbrFpu18PQFXWBqTd+8dnq3teV3aZjzahLPpE0qJMb2Y3Mo+HyY6wm2dFiKQg1s9Dl5NqOjX+IHM657JUVjq2+yp5ren3NLwIN9/T0JG7ILBU15xmaFCxZNB2ZidfnDcAfgn8nmR5HWK76Wa4K0kB5dNISuL2lvN5B8kaXYXkZlsf+JDtSxrKmWp79bqxPmWtQtq/ZODilovNA4C1gFfZXknSK0iFCdevObUYoSxqyO6D75A2xTxAKih2i+02JabHDZJOApYn+eA7K267/1THvzO0al6aVMpEpM1M/7C9XIs5HQx8iNSnofPF7HvlXJFTyo8+EJJWtv1XDbMzvoH7aEfbP5X06WHk9NWHRNIfbW9QsXheeIiGGykrMtcm7RlZgFQaZz7gW7avaCjnVbZvbfr6w8h6GalmmYArbP+zhYw/A/va/mM+Xp/kAlqvhazVSO4sk4oRXt9CxlRgDVISyBp57AbbM6xpWcQs6jmY9MW70PYakt5C2vDTCElzkXLkX8P0F7CmlsW6wA+AV5PcGpOBJ1r80NcilR9ptVroKANJxwJn2D47H29CKuvchm1IPudnWp7foYgfvaIQp6OB0vk0sAdpsfEiMfS/W36e/HegDZC2N8h/B95Imb/PL/XQ3ox/A7tkC7xNufP7lJpvDRQjyBf1qbZ/p9Rk6POSDssxkSZ8FDgxxy5EykD8UEMZSNqbtPP79Cznp5KOcfMNds/YtqRO0sY8dScUp00K1ax0A6bkv9eTi5PRLp3zNJLi+RtpJ+n5wGFt5kNqoHIdSVHsAnyj5XwWL/D+vKgAXa+xPmWdDixaYE7XdM+DdkXgXla5LUEqu3DQjPrujfaNFOBei1Rqo+m5xwBb9hh/H3BUy8/+K6Rd9q8kKftftZBzA+mivBqpA+SewKUDvEfzAfMNcP4NwDyV43mAG1rI+SxDpeB3B/4MfGJGfl/CsqjnEaWy5JeR0hYfoLJJpwEr2N5a0ua2T5D0c+APbSZke5qkyU4B2+MlXQc0LZOxMKlV5FVMH3BvmhHzf0o7SjvF0XYgZRG14RvAdZJuGnBOT+cg922S9iL50edtOhnb/+oa+p7ShrYv93p+L3LQ9gmnjKh1Sf79abbPbCBjLlLQ92FSeY99SSvwvwEHu083S3apfp+0Sv4iqaLu/cCykj7nZrGY19veo3vQ9hmSmqYWQ7Io3185/kp2vTTlWduWtDlpo+GPJTUuIplTU99Pjul1EqpsHzTCaT1FMX0dsOfyWL/z2Br4je1v53jMY6SklC/bvqDhXAYilEU9m5NSJz9FuhDOT1oBNaWTafSIpNcC99GuYuiTkuYApkr6JnAv7fKtD2xxTi+2J60Cz8jHl+WxNpxASpe8kfZ7NSDVXpqbVDb7YJIrasSgdS+6Yg2TSKvwvn8zShVZdybVAzqFVO7jEuDdkjayvU+fok4kfX/mIfXevolURG4DUrXWzfqUczCpVMj8pE1mq9q+PbuOLmIo86cf5h7hsTbfx/9I2sDTxwj+00JOp5vgjsCb1L6b4K9JacXXUFm4tOB44EqlMiQiXU+alNT5AHCEhurK7ec+s/qKMyPNmJnhRtLqx7Y478Ok3ZtvIpmSDwAfaSFnGVLMYz7SRfpQktUy5u9Ngfe2ca+IrvMXJZUD/y3JSmnlPiCVGIHpd+9eQKpc+qoGcv5CiistQFoRzp3HZwNuaiDnpsp593U91rdLlOl3xt843GN9yroUWKfH+NqkumdN3/PVSa7eO4A7SW7W1VrIKdJNsMnn04esar+PNVqcPx9p0XEOaXF4NPDmUvPr9xaWxTBIWhX4NikL6kySyX44aad0o9zvzEVOG3MuI1c/VSro1u98FgEW8VDa3VMkU/01tNh5XSpQLmklkj91WaZPd21a6hzgD5K+QdosWHVD9Zs6eyJpJfgD0mr7+7QISpI2KOLBd/E+5RSsf0bS35y75DmV324SxH+mcl63i6/JKnNSTk2eBDyf73dcIk2tgX1Ju61/QnrPIVleHwS2aygL21OB1STNl48bB8mVduqfXP3cnFLc+0oH7+JPkl5n+8YW56LUQfC/tv9r+1pJT5BKqyxHUoR9k9+LE4ATcqbXVsD3lcruL9Vmfm0IZTE8x5IaqfyZtHNyKukD28G5/ENDTietMKr8kv6b+/wA6FUIbyHgCyRztQmHk37UpzH0I1+poQzy+UcDP6JlA50KnTII61bGmmQNLW77C/n+eZLa7s+YXyO0w3X/GykXyHIEzFeRKZIrqF+WlPT9fF7nfkdOkwY48zN9T4Tq+9MoK872VZLWIQWQP5SHbyY1jGpS0LJnOnAlRtBXWnB+7nOSnpc0v5vvtO687o2k92I2UnbX7aSFSye9uN9U1XNJ2Y+3SVqBdB35GbCZpHXcsMVvntuCpBpz25J+979sKmMQQlkMz5y2f5Lv3yppb9v/01SI0o7k1/DiC9B8NOu8tYLty7oHbf9BqVprY1wmUP6s7Vav32M+A9fj6VotT64eu/+NgvOTLJNegUjTfy+TSxnqi3IZ0/dIedFnOQLVsg5Tuh7rPh4W28s2eM1+5D1AcoUOwsBpvF38G7hR0gVMXy22r/1D9B//qWNBD/Xr3plk8XwixxuvAfpSFjm55n2kOOAaJKv7YOASZx/VjCKUxfDMpVTwq3PBeLp63MA1Uqrz1kg/qjYBvFKB8t9I+jgpwF11HfW9g3u41WVFVr+ry+6VMwytnk3/zY/udIES9E7tdAfGE2jHuFJJ/ydJmUg31T3fdptkkZH4Fc0bk1V5kOw+grRZkOQ+urOBRQnTW2pvJZUUx6nTYZPkjTtIVsqRpP4lrUrylCB2cA+DCtXjqchbz/afB5jP70g/wLO7xjchNdLZpKG8ZUhpk3OQMr3mB460Pa2hnF61aewGu6WVShkMyyhcUEZE0nXOu2SDZijt6F6aFPz+XB/Pfw0pbfasfPxdhlx0hzdYlFVlvgRY2i12hEu6DNjNdsd9dBXJfbQKqS5YX5a3pJ+SMh7vIVkRyzkVNVyAtO9jtX7/F9ttssKKE8pilJG0O8lkvE3JEftjUv72naSaNf2WfFiR1MviT0wfUFyPVK//f1vMrfWPamZG0mv7WRUHg6NUCfcbtv+Uj/9Cqjg7N/B+21s0lPceUmLKHLaXk7Q6aSNlX3t1NH1BxIOBhWzv2XEfuc8GUfm3tTewOKl/xfV5/I0k5di4kGCX/EYWXAlCWYwyeYPZGrb/K+kDpDz5jUn+xwNsbziigOllzUkKZL82D90M/LxNwH3QH1VFztykVMWlbe+RldqrbDfqH5BlrURKKljM9mtzRtp7bbfZ5BUMg3oXgXy8jYtDLy57Dik7bwrww7rvprpanUq6wva6+f4fnUuUNJjPNSS3zyUeqqF0k+3XjnzmC+e/UG9JqXT/t5w3UEq6vl+LYLRpasGVIGIWo8+zlR/hZqQ2mP8CLsyxgr6x/TRpk08JDgTWIW0Sw/bUJqm8FY6nQLOZzLGkYO4P85xuUNrpPuGVhQar8Nspmd6TBsHbDteSKvtWiz/eJ+l+YHfb14xwbje3k1KNT87H25LicSuRPs+das6fLhbXURSZNptW/2v7UU3fwqJJjOAGSd8mfY9XIJXlIbuPBqaUReBUk+tqUpblDCGUxejzvFKjkodJdfarjZNeMjZTAnr/qNqYmUWazWTmzimZ1bFn2wjKOfeLMf3FuWnXtSJomAq/9J//38l4Wp/kO/9FPt6atPGvKRcAv7R9Xp7fxiTX6PGkQGqTvs5v9PQ90n8j6Wrba0u6uY/z/0/SG2xfWR1U2gfUpmzMzdmCn5yt3E+SXLf9sjvJfbQssLHz3hjS+/7tFvPp5nCSRbAT0LdFMKgFV4JQFjXkC98OwCttHyRpaeDltq/qU8SXSR/oZOAs2zdnuW8mrcrGikF/VB2eyf7ZTjXM5WlfHuGf+fyOrK1IWVqNkPQJUkrn/QytKg30lSNfybXvSYNc+w6DVvg9Ic/rY8AGtp/Nx0fTrr7YurZfyMSzfb6kb9v+SHZ1NmFeSUt3FHH+fXTqcPWz8fBzpK6GP2Eoc+31pHTTbRvOBdIu6S+QvoMnA+eRUk37IgeTD+kx/ifa/T665bS1CAa14AYmYhY15D0MzwNvtf3qnLd/ftdqqk7GbKRyzg9XxuYhvf//Lj7p/uY0N+lHtTHJFXEeqShdoxWKCjWbybJeSapm+kaSJfZ3YEfbdzSUM420Oay7EGC/5y+T7+6Z/3aCkTsAuOGGKqWWvJ+03Vjxdcm5FVivk5acv4tXuHmjofNJtaBOyUPbkroAvotUcqVn/41hZG1K2pT5N9L3aDng4yT35u62v9eHjEWBvUj7kSDF4o7w9O2Dx5S27qNSFkHHWus1Julmz4D+OqEsapB0rVN7xhfSKcci0DUKq92BkDRbZYU7cLOZLtnzkMrBP97y/IuBd3TmN8A8XpRC2/k+tJjP6qQ0zNbVdCXtQoo1XUx6r98EHOiG+zAkLUyyvDrB48tJxTEfJSUqNE2fnhNYOR/eOiNcIj3m0Oui3OFpkjI7wvZdLeW3CigrtVPutggey3Odz3ZfFoGkW4B3dllw5+UF7Iu+p6NBuKHq+W/2f3dcI4swWEXUtnR2lvZc7fZLzY+qyQXsKobKlxxo+xNN5tE1p2IlHzK3A5co7U2pXpybypGk9W1fng/eyBhW+HXqvXwOQzGFz9m+r4Wcf5LcNb1opCgyr2coeL+apL6D98PRYiU/UjxhNpLVciop1bwxA7iPBo3pdPgM8EdJ01lweWE1QzZthrKo5/uk3cmLSvoaqYjXF2f0JJw7fUl6R9cqYj+lGkj9ukZKBOlg+l3Sg/YBrmbEfIScDTUA/8i3OfKtLbsBx2moW9rDQOOd3bYvHWAO3TxNiuPMBawkaSX3KAMzEipY/LFA8H44GgWC+3iPL8qp2H1RMKA8aEwHANtn59hiLwvue/3KGYRwQ9WQTezlSJlMIvl673eDchZZzqCB8o6cqcCeXavdI91nI3m9uHptZ3wV4EHbD/Yp5wV3TBvXzAhyi5nUSnV1GDQulJUFbt7is2jPa0kfJmXqLEm6OK8L/LnpRV7S9aQ4wzVUij82TJntyLqFAYL3o80AsYZS7qOBYzoVWa3Tr0sQyqKG7MrYwkO1YhYHfmu732qxHTkDB8qznNcDx5FKIryw2nX/O8FPISmXy7rGNwQ+Zruv6rWSniS5LERaWXbcF02rc3bLHVjxKDWXOolUmRPgn6SeBk3M/s5C4YVuaZ1xN++WVoQct1qbFBdaXalI5ddtD1shdxg51zT9/o4gq1TwflRSQweINRQLKJeI6Qxnwbn5HpvWhBuqnjNJdfu3Im1kOotkwjflDZ1AOYDth5VKCDQir/5Wa7vapVz12lc3fN0ZyTHAp21fDCBpI1J64RtHOKcXpbqlkeexKJVKw26+7+Mp209JQtKctv+qVOiuKQMXf6xQqj3vqKSGDhBrKOI+ypSI6QyUfl2CUBY12D42X9TPJH3gH3GuY9OQIoHy7tWumvcGLlK9thNDKUFXptcKkm7oPEQ7K2WejqIgCbgkBwKbsqTtd7U4bzqUel9/h9RI6wFSt8NbGEoV7Ze7lXYSnwlcIOlhUo2xpnRazFZLnzepylvlwBbn9KJIILighVIkoFwwpnMTqQvgQBbcIISyGIauDB2RTNmpwLqS1m2RWVMqUD7oaneapE3du3rtwJsEJV1I6hd9hPuvD1Wqh0CH2yV9iaGMsR1p978N1C2twsGk+MKFtteQ9JY8p0bYfl++e2BOx52fVL66qZw2ZV2Gk1UqeF9qJV/EQikYUC5lEZSy4FoTymJ4ulfgvxpmvF9+SbrAdwLlW5B2GDdl0NXuPsDvJG1Dj+q1A8jt8EFSpc11657YoaSVktmVtG+g85n9gRZZTKR9CB9SKsPepltah//a/pekSZIm2b5Y0vdazAdJqwGd4pN/cGrb2u+5b7X9ew3TBdAN+jWUDt5TLjW0VKoqlHEflbIIDhzw/IEJZTEMHp2mLFvY/iu8ECi/gP7bqnYYaLXrVCr9dUxfvfZSknttoM1UOWi/cI6rNM6s6SGvjZWC0075EoG/Rj1CRuCRnJl1GfAzSQ9Q6eLWL5L2JtUu6lzUfyrpGNs/6FPEm4HfM30Trg5NOgDiXA3WdpFOdwVX8kUslILuoyIWQUELrjWRDTUMkr5ne59hfKBtdt/uTuq4NV2g3Pb5DeX8hVQNc9DVbhEkXQK8l7TwuIbkk7/c9ojd7/qU/QqylWL7iD6eX/Qzq8gdKDCdV8f/IW3o24HkPvpp04ByjuWsZ/uJitw/N/nsJU0CtrJ9apPXrpFZpGhjidTQUqmqpVKClWrAvYh+L/6jYMG1JpTFMEh6ve1rBv2wu2TuSaq/sywtA+UaqlvUPZ+BXDltV/HK+yKU9gAsZfsAVXoCDDCfBbO8G2qfPHRO0c9suMB0k7TJLOf/dadt9hrrQ86NwNqdFbekuUi1nPpqyFORM10PiUHQMEUbm37+JVNDC6WqFkkJnpkIN9QwZFfKwOZf6UC5h3ZyT7faLUDjWENmtuxS24ZUmLA1vawUSX1bKR7aVLa67cO6ZO9Ncrc1oUhgmlSkr1sxbNJjrI7jgSslnZGPtyDtuWnKhZI+Syp1/oI7rGXq7N6kZletijZWKJkaWiLWMJD7aDQsglIWXFtCWQxD9p9+AXgIOJSUSbEhybzdzfaUEU6vUjRQXjANsypzkFjDQaSKtZfbvlqpcuxtLacyv+3HspVyYsdKaSFnZ+CwrrEP9RirY6DAtFJJ8Y8Dr+z6P15KKt7XCNuHZoXaKQC4C9C4nS5Dpb/3rIy1TZ29i5SdNyhFAsEFYw0HDjKP0jGd4Sw4+iy7X2QO4YbqjaQ/kr5g8wGfImUR/YakML5qu0mDmJLzup7UNnK61a7t3RrKuYRRijW0JbtZNiZlv3whK5++XVpKDZg+QLqYVvs8vBR43vbbGs7nQtLq/RukleYDJDdQX5v7lDZOLpjPr9buerxFvGIJkuV3g+1nsmW5D6kc/CuayCpBxWJ+DfAqUn/41kUbVa4y77grP1LCItCAZfdLEJbF8Mxr+xgASR+1fVoev0DSt/oVMgpB11JpmEVW8SrbN3tQK+VPpJXpwiTrq8PjQBsLZXNSYPpTDAWm+y714bS7/lFg+64LxryS5u33giFpH5KVOw2YU9KRwP8jLWYal+2Q9MFh5ttk9d1ZMfcq2tjmQn1gi3N6MZCFUtp9VNAiKGXBtSYsi2HQCIXyuo9r5JQOug602q3IGWgVX5FzKblvtof6fdxk+7UjnznrIGkv0sWwVRA4Z8BtYPuhnAr6v8D6blH4L8urptrORdr7c63trVrI2rqykBp2bEZRykIpOJ9BG3EVteAGISyL4Vk5r7QFLK/pS1D07dstFSivMNBqt0KpWEPJvtlFrBSl/s0/INWvmoPU0vaJGZlm2MU+DBYEfqrjtrL9D0m3tlUUWcZ0vSyUSoic0vvZtewPdCuGXmM9GYVA8IENnz/S3EoElAe1CEpbcK0JZTE8RQrlFQyUA+CcY09aobZuepJXfqdVjm8n1ZxqSpG+2ZljyVZKntMNkn4ONHVpHQ5sR/r/1iJleq3Uck4lGPSCsaSk71eOF68et0kv7eIJ0n6EvlEqD7MpsETX3OajwWKhdCC41KJsUPdRxSIYqBGX8+bg4Sy4fmSUIpTFMLhcCYrjGQqUX0laZb6PpDCOYKjr2QylYKxhT1KV15Ul3UPum91yWsWsFNvTJE22/RxwvFK13/1bzqvVvo8Kg3bu27freKDd8V3xs8mkhVHTTXr/RyrO996u+TxOsnrbzKv1Sn4ULJRBU4JLWwQDWXAlCGXREDXfvFYkUD4KFFnFZ4vk7Rqwb3amlJXypFKl4KmSvpllNG6HOui+jwoDde5zwx7bfVDtlvgscKftu5sIsH09cH3+zoghy+1W594vTRh0JV/aQmFAa7CURVDKgitBKIvmNN28Vi1D/tgIjzVmwNXuQKt4STva/qm6+merfd9sKGel7ERSDnuRVrlL0c7FViRjzOXrjAEg6eukC9qPmqyAbV8qaTFSIyVovy8GUo+QE4E7SEpjKUk7u2GrV8pt7hvUQiniPqowqEVQ3IJrSyiLBqjd5rUigfLKHC6hzGp30FV8pz9EqZVcESslXyi+bnsH4ClS9dm2FNmdnjN0eqVNN+553cVVpA1o3yUtYvqdzzbAt0j1kgT8QNK+tn/ZYg6HAhvbvjXLXolUHrxpSm+R1NACqapF3EcFYzpFLbhBCGVRQ4GLc+mOckVWuwy4irf9w3xhfsz2d1u8/guUtFJsPydpGUlzuEH57mEolTFW7aw4F8nKGdiFYPvMlqd+gZRu/QCAUiOuC0ll9Jsye0dR5Dn9r6S+m2iNwkp+IAulYEC5tEVQyoJrTSiLega6OBcMlHcostotsYrPF+btSSvbQShtpdwOXC7pLKavfdS0DleRjLEeaa6XK9UcakSOv3yVlDp9Lmm1/CnbP20oalJHUWT+RYuYTmaKpB8BnTnsQLpI9kvpQHCpzWsDuY9GwSIoZcG1JpRFPcUK5VVpESjvMNBqdxRiDZdLOpwXF6W7tl8BJa2UzN/ybRIDKKCC+z4WqhxOIv3A528xpY1t/4+k95FWmFuSemT0pSwkfd3254FzJZ3H9N3kzmkxH4CPkazUTvruH4Aj+z25YCC4iIUyCgHlUhbBQBZcCWIHdw35C/sl0sX5Y/ni/C3bbQKmVbmNejWUQtJH8sX5gF6PNw3GZn98DzHN/fGSrrK9TtPzRgsV2p2u1GnPpIvFsySX30G2/9hQzk1Zaf0I+KXtcyVdb3u1Ps+vViXYkqGChH+wfcbwZ44+6lEVodfYCOf3/D5n7D571Ct1IlydtCj7cuWhx4GLnRpr9Y2ka4APdFsEthtZBJKOI8VgqhbcZNu7NpEzCKEsxoBBsphKrHbzKv6ThVbxxZD0XWB2WlopGqb+VkVO06J0nXac11WUxVTbqzeRUwpJh5BKvfwHWAdYAPit+yxqqVSEciOS0noRblDcUKlczEjvdb+b1zor+W1In3uH+UgFARstHoazULrH+pAzO2VSgl9UQqfXWB9y5iRZcC8oeOBI208Pf1ZZQlnUUNAVcQkFqrwWXO0WWcUrVVY9AHhTHrqUtGpu7Dce1ErRUP2tLUnF5DqrsO2B+203CixKOoeUfnua7TVzxthuthu1W80Xno8x9B5dQvr82lx8FgIezfGieYCX2r6vz3OfBu4hb1SrPkR6n/vOzlOqTLAYKUZQZSngPtvT+pRTeiU/kIVSOefNdLmPgMbuo/FgEZQilEUNBS/O17lAR7lSq91BV/EVOaeTKn12No7tBKxme8smckqiHp3geo31IeeVpIyxNwIPk9xHOzRNWshuo9mZ/j16zvaHG8qZG/g0sLTtPfIF+1X9xryq35lBkfRbYH939YJX6u/+ddu9+nyPJG+glfwoWCil3EcDWQSlLLgSRIC7nlIlKEoFykvtcl49/636ck3qldGE5bviN1+RNLXFfEpaKfNIeqVT9hKSlmMo46rfuUwGPm67xO70tbviCr/PLqGmHE+ySjsVhu8hZec0SZAoxWLdigLA9o2Slm0hb9BAcOlU1SIB5awUDs23NmzJCBZcS5mtCGVRT6mLc6mc/SK7nG2/pcVr9+I/kjboBGslrU/yqbfhOJKVsk0+3ol0gWxqpXyKlBFzO+nCswywRxMB2c3TKSHxRN3za3hO0vK2/wYvWCzP1ZzTi+Vtb6uUroztJ9W1iqmhaafAkVhghMde0kLeQKmhLp+qOlBKcEGL4LskC246a1bSfPmxRhbcIIQbqoZhXBE72r5jjOc10Gq31Cpe0uok98r8pB/pQ6TubY1Xzr3caW0Dytn8Xzkf/rVNIFDSUcASpNV71VX3q2FP6i3nbSSlV1Veu9juFaMZSc6fSL0nLs8xlOVJrpGBYk9qUTZE0snA720f2zX+YeAdtrftfeaw8koFgkvFGgZ1H5WK6Vxte+1hHrvR9uv6kVOCUBZ9UuDiPFCgXF37Irpx8zaWRWMNeaWD7e76V01k/BnYt8tK+bbt9RrKuQb4MelC2ihA2iXn+B7DbhOczBefV+XDW1sqr3cAXwRWAc4H1icp5kuayuqSuwWpbMhqtvsqG6JUW+oM4BmG3D5rkTbUva/foHtFXpFAcKlYw6CUiulIus32isM8Ns32CoPPtj9CWQyDhtm81qHFxXmgQLkK5ZFX5BVZxUvam7RqfpxUyXZNYD/b5zeRk2WtTgErRdIKwC6kzWZT8vzO9wz+sivtZRiWFhbKQqT3Zd389wpSNtTfW09yQJR6wHe+wzfb/n1LOUVSQwe1UEq5j0pZBKUtuEEIZTEMKr95rVQW0/q2L68b60NOqVX89bZXk/RO4KOkle9Jbpiq2CVzYCsly5kEbEay6J4jKY3DXLOfQNL/2P6mUvvRXgUA+2o2JOl5YGq+AdPtb2hsoUi6HNik875IejUprbdpZl6psiHjjkEtlILuoyIWQWkLbhAiwD0MLl+ColSg/Aek1XvdWB0fA07IsYsXVvEt5tO5AG5Kqp11c8Og65CgLitF0iBWyqok62JT4HTgZ6RV6+8ZygQbjr/kv426GPZgS1LHvlWBX5PcIX1dbIbh68BvJG1KisecSLoYNmWgsiElKRgI7jBQ+RHKBZSnSNp9GIug7+ZVtu8H3thlwf2urQU3CGFZ1KBym9cGCpRLWi+fuw/TF+6bj7TC6KvkQw+5A63is19/CVJbztVIndcuaeMjLmWlZL/1I6S4xelVV4akX9XFZSSdb3vjpvMfQd48pN7p2wIvA77glu0/c3zhf0g1r95v+39byBiobEhJSq3kC86nlPto3FgEpQjLop6BC+Xl5w9a5XUOYF7SZ1YtjvcYsFVDWSVX8buRVuq3O6VyLkRa0behlJWydX6/X0SfAfyFW7zmSDxFyjZ6jJQJNVeTk3u4w+YnFUrcS1KbHty/lfRXkhvqY0olyp9qKKMURVbyBS2UBUZ4rO+U4PFkEZQiLIsaNHgJitKB8v+x/c2usTa1b0qt4tcHptp+QtKOJHfYYd0//j5lDWSllMoYU9qf8dnhHu83MC3prSQ31DqkfhGn2G7s2pK080iPu0XbVQ1QNqQkBVfypWIN4yagPN4Iy6IGD755rXSvhu2Ab3aNtWncXmoVfxSwmlKNn88APyL50t884lm9GdRKqb7HHyH3F2/B/KTAeK/3w0C/WUwXAjcAfwTmBD4o6YXU1H4tgjbKYCSUyoZ8HFiatFnxFaS03rHYCb7ACI812dxXKtawD3CGpB3o4T5qMJ+ZjlAWNWjAzWulAuUqX2f/Gknnk1bx+0t6Ke16gj9r25I2Bw63/WNJu7WQA7AePayUfk+uZqhJ2qJpxlqFO5tmKg1DW3fcdEg61fY2w7laWgSBx1PZkCKBYAqVH5kZ3UelCDdUDSq0eW3QQLnKV+ecxNAq/pG8il/SDcumK+0fORfYFdiQVE33+n7dB12ybiC5n1YFfkKyUrax3dhKUYtKo5VzX0hvHg9IWtz2vZKW6fV4U5efclHFrjTusQpwFwkEl0pVDYYnLIt6ShXKGyhQ7vK1bwZaxVfYFvgAsKvt+yQtDXyrhRwoa6UMwk6jKVwNy2vYvjf/fUEpSFoY+JfbrfaekfQShtK4l6fSVW5GUnAlX8pCCYYhLIsaVG7zWpGOcipX+6bkKn4ZYEXbF2Z/+OQW2V4DWyldbpoVgE5Qs9OvYaByzmrfCrdbzhY0KK8haV3gENJemIOBk0gZW5OAD9o+t+Hrj0rZkLFkZkxVHW+EsqhBBQvlFZpPqTr71zoVo/sycE9exbdpErM7KUi6kO3lc1bK0bbf1kROlvVykpVyte0/ZCtlI9sn9nl+TzdNhzYZWl3yx6oV7hTg86Tv4DGkXdxXSFqZ9Nk3cplpHJYNKYUKlR8JemA7bn3cSIHk+QY4f35SGeYp+fYdYP4Wcm7oZ6wPOZeSsqhuI3WVmwTc2ELOVNLq7brKWGM5lXOXAd6e789NuoiNh89/QWDVlud+M39/ZgcuAh4kbcjs+z2u3L+l67HrWszn8up3GXg1cNNYv8dxG9+3SeXUzsyJpL1z+t3jwKGSrpXUZnfvcVnGNvn2GCkrpSlTJP1I0kb5diztylJsS/JT7+pkoi9Ju1jD07af6RxImo0RNkeNRLZSfslQyusSwJltZHXJvVDSOZI2a3jeJZLmyyvxa0mbF9s0sdnYaYf8ZiT34QqkopL9Us1S6+4V0ua97pQNmUfS60nveeOeKMGsRQS469nV9mF589rLSMHPk0i+3iaUCpQPWvsGAKdg9OlAJ4PknySfb1MulfR54CXZF/5x4Dct5ED6v9YBrsxzvE3Soi1lVfkg2X3U8Lz5bT+Wg6QnOrfCbfH6nd/Zu0mF/x5tuKVlNUmPkVxGL8n3yceNdoMD2P6dUte3C0h7U97nFmVDglmLUBb1lNq8VqSjnAdv00h+/RdiDaRg6xLA0aTmOk3Yj7SZ7kbSRrizScHyNjxt+5nO2zuIldJB0oLAwravoXlWTKlWuAOV17A9eYDXfgGVLxsSzEKEsqin1Oa1gaq85sDxF/J5h5J6R2xI+rF/2PbVDedTahX/EuA455RFpQ2ILwGebCGriJUi6RJSL+bZSAriAUmX2x6xHEgPirTCtb2fUlnwTnmNJ0mFBWc03e7KSCkN+iayoWootXmtIq9VlVdJfySlzM5H6jG9D+lCuiHwVdtvaCjvSttv6GzMyqv4a928jeUVpID0v/PxvKRGQ28c+cyesiaRrJSNSQr1PNJehEZf0sr/9GFgqY77qOn/VoqcTvxpYGnbe2TF/yoPkH4bBDOaCHDXsx5p49sjefPaF0kbqhpRIFA+r+1jbH8b+I/t02w/ZfsCUt2hpnSv4k+jXaxhro6iAMj3524hB4aslK1tb0VKCmhSH6hD1X00yH6IlSRdJOmmfLyqpC+2EHU8Kf+/Wl6jr3a6JZF0av57o6Qbum8zej7BxCKURT1HAU9qqFDe30gr/Kbsmq2JjRkKlB/S4Pyq66vbKmnjFtuPlMJZjTW0uRA+oVTeHICcXdM4FpO5iOmVw0tIxfia0nEf/W0Q9xHJ1bc/aSMe2ZrcroWc5Z0qBXfkPEnvIoWjzd7572akwnrdtyAYlohZ1FOqBMWggfKV8+pPwPKVlaCAV7aYT6lYwz7AaZL+L8/l5aS03Da8yErJLpxGOJVrP61yfDvw/uHPGJa5bV/V9TG1Kdo4LspruHzZkGAWIpRFPY9L2p9kCWyY/eqzt5AzaKD81S1ecyQuAt4OdC7OLyGlAzeKNeSV+8qkEtfQvlYVZCvFuV5WWytFaVf7UaRKpK9VarH6XttNXT+lWuEeQCpjspSkn5HLa7SQMxAaoWyIpMZlQ4JZjLHeFTjeb6SV8qeBDfPx0qR6PE3lTCIV61sgHy9Eyx3Bhf6vqf2M9SFnz87/lI8XBD7eck5rk9x8fyD1gJgGvL6FnEtJmV7XVcYa71AmWWwXkqyte/Kclm0hZyGS6/HdJBfQwsByY/CZTyG5QbcmtfZdN4+vTIud4HGbtW4Rs6jBaXfz6QwFkdtuXisSKO+m7e5kysUadrf9SOfAqVT67i3k4JT+uzIpzfijwKud9kc0ZW7bV3WNNXYf2b7d9tuBRYCVbW/gPnumd/Eb4L+2f+eUAbUI7TcuDsJsts93ctPdZ/sKANt/HYO5BBOMcEPVUHDzWsmOclXa7k7ehzKxhsmSZLvjqplMqhXVGEl7Aj+z3ck+WlDS9rab7lAfyH2kYVrhdmIXbtgKl6HyGpuSlOGJwA4NZZSgdNmQYBYilEU9pTavFe/VMMjuZJeLNZwL/EJSp57TR4BzWsiBZKW8UM3V9sNZWTdVFnuSqrOuLOke4O80q31UtBWux095jaJlQ4JZi1AW9ZQqQVEkUF5qd3LBVfznSJbXR/PxDSQrpQ1FrBSn7Ke3S5oHmOSGvTVcrhXuuCqv4UJlQ4JZk1AW9RQpQUG5jnLzu0xxuyKreNvPS7qS5KLbhhS8Pb3FfGBAK6Wk+8ipLMf2QGtlQZTXCGYiQlnUU6RQnstVeS1V3G6gVXxOT90+3/5JaheL7bcMMKdBrZSi7iMGb4V7Qv2zgmBiEMqiniKb1woGyosUt2PwWMNfSSmum9meBiDpUy3m8QKDWiml3EcVVs9/D6q+DNBXK1xJp9reRtO3ex0SNEa1qoKgDVFIsAYVKpSn1LtiHeBK5zaYkm50n/2lS5NjJnswpKxuAF5ue88+z9+CVPpifZLiOYVU9G+5FnPpZaV81vaIbVJHkHeV7XXanFsSSYvbvlfDtHv1gG1eg2BGEvss6ilVKK9IRzkVKm5n+3lShtcdJCX2VuCWBuefaXs7UiroxaRU3EUlHaXmnQT/ml9/s7yX4QfAcw1lVLlc0uGSNpS0ZufWVIik+SUdKmlKvn1HqcR8X7hSXqNzI7mz/hGKIphohLKop9Tmte5AedsqrwMVt8vK5gClZjw/AP6R5bzF9uFNJ2P7Cds/t/0eUmvW60ixhyZsSdoHcbGkYyW9jcEK7a0OvIbkPvpOvn27hZyBWuFKWlepNeuvJK2RFfxNwP2S3tViPkEwZoQbqgZJa5NcLNNtXmu6s1jlejVcbXtt5Z4NeWyq7dX7PP95Uqxht0qs4XbbbYoRFiWnum5Ocke9lbR57QzbTVvYlprPi97Xhu/1FODzpJTZY4BNbF+R97ec3Pn8gmAiEAHuGgpuXitV5XXQ4nZbkiyRiyV1Yg1jUS77Rdh+Avg58PO84XBrkpXSSFlkV9EBwJvy0KXAQbabllcZtBXubB1FJ+mgankNterMGwRjR7ihasib1+axfVPewDavpI+3EFWqV8OewA8Z2p28D6mWUl8UjjWMGrYfdmr21DRbDAZ0H1X4GHCEpDsk3QkczlBabz9EeY1gpiHcUDUM44q4rqkLYVCXRg95rXYnDyOrs4rftuXFeVwxCu9121a4z5EC2mJ6K1KkxIk2pe6DYEwIN1Q9pQrlDdSroeTu5G6cKsUek28zA4O6j8jn7U2ySB4Hjs2JDvv1G0OJ8hrBzEQoi3p6bV5r0yRmHwar8lp6d/LMzMeAE3LsQqRmPx9qIWdX24dJeidDrXBPomEMJQhmBsINVUNl89rb89AFwLF5n0JTWbMzQKA8WzWfLLQ7eaanrfuocv4NtleVdBhwie0z2rggg2BmIALcNdh+3vbRtreyvRXwF9L+hEaUCJTbfo6UVhqMgKS9s6J4HDhU0rUtg/edVribAuepeSvcIJhpCMuiDyStQbpIb0PqjfCrvMu4iYxSgfLvkkqbtypuNysg6Xrbq2X30UdJXQlPst1oF3e2KlcHbnfqcLgQsGTeCBkEsxQRsxiGYeoVaYCqqqUC5avnv62K280idDYxbEoq436z2m1sWI/Ul/wJpVa4awKHlZpkEEwkwrIYhtI7nSV9C1iGtEcCUqD8LtufKTHfYAhJx5Oq+i4HrAZMJsUcXt9Qzg35/FWBn5BK029je9BWuEEw4QhlMQwqWFU1yysSKC+4O3mmpZT7SNK1tteU9GXgHqdWuNc2dWcFwcxAKIsaRqtekaQNge3cZ0nwynmnk4rRdRrr7ASsZnvLQeYzM5H3VbzIfdS00qukS0kLhV2BDYEHgOs9RmXlg2AsCWXRgEF3Oo9ioLz17uSZkVLuI0kvJ7XCvdr2H5Ra4W5k+8TCUw6CcU+kzjagTb2iHiXB7yIHypsqisx/JG1Qkd9qd/JMzrM5kWBz4HCnXuONNzPavo/UqW/OPNS2FW4QTHgiG2r0Kd1+tNTu5JmZxyXtT3LRbZhjGI3rMKlcK9wgmPCEZTH6FG3sY3uq7Y6L5XW217B9faG5zixsCzxNKtdxH6kp07dayNmTlODwGIDt24BFS00yCCYSoSxGmdIlwQvuTp5pKeg+KtIKNwhmBkJZzCBcpv0opNXyY6SOe53idoeUm+nEJ7uPfsnQnpYlgDNbiLpUZVrhBsGEJ7KhJhhR3K4eSVOBdYArPdR69samKa8q1Ao3CGYGIsA98egUt1sO2D+K2/XkadvPdCp8DOA+KtUKNwgmPOGGmnjsBuwHrG37SVKWzy5jO6VxRyn3UalWuEEw4QllMfFYj9QL45G8O/mLQJT6mJ79gAeBG0k1uM4mvU9Nmcv2vzsH+f7cRWYYBBOMUBYTj6OAJyWtBnwG+BupBEkwRMd9tHXuQXIc01sI/fJEbqUKNG+FGwQzE6EsJh5FdifP5JRyH+1DaoX7B0l/JJWp32vw6QXBxCMC3BOPIruTZ3Je5D6S1Nh9ZPtqSSszQCvcIJhZCMti4lFqd/LMTBH3UYlWuEEwsxD7LCYgkpYBVrR9YV4xT7b9+FjPa7wgaW1S/5H/I+2PeDmpUvA1DeUUaYUbBDMD4YaaYERxu3oKuo9KtcINgglPuKEmHlHcroaC7qNzgV9IelsuAHlyHguCWY5QFhOPKG5Xz+62H+kc2H4Y2L2FnM8BvyeVhf8YKctq3xITDIKJRiiLiUcUt6tnsjq1PmjvPrL9vO2jbW+V92v8hdTAKghmOSLAPcGI4nb1SPoWsAxDVWc/Atxl+zMtZA3cCjcIZgZCWUwwJM0DPGX7uXw8GZgz14kKeEGh7gG8PQ9dABxru6+Ci5JWIimI7Um9MH4BfNb2MqMw3SCYEISymGBIugJ4e2fTmaR5gfNtv3FsZzZ+kbQhsJ3tPft8/vOkVri7VVrh3m77laM4zSAY10TMYuIRxe36QNIakr4p6Q7gIFIv9H4p2go3CGYGYp/FxOMJSWvavhaiuF2VYdxHsv2WJnJsnwmcmV1+m1NphQucYfv8kvMOgolAuKEmGKV2J8+MjKb7SNKCwNak9zo2QAazHKEsJiCSZieK270ISVsA25E2LZ5LUqo/sr3cWM4rCGYGImYxwYjidsNj+0zb2wErAxdTcR9J2nhMJxcEE5ywLCYYUdyuGeE+CoIyhLKYYEi6EVi1q7jdDbZfM7YzC4JgZiayoSYeneJ21d3JUdwuCIJRJSyLCcagu5ODIAjaEMpigtN0d3IQBEEbwg01AelV3G5sZxQEwcxOKIsJQqndyUEQBG0IN9QEIYrbBUEwlsSmvIlDFLcLgmDMCMtiglEpbrc98FbgRKK4XRAEo0woiwlM7E4OgmBGEcoiCIIgqCViFkEQBEEtoSyCIAiCWkJZBMEISHq5pFMk/U3SNZLOznteej13gSgXH8yshLIIgmGQJOAM4BLby9t+PbA/sNgwpywAjLqykBSbaYMZTiiLIBietwD/tX10Z8D29cB1ki6SdK2kGyVtnh8+BFhe0lRJ3wKQtK+kqyXdIOkrHTmSviTpVkl/lHSypM/m8dUlXZGff0bOeEPSJZK+J2kK8AVJf88dE5E0X/U4CEaDWKEEwfC8FujV2/wp4H22H5O0MHCFpLOA/YDXdppT5e58KwLrkDZQniXpTcB/gPcDqwGzA9dWXudE4BO2L5V0EHAAqeMfwBy218qylwXeDZxJaiX7q2ivG4wmoSyCoDkCvp4v/M8DS9DbNbVxvl2Xj+clKY+XAr+2/RTwlKTfAEiaH1jA9qX5+ScAp1Xk/aJy/0fA/5CUxS7A7oP/W0EwPKEsgmB4bga26jG+A7AI8Hrb/5V0BzBXj+cJ+IbtH043KO3Tcj5PdO7YvlzSspI2AibnfuxBMGpEzCIIhuf3wJyS9ugMSFoVWAZ4ICuKt+RjgMdJVkOH84BdJc2bz11C0qLA5cB7JM2VH9sMwPajwMO5RwnATsClDM+JwM+B4wf8P4OglrAsgmAYbFvS+4DvSfocKVZxB3Ag8P3cD30K8Nf8/H9JulzSTcA5tveV9Grgzymxin8DO9q+Osc4bgDuB24EHs0vuzNwtKS5gdtJLqbh+BnwVeDkgv92EPQkyn0EwRggaV7b/85K4TJgD9vXNpSxFbC57Z1GZZJBUCEsiyAYG46RtAop1nFCC0XxA2ATYNPRmFwQdBOWRRAEQVBLBLiDIAiCWkJZBEEQBLWEsgiCIAhqCWURBEEQ1BLKIgiCIKgllEUQBEFQy/8H2OBviouzzCAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plotting the data\n",
    "pro_cat = np.sort(df[\"Category\"].unique())\n",
    "plt.bar(pro_cat,category[\"Revenue\"])\n",
    "plt.xticks(pro_cat,rotation=\"vertical\")\n",
    "plt.title(\"Category V/S Revenue\")\n",
    "plt.xlabel(\"Category\")\n",
    "plt.ylabel(\"Revenue\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "90fa906b",
   "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>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2013</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2015</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2014</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1366</td>\n",
       "      <td>1035</td>\n",
       "      <td>2401</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2016</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>20</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1188</td>\n",
       "      <td>900</td>\n",
       "      <td>2088</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2014</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>238</td>\n",
       "      <td>180</td>\n",
       "      <td>418</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Day     Month  Year  Customer_Age       Age_Group  \\\n",
       "0  2013-11-26   26  November  2013            19     Youth (<25)   \n",
       "1  2015-11-26   26  November  2015            19     Youth (<25)   \n",
       "2  2014-03-23   23     March  2014            49  Adults (35-64)   \n",
       "3  2016-03-23   23     March  2016            49  Adults (35-64)   \n",
       "4  2014-05-15   15       May  2014            47  Adults (35-64)   \n",
       "\n",
       "  Customer_Gender    Country             State Product_Category Sub_Category  \\\n",
       "0               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "1               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "2               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "3               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "4               F  Australia   New South Wales      Accessories   Bike Racks   \n",
       "\n",
       "               Product  Order_Quantity  Unit_Cost  Unit_Price  Profit  Cost  \\\n",
       "0  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "1  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "2  Hitch Rack - 4-Bike              23         45         120    1366  1035   \n",
       "3  Hitch Rack - 4-Bike              20         45         120    1188   900   \n",
       "4  Hitch Rack - 4-Bike               4         45         120     238   180   \n",
       "\n",
       "   Revenue                Category  \n",
       "0      950  Accessories,Bike Racks  \n",
       "1      950  Accessories,Bike Racks  \n",
       "2     2401  Accessories,Bike Racks  \n",
       "3     2088  Accessories,Bike Racks  \n",
       "4      418  Accessories,Bike Racks  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93342404",
   "metadata": {},
   "source": [
    "### What age group buy which type of products"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "570b716f",
   "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": [
    "category[\"Customer_Age\"] = category[\"Customer_Age\"].astype(\"int32\")\n",
    "age_pro_cat = np.sort(df[\"Category\"].unique())\n",
    "plt.bar(pro_cat,category[\"Customer_Age\"])\n",
    "plt.xticks(pro_cat,rotation=\"vertical\")\n",
    "plt.title(\"Category V/S Customer_age\")\n",
    "plt.xlabel(\"Category\")\n",
    "plt.ylabel(\"Age\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fcd82c40",
   "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>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2013</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-26</td>\n",
       "      <td>26</td>\n",
       "      <td>November</td>\n",
       "      <td>2015</td>\n",
       "      <td>19</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2014</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1366</td>\n",
       "      <td>1035</td>\n",
       "      <td>2401</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-03-23</td>\n",
       "      <td>23</td>\n",
       "      <td>March</td>\n",
       "      <td>2016</td>\n",
       "      <td>49</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>20</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1188</td>\n",
       "      <td>900</td>\n",
       "      <td>2088</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2014</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>4</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>238</td>\n",
       "      <td>180</td>\n",
       "      <td>418</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Day     Month  Year  Customer_Age       Age_Group  \\\n",
       "0  2013-11-26   26  November  2013            19     Youth (<25)   \n",
       "1  2015-11-26   26  November  2015            19     Youth (<25)   \n",
       "2  2014-03-23   23     March  2014            49  Adults (35-64)   \n",
       "3  2016-03-23   23     March  2016            49  Adults (35-64)   \n",
       "4  2014-05-15   15       May  2014            47  Adults (35-64)   \n",
       "\n",
       "  Customer_Gender    Country             State Product_Category Sub_Category  \\\n",
       "0               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "1               M     Canada  British Columbia      Accessories   Bike Racks   \n",
       "2               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "3               M  Australia   New South Wales      Accessories   Bike Racks   \n",
       "4               F  Australia   New South Wales      Accessories   Bike Racks   \n",
       "\n",
       "               Product  Order_Quantity  Unit_Cost  Unit_Price  Profit  Cost  \\\n",
       "0  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "1  Hitch Rack - 4-Bike               8         45         120     590   360   \n",
       "2  Hitch Rack - 4-Bike              23         45         120    1366  1035   \n",
       "3  Hitch Rack - 4-Bike              20         45         120    1188   900   \n",
       "4  Hitch Rack - 4-Bike               4         45         120     238   180   \n",
       "\n",
       "   Revenue                Category  \n",
       "0      950  Accessories,Bike Racks  \n",
       "1      950  Accessories,Bike Racks  \n",
       "2     2401  Accessories,Bike Racks  \n",
       "3     2088  Accessories,Bike Racks  \n",
       "4      418  Accessories,Bike Racks  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "460bd0e6",
   "metadata": {},
   "source": [
    "###   What category of products were bought with maximum category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5ca9eec0",
   "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": [
    "category = df.groupby(\"Category\").sum()\n",
    "pro_cat = np.sort(df[\"Category\"].unique())\n",
    "plt.bar(pro_cat,category[\"Order_Quantity\"])\n",
    "plt.xticks(pro_cat,rotation=\"vertical\")\n",
    "plt.title(\"Category V/S Quantity\")\n",
    "plt.xlabel(\"Category\")\n",
    "plt.ylabel(\"Quantity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7fd8d28b",
   "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>Date</th>\n",
       "      <th>Day</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Customer_Age</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Customer_Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>State</th>\n",
       "      <th>Product_Category</th>\n",
       "      <th>Sub_Category</th>\n",
       "      <th>Product</th>\n",
       "      <th>Order_Quantity</th>\n",
       "      <th>Unit_Cost</th>\n",
       "      <th>Unit_Price</th>\n",
       "      <th>Profit</th>\n",
       "      <th>Cost</th>\n",
       "      <th>Revenue</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2016-05-15</td>\n",
       "      <td>15</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>297</td>\n",
       "      <td>225</td>\n",
       "      <td>522</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2016-05-22</td>\n",
       "      <td>22</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>100</td>\n",
       "      <td>90</td>\n",
       "      <td>190</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016-05-17</td>\n",
       "      <td>17</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>29</td>\n",
       "      <td>Young Adults (25-34)</td>\n",
       "      <td>M</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>590</td>\n",
       "      <td>360</td>\n",
       "      <td>950</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2016-05-23</td>\n",
       "      <td>23</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>47</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Canada</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>1697</td>\n",
       "      <td>1035</td>\n",
       "      <td>2732</td>\n",
       "      <td>Accessories,Bike Racks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2016-05-30</td>\n",
       "      <td>30</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>38</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>United States</td>\n",
       "      <td>California</td>\n",
       "      <td>Accessories</td>\n",
       "      <td>Bike Racks</td>\n",
       "      <td>Hitch Rack - 4-Bike</td>\n",
       "      <td>2</td>\n",
       "      <td>45</td>\n",
       "      <td>120</td>\n",
       "      <td>145</td>\n",
       "      <td>90</td>\n",
       "      <td>235</td>\n",
       "      <td>Accessories,Bike Racks</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>112947</th>\n",
       "      <td>2016-05-23</td>\n",
       "      <td>23</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>22</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Vests</td>\n",
       "      <td>Classic Vest, S</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>64</td>\n",
       "      <td>159</td>\n",
       "      <td>144</td>\n",
       "      <td>303</td>\n",
       "      <td>Clothing,Vests</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112973</th>\n",
       "      <td>2016-05-26</td>\n",
       "      <td>26</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>60</td>\n",
       "      <td>Adults (35-64)</td>\n",
       "      <td>F</td>\n",
       "      <td>Australia</td>\n",
       "      <td>Queensland</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Vests</td>\n",
       "      <td>Classic Vest, M</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>64</td>\n",
       "      <td>89</td>\n",
       "      <td>72</td>\n",
       "      <td>161</td>\n",
       "      <td>Clothing,Vests</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112985</th>\n",
       "      <td>2016-05-05</td>\n",
       "      <td>5</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>25</td>\n",
       "      <td>Young Adults (25-34)</td>\n",
       "      <td>M</td>\n",
       "      <td>Australia</td>\n",
       "      <td>New South Wales</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Vests</td>\n",
       "      <td>Classic Vest, L</td>\n",
       "      <td>14</td>\n",
       "      <td>24</td>\n",
       "      <td>64</td>\n",
       "      <td>444</td>\n",
       "      <td>336</td>\n",
       "      <td>780</td>\n",
       "      <td>Clothing,Vests</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113003</th>\n",
       "      <td>2016-05-23</td>\n",
       "      <td>23</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>20</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>F</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>England</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Vests</td>\n",
       "      <td>Classic Vest, M</td>\n",
       "      <td>15</td>\n",
       "      <td>24</td>\n",
       "      <td>64</td>\n",
       "      <td>562</td>\n",
       "      <td>360</td>\n",
       "      <td>922</td>\n",
       "      <td>Clothing,Vests</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113005</th>\n",
       "      <td>2016-05-03</td>\n",
       "      <td>3</td>\n",
       "      <td>May</td>\n",
       "      <td>2016</td>\n",
       "      <td>21</td>\n",
       "      <td>Youth (&lt;25)</td>\n",
       "      <td>M</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>England</td>\n",
       "      <td>Clothing</td>\n",
       "      <td>Vests</td>\n",
       "      <td>Classic Vest, S</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>64</td>\n",
       "      <td>112</td>\n",
       "      <td>72</td>\n",
       "      <td>184</td>\n",
       "      <td>Clothing,Vests</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5015 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Date  Day Month  Year  Customer_Age             Age_Group  \\\n",
       "5       2016-05-15   15   May  2016            47        Adults (35-64)   \n",
       "7       2016-05-22   22   May  2016            47        Adults (35-64)   \n",
       "21      2016-05-17   17   May  2016            29  Young Adults (25-34)   \n",
       "33      2016-05-23   23   May  2016            47        Adults (35-64)   \n",
       "73      2016-05-30   30   May  2016            38        Adults (35-64)   \n",
       "...            ...  ...   ...   ...           ...                   ...   \n",
       "112947  2016-05-23   23   May  2016            22           Youth (<25)   \n",
       "112973  2016-05-26   26   May  2016            60        Adults (35-64)   \n",
       "112985  2016-05-05    5   May  2016            25  Young Adults (25-34)   \n",
       "113003  2016-05-23   23   May  2016            20           Youth (<25)   \n",
       "113005  2016-05-03    3   May  2016            21           Youth (<25)   \n",
       "\n",
       "       Customer_Gender         Country             State Product_Category  \\\n",
       "5                    F       Australia   New South Wales      Accessories   \n",
       "7                    F       Australia          Victoria      Accessories   \n",
       "21                   M          Canada  British Columbia      Accessories   \n",
       "33                   F          Canada  British Columbia      Accessories   \n",
       "73                   F   United States        California      Accessories   \n",
       "...                ...             ...               ...              ...   \n",
       "112947               M       Australia          Victoria         Clothing   \n",
       "112973               F       Australia        Queensland         Clothing   \n",
       "112985               M       Australia   New South Wales         Clothing   \n",
       "113003               F  United Kingdom           England         Clothing   \n",
       "113005               M  United Kingdom           England         Clothing   \n",
       "\n",
       "       Sub_Category              Product  Order_Quantity  Unit_Cost  \\\n",
       "5        Bike Racks  Hitch Rack - 4-Bike               5         45   \n",
       "7        Bike Racks  Hitch Rack - 4-Bike               2         45   \n",
       "21       Bike Racks  Hitch Rack - 4-Bike               8         45   \n",
       "33       Bike Racks  Hitch Rack - 4-Bike              23         45   \n",
       "73       Bike Racks  Hitch Rack - 4-Bike               2         45   \n",
       "...             ...                  ...             ...        ...   \n",
       "112947        Vests      Classic Vest, S               6         24   \n",
       "112973        Vests      Classic Vest, M               3         24   \n",
       "112985        Vests      Classic Vest, L              14         24   \n",
       "113003        Vests      Classic Vest, M              15         24   \n",
       "113005        Vests      Classic Vest, S               3         24   \n",
       "\n",
       "        Unit_Price  Profit  Cost  Revenue                Category  \n",
       "5              120     297   225      522  Accessories,Bike Racks  \n",
       "7              120     100    90      190  Accessories,Bike Racks  \n",
       "21             120     590   360      950  Accessories,Bike Racks  \n",
       "33             120    1697  1035     2732  Accessories,Bike Racks  \n",
       "73             120     145    90      235  Accessories,Bike Racks  \n",
       "...            ...     ...   ...      ...                     ...  \n",
       "112947          64     159   144      303          Clothing,Vests  \n",
       "112973          64      89    72      161          Clothing,Vests  \n",
       "112985          64     444   336      780          Clothing,Vests  \n",
       "113003          64     562   360      922          Clothing,Vests  \n",
       "113005          64     112    72      184          Clothing,Vests  \n",
       "\n",
       "[5015 rows x 19 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cond = (data['Year'] == 2016) & (data['Month'] == 'May')\n",
    "# data.loc[cond].shape[0]\n",
    "df[cond]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0c81a68b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.91921157861212"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Customer age mean\n",
    "mn = df[\"Customer_Age\"].mean()\n",
    "mn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "68887592",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plotting a box plot of customer age\n",
    "df[\"Customer_Age\"].plot(kind=\"box\",vert=False,figsize=(8,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "772062a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j8jQ9vj9hfV053YOjNHcMhF2KiKQIBb/INCbO30/XgX0T1i+KD/Db3aIBfiISp+AXmcYzje2sXVhGZXFe2KWclXMWlJCTZew+quAXkTgFv8gUgyNj7DjckfbH9wHyc7I5Z36pBviJyJsU/CJTvHiog+HRca5Ylf7BD7C+rozdLRrgJyJxCn6RKZ5pbCc7y3jHsnlhl5IQ6xaV0943zBvdQ2GXIiIpQMEvMsWzTe2cX1dOaUFu2KUkxPq6MkAD/EQkTsEvMknf0Ci7jnRmxPH9CWsWlmGGBviJCKDgF3mLXUc6GR133rE8M7r5AYryclhZU6IBfiICKPhF3mLnkU4ANi6uDLeQBJu4gp+IiIJfZJKdhztYWVNMeVFmHN+fsL6unGNdg7T1aoCfSNQlNfjNbLOZ7TezBjO7Y5r5+Wb2QDB/m5ktC6Zfa2Y7zOyV4N/3TVrn58E2XwoetcncB4kOd2fn4U4uWpJZrX2Ij+wH2HNU3f0iUZe04DezbOBu4DpgLfAJM1s7ZbFbgQ53XwXcBdwZTG8DPuTu5wO3APdNWe9md78weLQmax8kWg6f6Ke9b5iLllSEXUrCrV2kkf0iEpfMFv8lQIO7N7n7MHA/sGXKMluAe4PnDwJXm5m5+053PxpM3wMUmll+EmsVYefhTgA2ZmCLv7wwl6VVRTrOLyJJDf464Mik183BtGmXcfdRoAuYeh7VbwMvuvvkg5PfDbr5/8LMLLFlS1TtPNxBUV78EreZaP2ico3sF5HUHtxnZuuId/9/ZtLkm4NDAO8KHr93knVvM7PtZrY9Foslv1hJe7uauzi/rpzsrMz8LrmurozDJ/rp6h8JuxQRCVEyg78FWDzpdX0wbdplzCwHKAfag9f1wEPAp9y9cWIFd28J/u0B/pn4IYW3cfd73H2Tu2+qqalJyA5J5hobd1493v3mILhMNHGL3j3H1N0vEmXJDP4XgNVmttzM8oCbgK1TltlKfPAewA3AU+7uZlYB/AS4w91/PbGwmeWYWXXwPBe4HtidxH2QiDjY3sfgyDhrFmZmNz/AumCA3x5194tEWtKCPzhmfzvwGLAP+L677zGzr5jZh4PFvg1UmVkD8AVg4pS/24FVwJennLaXDzxmZi8DLxHvMfhmsvZBomPfsXgYrllYFnIlyVNVks+i8gJe0ch+kUjLSebG3f1h4OEp07486fkgcOM0630V+OpJNntxImsUgXjw52QZq+eXhF1KUq2vK9cpfSIRl9KD+0Tmyt6j3aysKSE/JzvsUpJqQ305TW199AxqgJ9IVCn4RYB9x3oy+vj+hPV18QF+Oq1PJLoU/BJ5HX3DHO8efPPqdpns/DeDX939IlGl4JfIi8LAvglVJfnUVRTysoJfJLIU/BJ5+9/oAeDcBZnf1Q/xVv8rzZ1hlyEiIVHwS+Q1xnopLcihpiQat4M4v76cg+39dA1ogJ9IFCn4JfKaYn2srCkhKrd9mDjOv0fd/SKRpOCXyGuM9bKyJrPP359sIvh1IR+RaFLwS6T1DI7wRvcQK2uLwy5lzlQW51FfqQF+IlGl4JdIa4r1AUSqxQ/xVr9O6ROJJgW/RFpjrBeIYPDXl3OoXbfoFYkiBb9EWmOsl5wsY2lVUdilzCkd5xeJLgW/RFpTrI8l84rIzY7Wr4KCXyS6ovXXTmSKxlgvKyLWzQ9QUZTH4nmFvNLSGXYpIjLHFPwSWaNj4xxs64/UiP7JNtRVqMUvEkEKfoms5o4BhsfGIzewb8L6unKOnBigo2847FJEZA4p+CWyojqif8KGeh3nF4kiBb9E1m/O4Y9mV//6RcEteo8q+EWiRMEvkdUY66W6JI+KorywSwlFeVEui+cVsqelO+xSRGQOKfglshpjvayojmY3/4Tz68rV1S8SMQp+iazGWF9kR/RPWLeonMMndAU/kShR8Esknegb5kTfcGQH9k1YP3GLXh3nF4kMBb9EUlPER/RPWL+oDNAAP5EoUfBLJEX1rnxTVZXks6i8gN0a4CcSGQp+iaTGWC95OVnUVRaGXUro1usWvSKRouCXSGpo7WV5VTHZWRZ2KaFbX1dOU1sfPYMa4CcSBQp+iaSGWC+raqPdzT9hfV38OP++Yz0hVyIic0HBL5EzODLGkRP9rFTwA78Z2a/z+UWiQcEvkXOgrY9xRy3+QG1pAbWl+exR8ItEgoJfIqehNX4q36qIj+ifTFfwE4kOBb9ETkNrL2awIqI355nOurpyGmO99A+Phl2KiCSZgl8ipzHWy+LKIgpys8MuJWVsqCtn3NH5/CIRMKvgN7MfmtlvmdlpfVEws81mtt/MGszsjmnm55vZA8H8bWa2LJh+rZntMLNXgn/fN2mdi4PpDWb2t2am87HktDS0akT/VBuXVgKw/dCJkCsRkWSbbZD/PfC7wOtm9l/N7NyZVjCzbOBu4DpgLfAJM1s7ZbFbgQ53XwXcBdwZTG8DPuTu5wO3APdNWucfgD8AVgePzbPcBxHGxp2mtj4F/xTzivNYUVPMi4c6wi5FRJJsVsHv7k+6+83ARuAg8KSZPWNm/4eZ5Z5ktUuABndvcvdh4H5gy5RltgD3Bs8fBK42M3P3ne5+NJi+BygMegcWAmXu/py7O/BPwEdmt6si0NzRz/DouAb2TePiJZXsONRB/FdLRDLVrLvuzawK+DTwfwI7ga8T/yLwxElWqQOOTHrdHEybdhl3HwW6gKopy/w28KK7DwXLN8+wzYl6bzOz7Wa2PRaLnXLfJDr2H49fpGbVfAX/VBcvraSjf4QDbX1hlyIiSTTbY/wPAb8Cioh3wX/Y3R9w9/8IJO0vqJmtI979/5nTXdfd73H3Te6+qaamJvHFSVrad6wHMzhvQWnYpaSci4Pj/DvU3S+S0Wbb4v+mu691979292MQH5gH4O6bTrJOC7B40uv6YNq0y5hZDlAOtAev64GHgE+5e+Ok5etn2KbISe071s2yqmKK8nLCLiXlrKwpobwwlxcPK/hFMtlsg/+r00x7doZ1XgBWm9lyM8sDbgK2TllmK/HBewA3AE+5u5tZBfAT4A53//XEwsGXjm4zuywYzf8p4N9muQ8i7DvezZqFau1PJyvLuHhpJc8f0Mh+kUx2yuA3swVmdjHxwXUXmdnG4PEe4t3+JxUcs78deAzYB3zf3feY2VfM7MPBYt8GqsysAfgCMHHK3+3AKuDLZvZS8KgN5v0R8C2gAWgEHjm9XZao6h0a5VB7P2sWlIVdSsq6bMU8GmN9tHYPhl2KiCTJTP2dHyA+oK8e+Nqk6T3An860cXd/GHh4yrQvT3o+CNw4zXpfZfpeBtx9O7B+pvcWmWr/8fjFadYsVPCfzGUr4mNrn21qZ8uF046bFZE0d8rgd/d7gXvN7Lfd/V/nqCaRpNgb3HZ2zSIF/8msW1ROaUEOzyn4RTLWKYPfzD7p7v8LWGZmX5g6392/Ns1qIilp5+EOqkvyWFReEHYpKSs7y7h0+Tyea9JxfpFMNdPgvom7mJQApdM8RNLGzsOdXLSkEl3l+dQuW1HFgbY+jnfpOL9IJpqpq/8bwb9/NTfliCTHib5hDrT18TubFs+8cMRdvnLiOH8bH72ofoalRSTdzPYCPv/NzMrMLNfMfmpmMTP7ZLKLE0mUiWvQb1xSEW4haWDNgjLKC3N5trE97FJEJAlmex7/+929G7ie+LX6VwF/nKyiRBLtxcMd5GQZG+orwi4l5WXpOL9IRptt8E8cEvgt4Afu3pWkekSS4sXDHaxdVEZhXnbYpaSFy1dWcfhEPy2dA2GXIiIJNtvg/7GZvQpcDPzUzGoAjfyRtDA6Ns6uI11sXFIZdilp483j/OruF8k4s70t7x3AFcAmdx8B+nj7LXZFUtKrx3sYGBnjIh3fn7VzakupLNJxfpFMdDp3KjmP+Pn8k9f5pwTXI5JwEzedmbj7nMwsK8u4bEUVzzW14+46BVIkg8wq+M3sPmAl8BIwFkx2FPySBl481EFtaT51FYVhl5JWLl9ZxSO7j9PcMcDieae8NYeIpJHZtvg3AWvd3ZNZjEgy7DjcwUZduOe0XR5ct/+ZxjY+Pm9JyNWISKLMdnDfbmBBMgsRSYZYzxBHTgywcWlF2KWknVW1JdSW5vN0g47zi2SS2bb4q4G9ZvY8MDQx0d0/fPJVRMK38/DEhXt0fP90mRlXrq7m5/tjjI87WVnqMRHJBLMN/r9MZhEiybKruZPsLGN9XXnYpaSld62u5ocvtrD3WLf+D0UyxGxP5/sF8Sv25QbPXwBeTGJdIgmx60gX584vpSBXF+45E+9cVQ3AL1+PhVyJiCTKbK/V/wfAg8A3gkl1wI+SVJNIQoyPOy83d3LB4oqwS0lbtaUFnLeglKdfbwu7FBFJkNkO7vss8E6gG8DdXwdqk1WUSCIcbO+je3CUC+rVRX023rW6mu0HO+gbGg27FBFJgNkG/5C7D0+8CC7io1P7JKW93By/pYRa/Gfn6jXzGR4b52f7W8MuRUQSYLbB/wsz+1Og0MyuBX4A/HvyyhI5e7tbusjPyWJ1bUnYpaS1dyybR1VxHo/uPh52KSKSALMN/juAGPAK8BngYeDPk1WUSCK83trLypoScrJn+2Mu08nOMt6/bj4/e7WVwZGxmVcQkZQ221H948QH8/2Ru9/g7t/UVfwk1TW09rJ6vlr7iXDd+oX0DY/x1Kvq7hdJd6cMfov7SzNrA/YD+80sZmZfnpvyRM5M79AoLZ0D6uZPkHeuqqauopD/9dyhsEsRkbM0U4v/88RH87/D3ee5+zzgUuCdZvb5pFcncoYaW3sBWFVbGnIlmSE7y/jdS5fwTGM7DcH/rYikp5mC//eAT7j7gYkJ7t4EfBL4VDILEzkbE+Gkrv7E+Z1Ni8nLzuIbv2gMuxQROQszBX+uu7/tyh3uHgNyk1OSyNl7vbWX3GxjqW4nmzA1pfl86vKlPPhiM/uOdYddjoicoZmCf/gM54mEqqG1h+XVxRrRn2C3v28Vpfk5/D9b9zA2rvG9Iulopr+KF5hZ9zSPHuD8uShQ5EwcPtHP0qrisMvIOBVFefz59Wt5/sAJvvWrprDLEZEzcMrgd/dsdy+b5lHq7urql5Tk7rR0DFBXURh2KRnpxovr2bxuAX/z+H72HO0KuxwROU3qB5WM0zUwQt/wGPWVCv5kMDP++mPnU1mUx+cfeEkX9RFJMwp+yTjNHQMACv4kqizO484bNvDaG7383VMNYZcjIqchqcFvZpvNbL+ZNZjZHdPMzzezB4L528xsWTC9ysx+Zma9ZvZ3U9b5ebDNl4KH7hIobzER/HUVGtGfTO89t5YtFy7im79q4mjnQNjliMgsJS34zSwbuBu4DlgLfMLM1k5Z7Fagw91XAXcBdwbTB4G/AL54ks3f7O4XBg9dQ1TeoiUIoTq1+JPui+8/FwfueuK1sEsRkVlKZov/EqDB3ZuCW/reD2yZsswW4N7g+YPA1WZm7t7n7k8T/wIgclpaOgYozM2mskjjT5Nt8bwifveSJfzopRZau/XrKpIOkhn8dcCRSa+bg2nTLuPuo0AXUDWLbX836Ob/CzOzRBQrmaOls5/6ykL0ozE3Pn3FMkbHne9tOxx2KSIyC+k4uO9mdz8feFfw+L3pFjKz28xsu5ltj8Vic1qghKu5Y0Dd/HNoWXUx7z23lu9tO8zI2HjY5YjIDJIZ/C3A4kmv64Np0y5jZjlAOdB+qo26e0vwbw/wz8QPKUy33D3uvsndN9XU1JzRDkh6Otqpc/jn2icuWUJb7xC/el1fskVSXTKD/wVgtZktN7M84CZg65RltgK3BM9vAJ5y95NeB9TMcsysOnieC1wP7E545ZK2hkbH6OgfYUFZQdilRMpV59RQWZTLQzuPhl2KiMwgJ1kbdvdRM7sdeAzIBr7j7nvM7CvAdnffCnwbuM/MGoATxL8cAGBmB4EyIM/MPgK8HzgEPBaEfjbwJPDNZO2DpJ+23vgtJGpK80OuJFrycrK4fsMivr/9CD2DI5QWaGClSKpKWvADuPvDwMNTpn150vNB4MaTrLvsJJu9OFH1SeZp6xkCoLpEwT/XPnJRHfc9d4hHdx/nxk2LZ15BREKRjoP7RE4qFgS/Wvxzb+OSCpZVFfHQzqlDeUQklSj4JaO09Sr4w2JmfOSiOp5taudYl67kJ5KqFPySUSZa/FUleSFXEk0fvagOd/iRBvmJpCwFv2SUWO8Q5YW55Odkh11KJC2tKubipZX88MVmTnGCjoiESMEvGaWtd0jd/CH76EV1vN7ay56j3WGXIiLTUPBLRon1DFGtbv5QXb9hIXnZWTy4oznsUkRkGgp+ySixniFqSnXxnjBVFOVx3fkLeHBHMz2DI2GXIyJTKPglo7T1DlOjc/hDd+uVy+kdGuWBF47MvLCIzCkFv2SMgeExeodGdYw/BWyor+CSZfP47q8PMqob94ikFAW/ZIyJc/h1jD81/P6Vy2npHODRPcfDLkVEJlHwS8Zo74tfp1/n8KeGa9fOZ1lVEd/8ZZNO7RNJIQp+yRhdA/GBZOWFukFMKsjOMm591wp2NXfxwsGOsMsRkYCCXzKGgj/13LCxnsqiXO75ZVPYpYhIQMEvGWMi+MsU/CmjMC+b37t8GT999Q2aYr1hlyMiKPglg3SrxZ+SPnnZErLM+NcXdUEfkVSg4JeM0TUwQkFulq7Tn2JqSwu4clU1P9p5lPFxDfITCZuCXzJGZ/8wFYUa0Z+KPnpRHS2dA7xw8ETYpYhEnoJfMkbXwIi6+VPU+9fNpzA3mx+/fCzsUkQiT8EvGUPBn7qK8nJ456pqnnq1Vef0i4RMwS8Zo2tgVCP6U9jVa2pp6Rzg9VaN7hcJk4JfMka3Wvwp7b3n1gLw032tIVciEm0KfskY6upPbQvKC1i3qIynXn0j7FJEIk3BLxlhZGyc3qFRBX+Ku/q8WnYc6qAjuK+CiMw9Bb9khImL91QUKfhT2XvOq2Xc4emGtrBLEYksBb9kBF2nPz1cUF9BeWEuv3gtFnYpIpGl4JeMoOBPD9lZxrtWV/OL12I6rU8kJAp+yQi6QU/6uOqcGmI9Q+w71hN2KSKRpOCXjKAWf/q46pwaAHX3i4REwS8ZQXfmSx+1ZQWsWVjGL17T+fwiYVDwS0bo7Ffwp5Orzqlh+8EOeodGwy5FJHIU/JIRugZGKMzNJi9HP9Lp4Kpzahgdd57RaX0ic05/JSUjdA2M6Bz+NHLx0kqK87J1nF8kBEkNfjPbbGb7zazBzO6YZn6+mT0QzN9mZsuC6VVm9jMz6zWzv5uyzsVm9kqwzt+amSVzHyQ96HK96SUvJ4srVum0PpEwJC34zSwbuBu4DlgLfMLM1k5Z7Fagw91XAXcBdwbTB4G/AL44zab/AfgDYHXw2Jz46iXddA2M6FS+NHPVOTU0dwzQ1NYXdikikZLMFv8lQIO7N7n7MHA/sGXKMluAe4PnDwJXm5m5e5+7P038C8CbzGwhUObuz3m8mfBPwEeSuA+SJtTiTz9vnta3X939InMpmcFfBxyZ9Lo5mDbtMu4+CnQBVTNss3mGbQJgZreZ2XYz2x6L6Q9LptMtedPP4nlFrKgp1nF+kTmWsYP73P0ed9/k7ptqamrCLkeSrFPBn5auOqeG55raGRwZC7sUkchIZvC3AIsnva4Ppk27jJnlAOVA+wzbrJ9hmxIxI2Pj9A+PKfjT0HvOrWVodJxnG0/1ay8iiZTM4H8BWG1my80sD7gJ2Dplma3ALcHzG4Cn/BRDfN39GNBtZpcFo/k/Bfxb4kuXdNKlW/KmrctWzKM4L5sn9r0RdikikZG04A+O2d8OPAbsA77v7nvM7Ctm9uFgsW8DVWbWAHwBePOUPzM7CHwN+LSZNU86I+CPgG8BDUAj8Eiy9kHSg67Tn77yc7K56twantz7BuPjOq1PZC7kJHPj7v4w8PCUaV+e9HwQuPEk6y47yfTtwPrEVSnpTnfmS2/XrJnPw68c55WWLi5YXBF2OSIZL2MH90l0qMWf3t53Xi3ZWcaT6u4XmRMKfkl7ujNfeqsoymPT0kqe2KvgF5kLCn5Je7ozX/q7du18Xj3ew5ET/WGXIpLxFPyS9tTVn/6uXTsfQK1+kTmg4Je01zUwQnFeNrnZ+nFOV0urilldW6Lj/CJzQH8pJe3pOv2Z4dq189l24ARdwaEbEUkOBb+kPd2ZLzNcs3Y+Y+POz19rDbsUkYym4Je0pxZ/ZriwvoLqknwd5xdJMgW/pL2ufgV/JsjKMq5ZU8sv9scYHh0PuxyRjKXgl7SnFn/muGbNfHqGRtl2QDftEUkWBb+kPQV/5rhydTUFuVnq7hdJIgW/pLXh0XEGRsZ0Z74MUZCbzbtWx2/ac4obdYrIWVDwS1rTxXsyz7Vr5nO0a5C9x7rDLkUkIyn4Ja3pznyZ531rajGDx/eou18kGRT8ktbU4s881SX5vGPZPB7dfTzsUkQykoJf0lrXwDCg4M80H1y/gP1v9NDQ2ht2KSIZR8EvaU0t/sy0ef1CAB7dfSzkSkQyj4Jf0lqXbsmbkRaUF7BxSQWPqLtfJOEU/JLWugZGAQV/Jrpu/UL2HO3mUHtf2KWIZBQFv6S1roERSvJzyNEteTPO5vULANTqF0kw/bWUtKar9mWuxfOK2FBfziOv6Di/SCIp+CWtdQ0M6xz+DPahDYvY1dzF62/0hF2KSMZQ8Etai7f4c8IuQ5LkoxvryM027n/hSNiliGQMBb+kNXX1Z7bqknyuXTufH77YzNDoWNjliGQEBb+kNQV/5rvpHUvo6B/RJXxFEkTBL2lNwZ/5rlxVzdKqIr719AHdsU8kART8kraGRscYHBmnoigv7FIkibKyjNvevYJdRzp5trE97HJE0p6CX9KW7swXHb+9sZ7a0nzu/nlD2KWIpD0Fv6QtXa43Ogpys/mDd63g1w3t7Dh0IuxyRNKagl/Slm7QEy03X7aE6pI8vvbEa2GXIpLWFPyStjqCFn9lkYI/CorycvgP71nFrxvadaxf5CwkNfjNbLOZ7TezBjO7Y5r5+Wb2QDB/m5ktmzTvS8H0/Wb2gUnTD5rZK2b2kpltT2b9kto6+4cBqNTgvsi4+dIlLCgr4GtP7NcIf5EzlLTgN7Ns4G7gOmAt8AkzWztlsVuBDndfBdwF3Bmsuxa4CVgHbAb+PtjehPe6+4XuvilZ9Uvq6wxa/BVq8UdGQW42n33fKl442MEvX28LuxyRtJTMFv8lQIO7N7n7MHA/sGXKMluAe4PnDwJXm5kF0+939yF3PwA0BNsTeVNH/zA5WUZJvi7ZGyUf37SYuopCvva4Wv0iZyKZwV8HTL7AdnMwbdpl3H0U6AKqZljXgcfNbIeZ3ZaEuiVNdPSPUFGUS/y7okRFXk4Wn7t6Nbuau3hyX2vY5YiknXQc3Helu28kfgjhs2b27ukWMrPbzGy7mW2PxWJzW6HMic7+YV28J6I+trGOZVVFfO2J1xgfV6tf5HQkM/hbgMWTXtcH06ZdxsxygHKg/VTruvvEv63AQ5zkEIC73+Pum9x9U01NzVnvjKSejv5hjeiPqJzsLD5/7TnsO9bNI7uPh12OSFpJZvC/AKw2s+Vmlkd8sN7WKctsBW4Jnt8APOXxg3ZbgZuCUf/LgdXA82ZWbGalAGZWDLwf2J3EfZAU1tk/ohZ/hF2/YRGra0u468nXGFOrX2TWkhb8wTH724HHgH3A9919j5l9xcw+HCz2baDKzBqALwB3BOvuAb4P7AUeBT7r7mPAfOBpM9sFPA/8xN0fTdY+SGpTiz/asrOMz12zmobWXh7fo1a/yGwldTi0uz8MPDxl2pcnPR8EbjzJuv8F+C9TpjUBFyS+Ukk37k5H/4jO4Y+469YvZFnVfv7nLxrZvH6BBnqKzEI6Du4TYWBkjOFR3Zkv6rKzjNvevZJdzV0826Sr+YnMhoJf0pIu1ysTPraxjuqSfP7h541hlyKSFhT8kpY6+uKX61WLXwpys/n9K5fxq9fb2N3SFXY5IilPwS9pqVMtfpnk5kuXUpKfwzd+2RR2KSIpT8EvaalzILhBT7Fa/BK/NfPNly3hJy8f5VB7X9jliKQ0Bb+kpQ7doEemuPWdy8nJyuKbv1KrX+RUFPySlk706pa88la1ZQV8bGMdP9jeTKxnKOxyRFKWgl/SUqx3kMqiXHKz9SMsv3Hbu1cwPDbOPz5zIOxSRFKW/mpKWmrrGaamND/sMiTFrKgpYfO6Bdz37CF6h0bDLkckJSn4JS3FeoeoLlHwy9v9h/espHtwlLt/1hB2KSIpScEvaSnWM6QWv0xrQ30FN1xczzd/2cT+4z1hlyOSchT8kpba1OKXU/jTD66htCCHP33oFcZ15z6Rt1DwS9rpGxqlf3hMLX45qXnFefzF9WvZcaiD7z5zMOxyRFKKgl/SzsSpWmrxy6l89KI6rj6vlv/+2Ks0xXrDLkckZSj4Je209caDXy1+ORUz4//92Pnk52Tzxw++zJi6/EUABb+koWNdgwDML1Pwy6nNLyvgrz68jh2HOvjO0zq3XwQU/JKGjnYOAFBXURhyJZIOtly4iGvW1PI/nnztzd4ikShT8EvaaekcoKwgh9ICXadfZmZmfOmDaxgcHefvntK5/SIKfkk7RzsHWKTWvpyGlTUl/M6mer637RBHTvSHXY5IqBT8knZaOgfVzS+n7XNXn0OWGX/709fDLkUkVAp+STtHOweoq1Twy+lZUF7AzZcu5Yc7WzjU3hd2OSKhUfBLWukdGqVrYERd/XJG/vCqFeRkGf+/jvVLhCn4Ja1MXIhlWVVxyJVIOqoti7f6H9rZwsE2tfolmhT8klZefyMe/Kvnl4RciaSrP3yPWv0SbQp+SSuvt/aSm20snVcUdimSpmpLC/jkZUv50Utq9Us0KfglrTS09rK8upicbP3oypn7zFUryM1Wq1+iSX89Ja283trDqlp188vZqS0t4JOXLuWhnc28eLgj7HJE5pSCX9JGrGeIQ+39bKivCLsUyQD/8erVLCwv5PMPvETP4EjY5YjMGQW/pI3tB08AcMnyeSFXIpmgvDCXuz5+Ic0dA9z6j9vp7B8OuySROaHgl7Tx/METFORmsX5RedilSIa4ZPk8vn7Thew80sH77/ol33n6AK3dg2GXJZJUOWEXIDIb4+PO43ve4JLlVeTl6PuqJM71GxaxZF4RX/3xPr7y47185cd7WVVbwpqFZaxZWMqaBWWsqi1hUUUh2VkWdrkiZ03BL2nhuQPttHQO8Cebzw27FMlAG+oreOAzl/Hq8R6eerWVnYc7efFQB/++6+iby+TnZLG8upiVNSWsrClmZW0JK6pLWFFTTHG+/pRK+kjqT6uZbQa+DmQD33L3/zplfj7wT8DFQDvwcXc/GMz7EnArMAb8J3d/bDbblMwzPu7c9cRrVBTl8oF1C8IuRzKUmQWt/LI3p3X1j7D/jR6aYr00xnppjPWx52gXj+w+xrj/Zt2F5QXUVxZSVZxPVUkeVSX5VJfkUVOST21ZPrWlBdSU5lOQmx3Cnom8VdKC38yygbuBa4Fm4AUz2+rueyctdivQ4e6rzOwm4E7g42a2FrgJWAcsAp40s3OCdWbapmSQzv5h7nz0VV442MF/u2GD/nDKnCovyuWS5fPeNqB0aHSMQ+39NLb20tTWR0NrL8e6BmiM9fL8wWE6+odxf/v2ygpyqC7Nx4Bxh7Hg24MT/7cwN5vi/BxKgsfbn2dTUpBDcV58Wk52Fl0DI3T2D3Oib5j2vmHae4fpGRwhLyeLgtxsygpyqSzKpaI4L/5vYR4VRblUBq8Lc7Mx0yGMKElmi/8SoMHdmwDM7H5gCzA5pLcAfxk8fxD4O4v/BG4B7nf3IeCAmTUE22MW20yqP33oFfYd637z9dRf7rf9rk9ZYOr86f44+JSl3vYeM7ynT7fRGd53xvec4T3evt/TvOdpbmNkdJyjXfGBVn941UpuvLj+7RsVCUF+TjbnzC/lnPml084fHRvnRP8wsZ4hWnuGiHUPEesdorV7kLa+YXDIyjKyjbeE7sDwGL1Do/QMjnK8a5C+oVF6hkbpGxp9Sw/DyevKorokn9KCHIZHxxkcGaN7cJTeodGTrpOXk0VlUS6VRXnkBhfGmijpzcqCCfbWl5JA129YxK1XLp+T90pm8NcBRya9bgYuPdky7j5qZl1AVTD9uSnr1gXPZ9omAGZ2G3AbwJIlS85sD6ZRlJtNyZTjeVO/LU/9nZj6SzLd78zpbmPqEjO9x3S/qDbTNt62zVO/ydvf8+1vejr/N1lZxrKqYq5ZM5+1i8oQSRc52VnUlhZQW1rAugRsz90ZHBmnZ2iEvqEx+obiYT4yNk5FYR7lhbnMK8mjOG/61vvw6DidA8N09o/Q0TdMR3+8l+A3/8bnjY77m1/I/c33ZsrrWXwDkdOWP4eDljN2RIq73wPcA7Bp06aE/aT++fVrE7UpEZFZMTMK87IpzMuG6TsZTikv5zdfRESS+RWjBVg86XV9MG3aZcwsBygnPsjvZOvOZpsiIiJyEskM/heA1Wa23MzyiA/W2zplma3ALcHzG4CnPN6PtBW4yczyzWw5sBp4fpbbFBERkZNIWld/cMz+duAx4qfefcfd95jZV4Dt7r4V+DZwXzB47wTxICdY7vvEB+2NAp919zGA6baZrH0QERHJNBaFgRqbNm3y7du3h12GiIjInDCzHe6+abp5uvapiIhIhCj4RUREIkTBLyIiEiEKfhERkQhR8IuIiESIgl9ERCRCFPwiIiIRouAXERGJEAW/iIhIhETiyn1mFgMOncGq1UBbgstJRdrPzKL9zCzaz8wyV/u51N1rppsRieA/U2a2/WSXPMwk2s/Mov3MLNrPzJIK+6mufhERkQhR8IuIiESIgv/U7gm7gDmi/cws2s/Mov3MLKHvp47xi4iIRIha/CIiIhGi4J+Gmf13M3vVzF42s4fMrGLSvC+ZWYOZ7TezD4RYZkKY2eZgXxrM7I6w60kUM1tsZj8zs71mtsfMPhdMn2dmT5jZ68G/lWHXerbMLNvMdprZj4PXy81sW/CZPmBmeWHXmAhmVmFmDwa/m/vM7PJM+zzN7PPBz+tuM/sXMyvIlM/TzL5jZq1mtnvStGk/P4v722CfXzazjeFVfnpOsp8plSkK/uk9Aax39w3Aa8CXAMxsLXATsA7YDPy9mWWHVuVZCmq/G7gOWAt8ItjHTDAK/N/uvha4DPhssG93AD9199XAT4PX6e5zwL5Jr+8E7nL3VUAHcGsoVSXe14FH3f084ALi+5wxn6eZ1QH/Cdjk7uuBbOJ/bzLl8/xH4n83JzvZ53cdsDp43Ab8wxzVmAj/yNv3M6UyRcE/DXd/3N1Hg5fPAfXB8y3A/e4+5O4HgAbgkjBqTJBLgAZ3b3L3YeB+4vuY9tz9mLu/GDzvIR4SdcT3795gsXuBj4RSYIKYWT3wW8C3gtcGvA94MFgk7fcRwMzKgXcD3wZw92F37yTDPk8gByg0sxygCDhGhnye7v5L4MSUySf7/LYA/+RxzwEVZrZwTgo9S9PtZ6plioJ/Zr8PPBI8rwOOTJrXHExLV5m2P9Mys2XARcA2YL67HwtmHQfmh1VXgvwP4E+A8eB1FdA56Y9Mpnymy4EY8N3gsMa3zKyYDPo83b0F+BvgMPHA7wJ2kJmf54STfX6Z/Lcp9EyJbPCb2ZPBcbSpjy2Tlvkz4l3G3wuvUjkbZlYC/Cvwf7l79+R5Hj+lJW1PazGz64FWd98Rdi1zIAfYCPyDu18E9DGlWz8DPs9K4i3A5cAioJi3dxlnrHT//GYjVTIlJ8w3D5O7X3Oq+Wb2aeB64Gr/zTmPLcDiSYvVB9PSVabtz1uYWS7x0P+eu/8wmPyGmS1092NB12FreBWetXcCHzazDwIFQBnx4+AVZpYTtBIz5TNtBprdfVvw+kHiwZ9Jn+c1wAF3jwGY2Q+Jf8aZ+HlOONnnl3F/m1IpUyLb4j8VM9tMvPv0w+7eP2nWVuAmM8s3s+XEB548H0aNCfICsDoYNZxHfJDJ1pBrSojgWPe3gX3u/rVJs7YCtwTPbwH+ba5rSxR3/5K717v7MuKf3VPufjPwM+CGYLG03scJ7n4cOGJm5waTrgb2kkGfJ/Eu/svMrCj4+Z3Yx4z7PCc52ee3FfhUMLr/MqBr0iGBtJNymeLuekx5EB9gcQR4KXj8z0nz/gxoBPYD14VdawL29YPER5k2An8Wdj0J3K8riXcbvjzpc/wg8WPgPwVeB54E5oVda4L29z3Aj4PnK4j/8WgAfgDkh11fgvbxQmB78Jn+CKjMtM8T+CvgVWA3cB+QnymfJ/AvxMcujBDvwbn1ZJ8fYMTPOGoEXiF+pkPo+3AW+5lSmaIr94mIiESIuvpFREQiRMEvIiISIQp+ERGRCFHwi4iIRIiCX0REJEIU/CIiIhGi4BcREYkQBb+IiEiE/G/d7sqeXZN+ZgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plotting a density curve of customer_age\n",
    "df[\"Customer_Age\"].plot(kind = \"density\", figsize = (8,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "76fa5d8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.901659648253654"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### Mean order quantity\n",
    "df[\"Order_Quantity\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "972fca66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Order_Quantity box plot\n",
    "df[\"Order_Quantity\"].plot(kind=\"box\",vert=True,figsize=(8,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "96f0df0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 8, 23, 20,  4,  5,  2, 22, 21,  7,  1,  6,  9,  3, 24, 25, 10, 11,\n",
       "       12, 14, 28, 27, 15, 13, 17, 16, 30, 29, 26, 19, 18, 31, 32],\n",
       "      dtype=int64)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Order_Quantity\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7d933df8",
   "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": [
    "### Plotting the histogram of order quantity\n",
    "plt.hist(df[\"Order_Quantity\"],bins = 30,density=True, edgecolor=\"black\")\n",
    "plt.xlabel(\"Order Quantity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f746c636",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sales in year 2011 : 2677\n",
      "Sales in year 2012 : 2677\n",
      "Sales in year 2013 : 24443\n",
      "Sales in year 2014 : 29398\n",
      "Sales in year 2015 : 24443\n",
      "Sales in year 2016 : 29398\n"
     ]
    }
   ],
   "source": [
    "### Sales per year do we have\n",
    "year = np.sort(df[\"Year\"].unique())\n",
    "sales = df.groupby(\"Year\").count()\n",
    "pro_sale = list(sales[\"Product\"])\n",
    "for i in range (0,len(year)):\n",
    "    print(f\"Sales in year {year[i]} : {pro_sale[i]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aca8cbe1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Pie plot for sales\n",
    "df[\"Year\"].value_counts().plot(kind=\"pie\",figsize=(8,6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "72d4a898",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sales in year April : 10182\n",
      "Sales in year August : 8200\n",
      "Sales in year December : 11200\n",
      "Sales in year February : 9022\n",
      "Sales in year January : 9284\n",
      "Sales in year July : 7462\n"
     ]
    }
   ],
   "source": [
    "### Sales per month\n",
    "month = np.sort(df[\"Month\"].unique())\n",
    "sales = df.groupby(\"Month\").count()\n",
    "pro_sale = list(sales[\"Product\"])\n",
    "for i in range (0,len(year)):\n",
    "    print(f\"Sales in year {month[i]} : {pro_sale[i]}\")\n",
    "### Or can use - df[\"Month\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9294daf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "United States    39206\n",
       "Name: Country, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Which country has the most sales quantity of sales?\n",
    "max_sale = df[\"Country\"].value_counts().head(1)\n",
    "max_sale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c6533e83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Plotting the countries\n",
    "df[\"Country\"].value_counts().plot(kind=\"bar\",figsize=(8,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6c60408d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Hitch Rack - 4-Bike',\n",
       " 'All-Purpose Bike Stand',\n",
       " 'Mountain Bottle Cage',\n",
       " 'Water Bottle - 30 oz.',\n",
       " 'Road Bottle Cage',\n",
       " 'AWC Logo Cap',\n",
       " 'Bike Wash - Dissolver',\n",
       " 'Fender Set - Mountain',\n",
       " 'Half-Finger Gloves, L',\n",
       " 'Half-Finger Gloves, M',\n",
       " 'Half-Finger Gloves, S',\n",
       " 'Sport-100 Helmet, Black',\n",
       " 'Sport-100 Helmet, Red',\n",
       " 'Sport-100 Helmet, Blue',\n",
       " 'Hydration Pack - 70 oz.',\n",
       " 'Short-Sleeve Classic Jersey, XL',\n",
       " 'Short-Sleeve Classic Jersey, L',\n",
       " 'Short-Sleeve Classic Jersey, M',\n",
       " 'Short-Sleeve Classic Jersey, S',\n",
       " 'Long-Sleeve Logo Jersey, M',\n",
       " 'Long-Sleeve Logo Jersey, XL',\n",
       " 'Long-Sleeve Logo Jersey, L',\n",
       " 'Long-Sleeve Logo Jersey, S',\n",
       " 'Mountain-100 Silver, 38',\n",
       " 'Mountain-100 Silver, 44',\n",
       " 'Mountain-100 Black, 48',\n",
       " 'Mountain-100 Silver, 48',\n",
       " 'Mountain-100 Black, 38',\n",
       " 'Mountain-200 Silver, 38',\n",
       " 'Mountain-100 Black, 44',\n",
       " 'Mountain-100 Silver, 42',\n",
       " 'Mountain-200 Black, 46',\n",
       " 'Mountain-200 Silver, 42',\n",
       " 'Mountain-200 Silver, 46',\n",
       " 'Mountain-200 Black, 38',\n",
       " 'Mountain-100 Black, 42',\n",
       " 'Mountain-200 Black, 42',\n",
       " 'Mountain-400-W Silver, 46',\n",
       " 'Mountain-500 Silver, 40',\n",
       " 'Mountain-500 Silver, 44',\n",
       " 'Mountain-500 Black, 48',\n",
       " 'Mountain-500 Black, 40',\n",
       " 'Mountain-400-W Silver, 42',\n",
       " 'Mountain-500 Silver, 52',\n",
       " 'Mountain-500 Black, 52',\n",
       " 'Mountain-500 Silver, 42',\n",
       " 'Mountain-500 Black, 44',\n",
       " 'Mountain-500 Silver, 48',\n",
       " 'Mountain-400-W Silver, 38',\n",
       " 'Mountain-400-W Silver, 40',\n",
       " 'Mountain-500 Black, 42',\n",
       " 'Road-150 Red, 48',\n",
       " 'Road-150 Red, 62',\n",
       " 'Road-750 Black, 48',\n",
       " 'Road-750 Black, 58',\n",
       " 'Road-750 Black, 52',\n",
       " 'Road-150 Red, 52',\n",
       " 'Road-150 Red, 44',\n",
       " 'Road-150 Red, 56',\n",
       " 'Road-750 Black, 44',\n",
       " 'Road-350-W Yellow, 40',\n",
       " 'Road-350-W Yellow, 42',\n",
       " 'Road-250 Black, 44',\n",
       " 'Road-250 Black, 48',\n",
       " 'Road-350-W Yellow, 48',\n",
       " 'Road-550-W Yellow, 44',\n",
       " 'Road-550-W Yellow, 38',\n",
       " 'Road-250 Black, 52',\n",
       " 'Road-550-W Yellow, 48',\n",
       " 'Road-250 Red, 58',\n",
       " 'Road-250 Black, 58',\n",
       " 'Road-250 Red, 52',\n",
       " 'Road-250 Red, 48',\n",
       " 'Road-250 Red, 44',\n",
       " 'Road-550-W Yellow, 42',\n",
       " 'Road-550-W Yellow, 40',\n",
       " 'Road-650 Red, 48',\n",
       " 'Road-650 Red, 60',\n",
       " 'Road-650 Black, 48',\n",
       " 'Road-350-W Yellow, 44',\n",
       " 'Road-650 Red, 52',\n",
       " 'Road-650 Black, 44',\n",
       " 'Road-650 Red, 62',\n",
       " 'Road-650 Red, 58',\n",
       " 'Road-650 Black, 60',\n",
       " 'Road-650 Black, 58',\n",
       " 'Road-650 Black, 52',\n",
       " 'Road-650 Black, 62',\n",
       " 'Road-650 Red, 44',\n",
       " \"Women's Mountain Shorts, M\",\n",
       " \"Women's Mountain Shorts, S\",\n",
       " \"Women's Mountain Shorts, L\",\n",
       " 'Racing Socks, L',\n",
       " 'Racing Socks, M',\n",
       " 'Mountain Tire Tube',\n",
       " 'Touring Tire Tube',\n",
       " 'Patch Kit/8 Patches',\n",
       " 'HL Mountain Tire',\n",
       " 'LL Mountain Tire',\n",
       " 'Road Tire Tube',\n",
       " 'LL Road Tire',\n",
       " 'Touring Tire',\n",
       " 'ML Mountain Tire',\n",
       " 'HL Road Tire',\n",
       " 'ML Road Tire',\n",
       " 'Touring-1000 Yellow, 50',\n",
       " 'Touring-1000 Blue, 46',\n",
       " 'Touring-1000 Yellow, 60',\n",
       " 'Touring-1000 Blue, 50',\n",
       " 'Touring-3000 Yellow, 50',\n",
       " 'Touring-3000 Blue, 54',\n",
       " 'Touring-3000 Blue, 58',\n",
       " 'Touring-3000 Yellow, 44',\n",
       " 'Touring-3000 Yellow, 54',\n",
       " 'Touring-3000 Blue, 62',\n",
       " 'Touring-3000 Blue, 44',\n",
       " 'Touring-1000 Blue, 54',\n",
       " 'Touring-1000 Yellow, 46',\n",
       " 'Touring-1000 Blue, 60',\n",
       " 'Touring-3000 Yellow, 62',\n",
       " 'Touring-1000 Yellow, 54',\n",
       " 'Touring-2000 Blue, 54',\n",
       " 'Touring-3000 Blue, 50',\n",
       " 'Touring-3000 Yellow, 58',\n",
       " 'Touring-2000 Blue, 46',\n",
       " 'Touring-2000 Blue, 50',\n",
       " 'Touring-2000 Blue, 60',\n",
       " 'Classic Vest, L',\n",
       " 'Classic Vest, M',\n",
       " 'Classic Vest, S']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### List of every product sold\n",
    "pro_list = list(df[\"Product\"].unique())\n",
    "pro_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c9aff7a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Bar graph of top 10 selling products\n",
    "df[\"Product\"].value_counts().head(10).plot(kind=\"bar\",figsize=(8,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "27aa6b80",
   "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": [
    "### Relation between unit_cost and unit_price\n",
    "cost = np.array(df[\"Unit_Cost\"])\n",
    "price = np.array(df[\"Unit_Price\"])\n",
    "plt.scatter(cost,price,color = \"blue\")\n",
    "plt.show()\n",
    "## or -> df.plot(x = \"unit_cost\",y = \"unit_price\", kind = \"scatter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "465d6038",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Order_Quantity', ylabel='Profit'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Can you see any relationship between Order_Quantity and Profit?\n",
    "df.plot(kind = \"scatter\", x = \"Order_Quantity\", y = \"Profit\", figsize = (6,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b22ba567",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\python3.7\\lib\\site-packages\\seaborn\\_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. 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",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Revenue'>"
      ]
     },
     "execution_count": 49,
     "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": [
    "### Sales evolve per year\n",
    "sales = df.groupby(\"Year\").sum()[\"Revenue\"]\n",
    "year = np.sort(df.Year.unique())\n",
    "import seaborn as sns\n",
    "sns.lineplot(year,sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "fc469593",
   "metadata": {},
   "outputs": [],
   "source": [
    "### increase 50$ revenue to every sale\n",
    "df[\"Revenue\"] = df[\"Revenue\"] + 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "21bc85f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25176"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### How many orders were made in Canada and France\n",
    "can = df[(df[\"Country\"].str.contains(\"Canada\")) | df[\"Country\"].str.contains(\"France\")].shape[0]\n",
    "can"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "0f25cd49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "104"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### Bike rack order from canada\n",
    "cnt = df.loc[(df[\"Sub_Category\"] == \"Bike Racks\") & (df[\"Country\"] == \"Canada\")].shape[0]\n",
    "cnt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "7c47296b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Orders in state Seine (Paris) are: 2328\n",
      "Orders in state Seine Saint Denis are: 1684\n",
      "Orders in state Nord are: 1670\n",
      "Orders in state Hauts de Seine are: 1084\n",
      "Orders in state Essonne are: 994\n",
      "Orders in state Yveline are: 954\n",
      "Orders in state Seine et Marne are: 394\n",
      "Orders in state Moselle are: 386\n",
      "Orders in state Loiret are: 382\n",
      "Orders in state Val d'Oise are: 264\n",
      "Orders in state Garonne (Haute) are: 208\n",
      "Orders in state Val de Marne are: 158\n",
      "Orders in state Charente-Maritime are: 148\n",
      "Orders in state Somme are: 134\n",
      "Orders in state Loir et Cher are: 120\n",
      "Orders in state Pas de Calais are: 90\n"
     ]
    }
   ],
   "source": [
    "### How many orders were made in each region of france\n",
    "france_cnt = df.loc[(df[\"Country\"] == \"France\")]\n",
    "france_cnt_state_order = dict(france_cnt[\"State\"].value_counts())\n",
    "for state,value in france_cnt_state_order.items():\n",
    "    print(f\"Orders in state {state} are: {value}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "401adde2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12164"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###Sales in year 2016 and month may,june,july\n",
    "cond = (df['Year'] == 2016) & (df['Month'].isin(['May', 'June', 'July']))\n",
    "df.loc[cond].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87b757a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
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}