ShazaSaleh/Cardio Good Fitness_ Project.ipynb

## Cardio Good Fitness_ Project.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b11f579a",
   "metadata": {},
   "source": [
    " ## Project: Cardio Good Fitness Case Study\n",
    " \n",
    "### Problem Statement Description\n",
    "#### Objective\n",
    "Explore the dataset to identify differences between the customers of each product and explore relationships between the different attributes of the customers.\n",
    "\n",
    "- Come up with a customer profile (characteristics of a customer) of the different products\n",
    "- Perform univariate and multivariate analyses\n",
    "- Generate a set of insights and recommendations that will help the company in targeting new customers.\n",
    " \n",
    "\n",
    "#### Data Dictionary\n",
    "The data is about customers of the treadmill product(s) of a retail store called Cardio Good Fitness. It contains the following variables-\n",
    "\n",
    "- Product - The model no. of the treadmill\n",
    "- Age -  Age of the customer in no of years\n",
    "- Gender - Gender of the customer\n",
    "- Education - Education of the customer in no. of years\n",
    "- Marital Status - Marital status of the customer\n",
    "- Usage - Avg. # times the customer wants to use the treadmill every week\n",
    "- Fitness - Self rated fitness score of the customer (5 - very fit, 1 - very unfit)\n",
    "- Income - Income of the customer\n",
    "- Miles- Miles that a customer expects to run\n",
    "\n",
    "###  1- Import necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "9a5d04f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "sns.set(color_codes=True) \n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7259af5",
   "metadata": {},
   "source": [
    " ### 2- Import the data file in the main data frame 'data'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "84f48da6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('CardioGoodFitness.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2edfaedf",
   "metadata": {},
   "source": [
    "### 3- Explore the  data set features:\n",
    "#### 1- View the first 5 rows of the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "0f2a5499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Education</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>Usage</th>\n",
       "      <th>Fitness</th>\n",
       "      <th>Income</th>\n",
       "      <th>Miles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TM195</td>\n",
       "      <td>18</td>\n",
       "      <td>Male</td>\n",
       "      <td>14</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>29562</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>15</td>\n",
       "      <td>Single</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>31836</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Female</td>\n",
       "      <td>14</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>30699</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>12</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>32973</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TM195</td>\n",
       "      <td>20</td>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>35247</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Product  Age  Gender  Education MaritalStatus  Usage  Fitness  Income  Miles\n",
       "0   TM195   18    Male         14        Single      3        4   29562    112\n",
       "1   TM195   19    Male         15        Single      2        3   31836     75\n",
       "2   TM195   19  Female         14     Partnered      4        3   30699     66\n",
       "3   TM195   19    Male         12        Single      3        3   32973     85\n",
       "4   TM195   20    Male         13     Partnered      4        2   35247     47"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "576bcd21",
   "metadata": {},
   "source": [
    "#### 2- Understand the shape of the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "1859a48c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(180, 9)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3d039e1",
   "metadata": {},
   "source": [
    "**Observation**: Data set consists of 180 rows and 9 columns "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4494f726",
   "metadata": {},
   "source": [
    "#### 3-Check the  data type of data set variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "1858968a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Product          object\n",
       "Age               int64\n",
       "Gender           object\n",
       "Education         int64\n",
       "MaritalStatus    object\n",
       "Usage             int64\n",
       "Fitness           int64\n",
       "Income            int64\n",
       "Miles             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af6ca5f0",
   "metadata": {},
   "source": [
    "**Observation**: Data set consists of 3 columnns of dtype \"string\" and all remaining 7 columns are of dtype \"int\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d788f1e1",
   "metadata": {},
   "source": [
    "#### 4- Check for null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "cf2b0a0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Product          0\n",
       "Age              0\n",
       "Gender           0\n",
       "Education        0\n",
       "MaritalStatus    0\n",
       "Usage            0\n",
       "Fitness          0\n",
       "Income           0\n",
       "Miles            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b03e67ea",
   "metadata": {},
   "source": [
    "**Observation**: No null values in the data set"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5dd1b7b3",
   "metadata": {},
   "source": [
    "### 5- Check the statistical summary for  the variables "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "a6b54f20",
   "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>Age</th>\n",
       "      <th>Education</th>\n",
       "      <th>Usage</th>\n",
       "      <th>Fitness</th>\n",
       "      <th>Income</th>\n",
       "      <th>Miles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>180.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>180.000000</td>\n",
       "      <td>180.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>28.788889</td>\n",
       "      <td>15.572222</td>\n",
       "      <td>3.455556</td>\n",
       "      <td>3.311111</td>\n",
       "      <td>53719.577778</td>\n",
       "      <td>103.194444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.943498</td>\n",
       "      <td>1.617055</td>\n",
       "      <td>1.084797</td>\n",
       "      <td>0.958869</td>\n",
       "      <td>16506.684226</td>\n",
       "      <td>51.863605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>29562.000000</td>\n",
       "      <td>21.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>44058.750000</td>\n",
       "      <td>66.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>26.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>50596.500000</td>\n",
       "      <td>94.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>33.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>58668.000000</td>\n",
       "      <td>114.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>50.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>104581.000000</td>\n",
       "      <td>360.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Age   Education       Usage     Fitness         Income  \\\n",
       "count  180.000000  180.000000  180.000000  180.000000     180.000000   \n",
       "mean    28.788889   15.572222    3.455556    3.311111   53719.577778   \n",
       "std      6.943498    1.617055    1.084797    0.958869   16506.684226   \n",
       "min     18.000000   12.000000    2.000000    1.000000   29562.000000   \n",
       "25%     24.000000   14.000000    3.000000    3.000000   44058.750000   \n",
       "50%     26.000000   16.000000    3.000000    3.000000   50596.500000   \n",
       "75%     33.000000   16.000000    4.000000    4.000000   58668.000000   \n",
       "max     50.000000   21.000000    7.000000    5.000000  104581.000000   \n",
       "\n",
       "            Miles  \n",
       "count  180.000000  \n",
       "mean   103.194444  \n",
       "std     51.863605  \n",
       "min     21.000000  \n",
       "25%     66.000000  \n",
       "50%     94.000000  \n",
       "75%    114.750000  \n",
       "max    360.000000  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc570844",
   "metadata": {},
   "source": [
    "### 6- Univarant Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a288637b",
   "metadata": {},
   "source": [
    "**(1) Age:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "27d2eab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Age']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a3b133d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Dk7u/Ncl1GV7imjns0xcO+/Nskrf03j82+TrPzHDtNoBTwktawKn0c0keTbK5935h7/3CDFc8f2aGiwi+prU2N/ncN2S4AnqS/FWS61prT2utbUjyexku0ghwSgge4FS6JsktvfdvHL2ZvIT1niS/mCFkdrbW/jnJXJLHJ5/2jiQPZjhZ+YEMR4LeumqjBspztXRgVbTWXpjkxb3390xu/1KSH+y9XzHuyID1wDk8wGr57yRva61dneGlrN0ZTmYGWHGO8AAA5TmHBwAoT/AAAOUJHgCgPMEDAJQneACA8v4PJZ/0Jmt9uRkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Age']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a12e2fe",
   "metadata": {},
   "source": [
    "**Observations:**\n",
    "- The Average age of customers is between 28-29 years old\n",
    "- The youngest customer is 18 years old and the oldest is 50 years old\n",
    "- About 75% of the customers are aged below 33 years old >> hence age variable is right skewed (proved by distribution diagram and bloxplot above )\n",
    "- The box plot shows some outliers for ages above 46 years old"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a43b492",
   "metadata": {},
   "source": [
    "**(2) Education:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "86551386",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Education']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "0ea52ea7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ytSTvSPLInNeYa+ns15k1z/Lxxz/cwTzATzHBA8zHZ5Oc2lpb1VpbkuT0Wes2JjkuSVprP5fkBUnSe9+S0d3XXzded3iSGzO61mZlkvf23q9JcmKSx2YUNcnoGp3lebTPJXl1a231+LVen9G1RLfv1a8SKMcpLWBbrmutzf2x9Pf03j/TWjs6yc1J7k/yn0lWj9dfnORjrbWe5I4kX5z1uacluaS1dm5GR17OTPJvSf4pyX+11h5OcmuSDUmOSPLtJJ9M8uXW2itnXqT3/vnW2geSfHEcXBuTnNx7n5p112mAn+Bu6QBAeU5pAQDlCR4AoDzBAwCUJ3gAgPIEDwBQnuABAMoTPABAef8PQsbv9P11vUsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Education']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50f5a137",
   "metadata": {},
   "source": [
    "**Observations:**\n",
    "- The Average education years of customers is between 15-16 years\n",
    "- The least educated customer studied for 12 years and the most educated studied for 21 years \n",
    "- Boxplot shows someo outliers of education years greater than 18 years"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e48ca9e6",
   "metadata": {},
   "source": [
    "**(3) Usage:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "c4a8afbe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1thnAGHMfcC3w9SP2+ynwNeBbHtYiMmL643FWrj/A/c/sItrXz7I5ZbxxbgVzphYR8PtJBAL8Zd1eACLRfvYc7ODlA208v60eu7eVJbNLqS7NdfyvEBGRkeJlGJsI1A5YrgWWD9zBGPMJYD2w2sM6REZMe3eUO+/fjN3Xytxpxdxw0UwqS3KOuX9GOMCsyYXMnFTAgYYu1m6v58l1B5hRlc+Zp5cTDGhYp4jIWOdlGPMDiQHLPiB+aMEYMw+4BrgQqH49b1BSkl69B6Wlea5LSCv1zd3k5WZ6dvzs7AxKi7M9O/6Jenl/K7fetY62jgi3XL+YC5ZUDzoO7Fjtkp+XxaypxazdVs/abXW0dER5yxumUJw//DZMtzYZrvH2s3Ii9HflaGqTwaldjjZa2sTLMLYfOHfAcgVQM2D5OqASWAuEgYnGmGestQNfc1xNTZ3E44mhdxwBpaV5NDR0uC4jvQQCdHT2enb47u4IDf39nh3/RGzf08Jt920kNyvE5967mKkV+TQ2dg6+8xDtcvqUQgpzQqzaVMt9T77EBYuqqCgZXpBIpzY5IePoZ+VE6O/K0dQmg1O7HC2d2sTv9x23A8nLcyCPAxcaY0qNMdkke8EeObTRWvsVa+0sa+1C4DKg5kSCmEi62L6nhdt+u5HSgiz+5f3LmFqRf9LHnDghh8vPmkJOZpDH1+5nV237KahURETSkWdhzFp7APgisBLYAKyw1j5vjHnIGLPUq/cVGUl2byqIFWbx2esXUZATPmXHzskK8ZYzJzOhMJNnNtayY1/rKTu2iIikD0/nGbPWrgBWHLHuskH22w1M9bIWkVOtprGL23/3IiUFmXz2+kXkn8IgdkhGKMDFS6t5akMNq7fUEfD7mFFVcMrfR0RE3NGlWiKvQ1tXlNt+u5FQ0M8t71zgSRA7JBDwc/7CiVSWZPPsiwd1ylJEZIxRGBM5QdG+fn74u020d0X55LXzmVCQ5fl7BgJ+zl9URVlRFqs21bK3Lj0GpYqIyMlTGBM5AYlEgrsf3cErNe186Iq5TKs8+cH6wxUK+nnzkmpK8jN5ekMN++uPcbWmiIiMKgpjIifg6Y01rHqxlre9cSpLTOmIv38o6OeipdUU5WXw1IYaahq7RrwGERE5tRTGRIZpV207v35sB3OnFfP2c9zd0z4cCnDR0knkZ4d46oUDNLT0OKtFREROnsKYyDB098a48w+byc8J8+ErTnd+M++McICLl00iKyPIE+v209zu3YSpIiLiLYUxkSEkEgnuetTS3B7ho1fOIy/buysnT0RWRpCLl00iGPTz+Nr9tHdFXZckIiKvg8KYyBCe3XyQ57bWceU5UzmtOr3m+MrNCnHx0uStXR9bs089ZCIio5DCmMhx1LV0c/djO5g1qZC3nTXVdTmDKsjN4MKl1URjce74/YvqIRMRGWUUxkSOIdYf58cPbCHo96XFOLHjKcnP5MIlVbR2RPjub16gTYFMRGTUUBgTOYb7n3mF3Qc7uOnS2RTnZ7ouZ0hlRdl85O3zaGjr4Tsr1tPaGXFdkoiIDIPCmMggtu5u5pHVezlv4USWmDLX5QzbrEmF3HLdAprbI3x7xQs0tmraCxGRdKcwJnKEju4oP3lwKxUl2bz7wpmuyzlhZnIRn37XAjq6onzzrnXsPpg+97Lsj8dpbu+lobWHxrYeunr7XJckIuJc0HUBIukkkUjw8z9to6unj1uuW0BGKOC6pNdlZnUhn79xCbfdu4Fv//oFPnLlXBbOnDCiNcQTCfYc7MDubWXHvlb2N3TS3B4hnki8Zr/87BCVpblkhQNMLs+lMDdjROsUEXFNYUxkgCfW7Wfjziauv2gmk8vzXJdzUqom5PDF9y3lP+7bxO2/28Rbl0/mHedNJxjwtkN8f0Mnq7fU8dzWgzS1J8etlRVlMX1iPm+Ym0VJfibBgJ94IkFXT4yapi721Xdi97Sw4aVGivIymDetmCmVefh96XvRhIjIqaIwJpKyr76Te1fuZP6MEi5aUu26nFOiMDeDL7x3Mfc8+TKPPL+XHftb+cCls6kqzT2l79Pc3stzW+v425Y69jd04vf5OH1aEW8/dzpzpxUP2duVCAR4+K872VvXyY59rTyzqZaNO5tYYkqZVHZqaxURSTcKYyJApK+f/3pgMzmZQT54+Rx8Y6hHJhQMcOMlhjmTi/jlI9v5ys/X8ObFVVx17jRyMkOv+7hdvX2s3V7P6i117NjXSgKYPjGfGy6aybI55RTknNidCrIzQ8yeUoSZXMjeuk42vNzIyvUHmFqRx/LTy8gM68+ViIxN+usmAtzzxEscbOrm0+9eSH6a3O7oVFs6u4zZU4r4/dOv8MS6/TzzYi1nz6vgzYurmTghZ1jHaOuKsvmVJtbvaGDTzib64wnKi7O56pxpnDm3nPKi7JOu0+fzMaUij+qyXLa80sSmnU0cbO7mTQsmUlFy8scXEUk3CmMy7q2z9fxlQw2XnjmZuVOLXZfjqdysEO97i+H8hRN5dM0+nt5Yw5PrD1BelIWZXMTUyjwKcsLkZYXp64/T3RujpaOXvfWd7D3Ywd76TgAKcsNcuKSaN8wtZ0p5nic9iQG/j/mnTWBSeR5Pb6jhsbX7koFycuGY6rkUEVEYk3GtvrWHXzy0nakVeVz9pumuyxkxk8vzuPltp/PON5/G6i11bN/Twprt9Ty9sWbQ/XOzQkwpz+XqN01n/vQSJpXnjtjg+qK8DC49azKrNh1kzbZ62jojLD+9XIP7RWTMUBiTcSva18+Pfv8iAB99+zzPrzJMR/nZYS5ZNolLlk0iHk/Q0hGhvTtKR3cf4aCfrIwg+TlhCnPDTnujwsEAFyyayAsvNbL5lWaifXHOmV+Z1reoEhEZLoUxGZcSiQR3PWrZW9/Jp66bT1lhluuSnPP7fZQUZFJSkJ63fvL5fCyeVUpGKMA620Bff5zzF04kMA5DtIiMLQpjMi6tfOEAf33xIFeePZX5M0Z2MlQ5OXOnFRMK+lm9pY6/bKjh/EVVY7aHrKM7Slck5smxM0JBgsqxImlBYUzGnc2vNLHisZeYP6OEK8+e5roceR1mTSokkUjw3NZ6Vm2q5ZwFlWNyDFlPb4w12+o8OfayOeUEM/QRIJIO9Jso48qBhk7ufGAzEyfk8JEr547ZHpXxwEwuoq8/wXrbQDDo56y55brKUkRGJYUxGTdaOiL8x32bCAcDfOq6+WSpV2DUmzetmL6+fl58pZm8rBBnzChxXZKIyAnTp5GMC+3dUb53zwt09vTx2esXUZyfnoPU5cQtnDmBzp4+XnipkdzsENMq812XJCJyQjR8U8a87t4+vn/PBpraevnktfP1YT3G+Hw+3jivgrKiLP764kHqW3pclyQickIUxmRMa+uM8J0VL1DT1MXH33EGZnKR65LEA4GAn/MXTSQnM8jK9Qfo6I66LklEZNgUxmTMqm/p5ta713GwpZt/uGY+86ZrPNFYlhkOcuGSahIkeGLdASLRftcliYgMi8KYjEnb97Rw613r6In089nrF3GGgti4kJ8T5oJFVXR29/HUCwfojydclyQiMiSFMRlT4okEDz67m+/e8wLZmSE+/97FzJhY4LosGUHlxdm88Yxy6lp6eH5rHYmEApmIpDddTSljRk1jF3c/atm+t5Xlc8p4/1tna/qKcWr6xAJaO6NsfqWZwtwMlp9e4bokEZFj0ieVjHpdvX08tHoPjz6/j4xQgJsunc258ys1Aeg4t2jmBNo6o6zdXs/SOWUsM2WuSxIRGZTCmIxaze29PPhiLU9tqCES7efseRVcd8Fp5OeEXZcmacDn83HO/EoeeW4vv/jTNqpKcpg4Icd1WSIiR1EYk1EjkUjQ1hWltqmb3bUdNLT24PPBmXPKeeuZk5lcnue6REkzoaCfCxZX8diafdx+3ya+9P6l5GaFXJclIvIanoYxY8wNwJeAEHCbtfaOI7ZfBXwN8AG7gA9Ya1u8rEnSVzyeINLXTyTaT2/qsScSo707SntXlMa2XqJ9cQAKc8Nc/sYpnDd/IhMKsxxXLuksNyvEh66Yy+33beRH97/Ip9+1kGBA1y6JSPrwLIwZY6qAbwJLgAjwrDFmpbV2a2p7PnAnsMxae8AY83Xgq8AnvapJ3OmN9tPS0Ut7Vx+dPVG6emNEov1E++LJANbXT18sPuhrgwEf+TlhJpXlUlaUTXlRFvk5YZbNKSdHA/RlGKZNzOemS2fz0we3seLxl7jxklkaUygiacPLT7KLgCettc0Axpj7gGuBr6e2h4CPWWsPpJY3Ae/xsB4ZQR3dUTbvaWXVplrqW3ro7Ok7vM3v95GdESQzHCAzHCA/J0RGOEBGKHD4MfPwY5CsjIA+OOWkvXFeJQcau3h49V6qJuRw4ZJq1yWJiADehrGJQO2A5Vpg+aEFa20TcD+AMSYL+BzwQw/rEY/1xeJseLmRVZtq2byriUQCMkIBKkqymTWpgOL8TApyw2RnBBWuxIlrzptBbWM3v3n8JcqLsnRXBhFJC16GMT8wcLZFH3DUeShjTAHJULbRWvvLE3mDkpLckyrwVCstHZ8DyLt7+3j42d384emdtHZEmFCQybVvnsmsSUW0dPR6FryyszMoLc725Nheqm/uJi8305Njq00GN7BdPv+B5XzujlXc+cBmbv37czitutCz9z1Z+lkZ3Hj9WzsUtcvRRkubeBnG9gPnDliuAGoG7mCMqQT+DDwJ3HKib9DU1Ek8TW53UlqaR0NDh+syRlSsP84T6/bz4LO76eqNMXdqER+8dDanTy3G7/eRCAT4y7o2z96/uztCQ/8ovP9gIEBHZ68nh1abDO7Idvn41Wdw611r+ep//40v3LiE0nS9CEQ/K0cZj39rh0PtcrR0ahO/33fcDiQvw9jjwFeNMaVAF3AN8OFDG40xAeD/gHuttd/wsA7xwOZXmljx+EscbO5m3rRi3n7udKZPzHddlsiwFOVlcMs7F/Jvd6/j+/du5PPvWaz56UTEGc/CWOoKyS8CK4Ew8FNr7fPGmIeALwOTgMVA0Bhzbepla621N3tVk5y8nkiM3zzxEqs21VJenM2nrpvP/BkTXJclcsImTsjhE9fO59/v2cD37tnAP92wSHOQiYgTns4LYK1dAaw4Yt1lqadr0Y3KRxW7t4WfPriV5o4Il581hSvPnkYoqP+FMnrNrC7k49ecwe33beIH927kM+9eqPuZisiI0yepDCmeSPDw6j189zcbCAb8fOHGJVxz3gwFMRkT5k0r4e+umseegx384N6NdPfGXJckIuOMPk3luHoiMe74/Yv89qmdLDalfPmmZcyYWOC6LJFTatGsUj561Vx21bbz3XteeM28eCIiXlMYk2NqbOvh3+5ex8aXm7j+wpn83VVzdQpHxqyls8v4h2vO4EBDF99esZ7mdu+u7hQRGUhhTAa1s6aNb/xyLU3tEW555wIuXjZJE7XKmDd/xgRuuW4+TW29fONXa9l9sN11SSIyDiiMyVE27Wzku795gYxwgC+9bwlzpxW7LklkxMyZWswX3ruEgN/Ht369nnW23nVJIjLGKYzJa/z1xVpuv+9FKoqz+cKNS6ksyXFdksiIqy7L5UvvW0rVhFzuuH8zKx7fQax/8BvZi4icLIUxOeyJdfv52Z+2YSYX8s83LKZAk2DKOFaQm8Hn3rOYi5ZU8/ja/dx61zpqGrtclyUiY5DCmADw6Jp9/PqxHSw8bQKfum6BBuqLAKGgnxsunsXHrj6DhtYevvqL53lg1S76YuolE5FTR5+4wsPP7eG3K3eyZFYpH7lqLsGAMrrIQEtMKTOrC/jNEy/xwKpdrN5ykKvfNJ2ls8vw68IWETlJ+tQd5x58dje/XbmTZbPLFMREjiM/J8xHrpzLLe9cQDDg578e2MK//nIta7fX0x9XT5mIvH7qGRunEokEf/zrbh5YtYs3zC3n/10+h4BfQUxkKGdML2Hu1GL+tuUgD6zaxY/+sJmS/EwuWFzFG04vpzg/03WJIjLKKIyNQ4lEgvufeYUHn93D2WdU8IFL5+D361SLyHD5/T7OPqOSs+ZW8MJLjTy2dh/3PbWT3z21k1mTClk0cwLzppdQWZKt+flEZEgKY+NMIpHgt0/t5JHn9vKmBZW8762zNeZF5HXy+30sMaUsMaXUtXTz3NY6nt9Wzz1PvgxPvkxRXgbTKvOZVpnH1Mp8plXkkZ0Zcl22iKQZhbFxJJFIcM8TL/PY2n1csLiK91w8S0FM5BQpL8rmyrOnceXZ02hs7WHzrma2721hd20H63c0HN6vrCiLSaW5VJXmUFWaS3VpDmVFWRomIDKOKYyNE/FEghWP7eDJ9Qe4aGk11184U6dPRDwyoTCL8xdVcf6iKgA6e/rYfbCdXbUd7D3Ywf7GLta/1EAikdw/GPBRWZJDVWkO1aW5VE1IPi8u0qTLR+rojtIViXly7IxQkKAysTigMDYOxBMJ7vqz5S8banjr8slcd8EMBTGREZSbFWLetBLmTSs5vC7a109tUzf7Gzo50NjFgYYu7N5WVm+pO7xPZjhAXnaI4vxMyouzKS/KGvdzAPb0xlizrW7oHV+HZXPKCY7z9hU39FM3xvXH4/zioe08u/kgl581hXe8abqCmEgaCIcCTKnIY0pF3mvWd/f2HQ5n+5u62bKzkZ0H2rB7WwEoyAlTXpxNZUk2EyfkEFJXjsiopzA2hsX64/z3H7ew1jbw9nOnccUbpyqIiaS57MwQM6sLmVldSCIQ4C/r9hKPJ2hq76WuuZu65h5eqWljx75W/H4flSXZTC7Lpbosd9z3momMVvrNHaOiff386A+b2bSziXe/+TQuWT7ZdUki8jr5/T5KC7MoLcxi3nSIxxM0tPawt66TffWd/K2hDrbUUVaUxfTKfKZU5pERCrguW0SGSWFsDOqJxPjh7zZh97byvrcazl9Y5bokETmF/H5fcgxZcTZLZ5fS0hFhX30nu2s7WJ2aXqO6LIfpE/OpKs3RlZoiaU5hbIzp6u3jtns3squ2g5uvOJ2z5la4LklEPOTz+SjOz6Q4P5P5M0pobo/wSk07u2rb2VvXSTjkZ1plPqdVFVCcn6GhCiJpSGFsDGlo7eG2326kobWHv3v7PJaYUtclicgI8vl8lBRkUlKQyRJTSk1TF68caOel/ckLAIryMphRlc/0ifmuSxWRARTGxoidNW3cft8m4vEE//iuhZjJRa5LEhGH/H4f1aW5VJfmEon2s+tgOzv3t7N2ewPrbQPb97Zy/sIqzpherNOYIo4pjI0Ba7fX85MHt1KYG+ZT1y2gskQTRYrIqzLCAWZPLmL25CJaOiLsPNDGKwfa2fRyEwU5Yc6aV8E5Z1QycYL+doi4oDA2iiUSCf78/D5+u/JlZlQV8PFrziA/O+y6LBFJY0V5GSydXcaHr5zLzv1trHqxlsfW7OOR5/ZSXZrLstmlLJ1dpi91IiNIYWyUivb1c/ejO1j1Yi3LZpdx89vmEArqUnYRGZ5AwM+iWaUsmlVKW1eU57bWsXZ7Pfc/s4v7n9lFdWkOS00Z808rYXJ5nu5jK+IhhbFRqL6lmzvu38y++k6uPHsqV54zTX8oReR1K8gJc8mySVyybBItHRHW2nrWbq/ngVW7+MOqXeRkBpkztZjTpxZx+tRiygqzXJcsMqYojI0yq7ce5K4/78Dvg09dN5/5Mya4LklExpCivAwuXjqJi5dOoq0zwtY9LWzd1cyW3c2s3V4PQH5OmCnleUypyGVyWfKWThMKMjVthsjrpDA2SnT39nH3oztYvbWO06oK+NAVp1Oqb6ci4qGC3AzOmlvBWXMrSCQSHGzuZuvuFnbXtrOnroMtu5qJJxIAhIJ+SvIzmVCQ/K+kIJPC3AxyskLkZobIyQqSkxkiOzNIMKCrN0UGUhgbBdbZBu5+zNLR1cfbz53G5WdN0aXoIjKifD4flSU5rxnYH+3r50BjF3vqOqhv7qGxrYfGtl52H+ygs6fvmMcKBnxkhAJkhgNkhoNkhJPPB1uXGQqknifXZWSGaGrrJRjwEwq++p/IaKYwlsYa23q454mXWb+jgUlluXzimvlMq9RkjSKSHsKhANMq8wf9u9QbjdHeFaWrN0ZXTx+dPX109cbo7u2jt6+fSLSf3mjqsa//8P69h9b39dMXiw+rjmDAd7jXLTsjSHZWiLysEPk5YfJzQmSEAjqFKmlNYSwN9URiPLR6D39+fh9+H1xz3nTesnyyuvZFZNTIDAfJDJ/cR0ysP060r/81Aa03lmDttoP0xeLEYnGisX56Iv109fbR3Rujtqubnt4YiQHHCQf95OWEyc8+FNDCFOaGyc8OE9DfVUkDCmNpJBLt58n1+3n4ub109vTxhrnlXHveDIrzM12XJiIy4oIBP8GAn+zM0OF1iUCAuqbO474uHk/Q2dNHe3eU9q4o7V19dHRHqW/pYVdtx+H9fEBudoiC3AwKc8IkEjC1Io/KkuyTDpIiJ0I/bWmgrSvKUy8c4Mn1++no7mPetGKuOncaMyYWuC5NRGTU8ft9h3vAOOIWvbH+OO1dUdq6orR1RmnrjNDaFeVAQyebdzUf3q8kP5OJE3KYOCGbypKc5POS7NcEwxMVi0OkL/a6X388md1RT44rI0NhzJF4IoHd28qqTTWs2V5PrD/B/BklvO2sqZxWrRAmIuKFYMBPcX7mUWcc4vEEUyryae3opaaxi5qmbmoau9i+t+U1Y9cKc8OHw1lFcTbF+RkU5yWvHs3JDB53bFqkL8aabXWe/LvOWzIZjYobvRTGRlA8kWBXTTvrdjSwdns9jW29ZGUEOW9BFRcuraaiONt1iSIi45Lf76OiJJsZE/NZYl5dH48naGzroaaxm5qmLmobu6hp6mLVploiff2vOUY4lJzeozg/k+K8DPJzwuRkhsjNSv4XCPpo64ySEfYTDgU0Wbcc5mkYM8bcAHwJCAG3WWvvOGL7QuCnQD7wNPBRa603fbgOJBIJmtsj7NjXyuZdzWzd3UxbV5SA38ecqUW847zpLJ5ZSjik2xiJiKQjv99HWVE2ZUXZLJz56iTbiUSC9u4+mtt7aWrrpbkjknze3ktze4T99Z109vTRH08c89gBvy81Ls53eHzcoeeB1KPf7yPo9xEI+Aj4/QQGPA8GfMntAT+bX2kiw89rpvsIBwOvWVb4S1+ehTFjTBXwTWAJEAGeNcastNZuHbDb3cDN1trVxpifAR8C7vSqJi/F+uMcaOziQEMnNY1d7G/o4pWaNlo7k+fxc7NCnD61iAUzJrDgtJKTGncgIiJu+Xw+CnLCFOSEjznlUCKRoCfST2dvH109fTS29/LiziYi0X6isX5i/XFi/Qlisfirz/vj9EZjxOIJ+vsT9MfjqcfEcYPdyvUHhqw5GPARCvrJCAXIygi++l/4iOVB1726HA76NVXIKeZlz9hFwJPW2mYAY8x9wLXA11PLU4Asa+3q1P7/A3yNNAtj8XiC7kiMrt4+unpidPb00dqZ/AbU0hGhpSNCU3svDa09xPqTvyg+H5QVZjF7chEzqgqYWV1AdVmuvpWIiIwjPp8vOfdZZhAKsygrzqbrOJPhDiWRSBCPJ14b1FLPz5hZRizaR3TAlB99sfjh5UPPo7Hk3G490X56IjF6IzGa23vpicToSc37NhS/z0dWRnIi3qyMAJkZQbIOPU89ZoWDqfXJEJeZ2hYe2GsX8hNOPff7x/fno5dhbCJQO2C5Flg+xPbqYR47AHj6P6+tK8qPfv8irZ0RBvsukrwkOjlXzZwpxVzyhnwKsoNUFGVTVpSlOcGAhN/naQ/goS780cbLdlGbDE7tcjS1ydG8bpMjp+k4lcyUInz9QwepocTjieR8btEYkWicnmgsNc9bjN5ostcukpq0N3LEuq7eGE3tEXr7YvT1DW/C3kMC/mSvXTDgJxTwEwr5D99lwe/3EfAlT8n6/T4Cfh9+34Dn/mRADPiT+/p8Pnw+yMoMEYnE8MHhdfhILafWpd576ewy8rLDJ91+xzLg52rQcUlehjE/vCbH+ID4CWw/nkqAoqKcofZ73UpK4HufOs+z448Xl587w3UJaUntcjS1yeDULkcbzW1SXamr5ce5SmDnkSu9DGP7gXMHLFcANUdsrzzO9uNZkzp2LXDyXwVEREREvBMgmXnWDLbRyzD2OPBVY0wp0AVcA3z40EZr7R5jTK8x5mxr7V+BG4GHh3nsCLDqVBcsIiIi4pGjesQO8Wxgk7X2APBFYCWwAVhhrX3eGPOQMWZparf3AD8wxmwHcoHbvapHREREJB35EoljXyorIiIiIt7SJX8iIiIiDimMiYiIiDikMCYiIiLikMKYiIiIiEMKYyIiIiIOeTnP2LhhjMkHngXeZq3d7bictGCM+QrwztTin6y1/+SynnRgjPk6yfuzJoCfWWu/77iktGKM+R4wwVp7k+taXDPGrATKgEM3MvyItfY5hyWlBWPMFcBXgBzgUWvtJx2X5JQx5mbg4wNWTQPustZ+/BgvGTeMMe8FPp9afNha+xmX9QxFU1ucJGPMmcBPgNnALIUxMMZcRPKm7xeQDB6PAP9prb3faWEOGWPOA74JnA+EgK3AW6211mVd6cIYcyFwD8ngfpPjcpwyxvhI3qFkirU25rqedGGMmQ48A5wJ1AFPArdaa4c7WfiYZoyZC/wBOMta2+i4HKeMMdkkf4dmAa3AX4EvWmsfd1nX8eg05cn7EPAxhn8rp/GgFvhHa23UWtsHbAMmO67JKWvtX4ALUh+uZSR7pbvcVpUejDHFJIPqra5rSRMm9fioMWajMWbc93KkXA38r7V2f+rvyruAcd9bOMCdwBfGexBLCZDMNzkkv/yGgB6nFQ1BYewkWWtvttY+47qOdGKt3WKtXQ1gjJlJ8nTlQ26rcs9a22eM+RrJXrEngAOOS0oXPyZ5t44W14WkiSKSPx9XAxcCHzXGXOy2pLRwGhAwxvzRGLMB+Hv0MwMcPhuRZa39reta0oG1tgP4F2A7yR6y3SSHEqUthTHxTKrb/DHgs9bal1zXkw6stV8BSoFJJHtVx7XUmJd91tonXNeSLqy1f7PWvs9a25bq5fgZcJnrutJAELgI+H/AWSRPV77faUXp4yOAxqCmGGPmAx8EpgATgX4grceMKYyJJ4wxZ5P8dv85a+0vXdfjmjFmtjFmIYC1thv4PTDfaVHp4V3AJamejq8DVxpjfuC2JLeMMeekxtAd4uPVgfzj2UHgcWttg7W2B7gfWO64JueMMWHgPOCPrmtJI28BnrDW1ltrI8D/kByvm7Z0NaWccsaYSSQHkr7LWvuk43LSxXTga8aYc0he1HAV8HO3JblnrT18+s0YcxNwvrX2FncVpYVC4OvGmDeSHOvyfuCjTitKDw8CvzTGFAIdwKUk/86Md/OBHdZajUF91UbgO8aYHKAbuAJY47ak41PPmHjhM0Am8H1jzIbUf+P6w8Ra+xDwJ+AFYB3wrLX2HrdVSTqy1j7Ia39Wfm6t/ZvbqtxLTe3xHWAVyXGXe4BfOC0qPUwnOS5KUqy1jwK/Ifn7s4nkl5pvOS1qCJraQkRERMQh9YyJiIiIOKQwJiIiIuKQwpiIiIiIQwpjIiIiIg4pjImIiIg4pDAmImOKMSZhjJlwxLprjTFPOSpJROS4FMZEREREHNIM/CIyrhhjZpO832MmyVsN/dRa+yNjTDnJm5aXAxUkJxV9p7W23hizDLgTCAM7Sd7z7tPW2qeMMVcAX0pt6wY+o0laReREqGdMRMabzwL/Z61dQvIG3G8yxviBdwN/s9aeRXJW827gRmNMkOS9RP/FWjsfuB1YCGCMmQncClxmrV0EfBj4feo2LCIiw6KeMREZawa7rYgf6E89vx/4lTFmOfA48AlrbRz4D2PMucaYTwMzgXnAc8AZANbah1OPK40xm1PHuhioBJ4wxhx6rzhwGsn744mIDElhTETGmkagJPV4SDnQBMl7P6Z6tC4GLgS+YoxZAvwDsJzkDdxXkryfnQ+IpR4HOhTsAsAT1tp3HdpgjJkE1Jzif5OIjGE6TSkiY83DwCdSpx4xxhQB7wceSi2vAN6VulH73wPtwAzgLcBt1tq7gHqSYS0AbAMixpi3pl6/nGRvWQJ4ArgkNQ4NY8xlJG9MnDUy/1QRGQt0o3ARGVOMMYXAvwNn8Wqv1q+A71lrE8aYOcBPgVySPVyPA/8MXA18G+gB+oDtgN9ae70xZiHwX0AGsAM4G7jaWrvGGHMd8EVe7UX7lLX2mZH514rIWKAwJiIyBGPMd0mGubrUaciNwHRrbavbykRkLNCYMRGRoe0hOUi/j2QP2M0KYiJyqqhnTERERMQhDeAXERERcUhhTERERMQhhTERERERhxTGRERERBxSGBMRERFxSGFMRERExKH/D4ErczhBwl39AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Usage']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "472ea043",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Usage']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c15eab6",
   "metadata": {},
   "source": [
    "**Observations:**\n",
    "- On Average customers use the trademills 3-4 time per week\n",
    "- The least usage is 2 time per week and the max usage is 7 timer per week\n",
    "- The mean usage is very close to the median hence data seems to be normally distributed (checked via distplot and boxplot)\n",
    "- The box plot shows some outliers for usage of 5 days and above"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c91e6c30",
   "metadata": {},
   "source": [
    "**(4) Fitness:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "0606454f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Fitness']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "00e741e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Fitness']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0583a170",
   "metadata": {},
   "source": [
    "**Observation**\n",
    "- On Average fitness level of custoemrs is between 3 - 4 \n",
    "- The least fitness level is 1 and the max is 5\n",
    "- Boxplot shows outliers of fitness level below 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e094536",
   "metadata": {},
   "source": [
    "**(5) Income:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "02df9942",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Income']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "fa6954ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Income']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37ee43c5",
   "metadata": {},
   "source": [
    "**Obserations:**\n",
    "- On Average annual income of custoemrs is between 53K - 54K \n",
    "- The least annual income is 29K and the max is 104K\n",
    "- About 75% of the customers earn annual income of 58K or less >> hence Income variable seem to right skewed (checked via distplot & boxplot)\n",
    "- Boxplot shows outliers for income level approx 77K and above "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1251a46f",
   "metadata": {},
   "source": [
    "#### (6) Miles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "9c5cce82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.distplot(data['Miles']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "914a55b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Pc0eSN/Xep/paPcD0coYH2CgfzuDXy694TZIPjXpwa21bBr/ddnfv/aIklya5urX24xlcBPOs3vuFSZ47/JanjmHNwBYheIAN0Xu/I8lSa+2i4bWezuq9f2mNb7kgyfcnuX54aYRbk5yZ5NlJ9iZ5Zmvtc0l2J3lP7/2eca4fqM1bWsBG+uMkr0zywPDva5lLsjg8i5Mkaa197/C+g621p2VwVesXJPnr1tobe+97xrJqoDxneICN9JEkL03y8iQffYjH9iTfbq29Mvn/K4B/KclFrbVfyuAzPJ/pvb8tyV8l+ZGxrRooT/AAG6b3/u9Jvpzk7t77fz3EY7+T5PIkr2+t3ZnkM0ne3nvfl8HngeaS3NVauyPJfKb8SszAdHO1dACgPGd4AIDyBA8AUJ7gAQDKEzwAQHmCBwAoT/AAAOUJHgCgvP8DDRWaL62rVWQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.boxplot(data['Miles']);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "146e8d6e",
   "metadata": {},
   "source": [
    "**Observations:**\n",
    "\n",
    "- On Average running miles expected by custoemrs is approx 103 miles \n",
    "- The least expected miles is 21 and the max is 360\n",
    "- About 75% of the customers expect to run 114 miles or less >> hence the miles variable seem to right skewed (checking via distplot & boxplot)\n",
    "- Boxplot shows outliers who expect to run 180 miles or above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "b7b69bde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age          0.982161\n",
       "Education    0.622294\n",
       "Usage        0.739494\n",
       "Fitness      0.454800\n",
       "Income       1.291785\n",
       "Miles        1.724497\n",
       "dtype: float64"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Applying the .skew() function to Double confirm that all variables are right skewed\n",
    "data.skew()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5985362a",
   "metadata": {},
   "source": [
    "### 7- Multivariant analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8088654c",
   "metadata": {},
   "source": [
    "#### 1- Derive the scatter plots between all variables via pairplot function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "71565de5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c86fda4",
   "metadata": {},
   "source": [
    "**Observation**:\n",
    "- Based on the above pair plots, it is observed that the 2 variables with strong +ve correlation are the \"Age\" & \"Income\" \n",
    "\n",
    "**Conclusion**:\n",
    "- The correlation between the \"Age\" & \"Income\" is strong yet, it does not provide an insight on the customers profiles with respect to the product, hence analysis is required between products and customer attributes (Age, Income, education, etc)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f20f4e0",
   "metadata": {},
   "source": [
    "## 8- Exploring the product line & Customer profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "ebbdbaa5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Product', 'Age', 'Gender', 'Education', 'MaritalStatus', 'Usage',\n",
       "       'Fitness', 'Income', 'Miles'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d125aec4",
   "metadata": {},
   "source": [
    "### Exploring Product Popularity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "de3ee006",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TM195    80\n",
       "TM498    60\n",
       "TM798    40\n",
       "Name: Product, dtype: int64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Product'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "c7e7eac5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TM195    44.444444\n",
       "TM498    33.333333\n",
       "TM798    22.222222\n",
       "Name: Product, dtype: float64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data['Product'].value_counts()/len(data['Product']))*100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "537e9f2d",
   "metadata": {},
   "source": [
    "**Observation**: \n",
    "Three product types:\n",
    "- <font color='blue'> TM195 </font>  is the most popular making **44.4%** of the sales \n",
    "- <font color='orange'> TM498 </font>  is in between making **33.3%** of the sales \n",
    "- <font color='red'> TM798 </font> is the least popular making **22.2%** of the sales"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54f4ce0a",
   "metadata": {},
   "source": [
    "### Exploring the customer profile for each product "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "077d45f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.countplot(data=data, x='Product', hue='Gender', palette='Set2');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a7174aa",
   "metadata": {},
   "source": [
    "**Observation**: \n",
    "- <font color='blue'> TM195 </font>  share **common interest between Males & Females**\n",
    "- <font color='Orange'> TM498 </font>  intrest in **Females is slightly less than Males**\n",
    "- <font color='red'> TM798 </font> is the **Most popular between Males than females** "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe4c57e7",
   "metadata": {},
   "source": [
    "### Diving deeper into the customer characteristic with respect to product:\n",
    "#### 1- Bin customers into 4 age groups : \n",
    "- 15-20 = Teens\n",
    "- 20-30=20s\n",
    "- 30-40=30s\n",
    "- 40-50=40s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "2641695a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Education</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>Usage</th>\n",
       "      <th>Fitness</th>\n",
       "      <th>Income</th>\n",
       "      <th>Miles</th>\n",
       "      <th>Age Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TM195</td>\n",
       "      <td>18</td>\n",
       "      <td>Male</td>\n",
       "      <td>14</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>29562</td>\n",
       "      <td>112</td>\n",
       "      <td>teen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>15</td>\n",
       "      <td>Single</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>31836</td>\n",
       "      <td>75</td>\n",
       "      <td>teen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Female</td>\n",
       "      <td>14</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>30699</td>\n",
       "      <td>66</td>\n",
       "      <td>teen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>12</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>32973</td>\n",
       "      <td>85</td>\n",
       "      <td>teen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TM195</td>\n",
       "      <td>20</td>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>35247</td>\n",
       "      <td>47</td>\n",
       "      <td>teen</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Product  Age  Gender  Education MaritalStatus  Usage  Fitness  Income  \\\n",
       "0   TM195   18    Male         14        Single      3        4   29562   \n",
       "1   TM195   19    Male         15        Single      2        3   31836   \n",
       "2   TM195   19  Female         14     Partnered      4        3   30699   \n",
       "3   TM195   19    Male         12        Single      3        3   32973   \n",
       "4   TM195   20    Male         13     Partnered      4        2   35247   \n",
       "\n",
       "   Miles Age Group  \n",
       "0    112      teen  \n",
       "1     75      teen  \n",
       "2     66      teen  \n",
       "3     85      teen  \n",
       "4     47      teen  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Age Group'] = pd.cut(data['Age'],bins=[15,20,30,40,50],labels=['teen','20s','30s','40s'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2035ba82",
   "metadata": {},
   "source": [
    "#### 2- Now plot the distribution of product with respect to age group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "ab28d2f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.countplot(data=data, x='Product', hue='Age Group');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfe4bad6",
   "metadata": {},
   "source": [
    "**Observation:**\n",
    "\n",
    "- The most common age group purchasing all products is the 20s- adults aged between 20 & 30 years old\n",
    "- <font color='blue'> TM195 </font>  is the most common between 20s followed by 30s(after a big gap) then 30s and 40s share almost the same intrest in that product \n",
    "-  <font color='orange'> TM498 </font> is the most common between 20s followed by 30s(after a moderate gap) then 30s and then 40s \n",
    "- <font color='red'> TM798 </font> is the most common between 20s followed by 30s(after a big gap) then 40s. Teens do not share any intrest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48e05fdc",
   "metadata": {},
   "source": [
    "#### 3- Now plot the distribution of product with respect to fitness level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "4b8577d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.countplot(data=data, x='Product', hue='Fitness');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d99a99d",
   "metadata": {},
   "source": [
    "**Observation:**\n",
    "\n",
    "- <font color='blue'> TM195 </font> is the most common for fitness level 3\n",
    "- <font color='orange'>TM498 </font> is the most common for fitness level 3\n",
    "- <font color='red'>TM798 </font> is the most common for fitness level 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34664607",
   "metadata": {},
   "source": [
    "#### 4- Observing if the expected Miles to run by customers affect the choice of product\n",
    "##### To observe this:\n",
    "#### Step 01: we will bin the miles into 3 different \"Stamina levels\" based on the IQR data derived earlier from data.describe() :\n",
    "- 21-66    Miles: Beginners\n",
    "- 66 - 114 Miles: Intermediates\n",
    "- 114 - 180 Miles: Advanced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "e3005638",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Education</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>Usage</th>\n",
       "      <th>Fitness</th>\n",
       "      <th>Income</th>\n",
       "      <th>Miles</th>\n",
       "      <th>Age Group</th>\n",
       "      <th>Stamina</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TM195</td>\n",
       "      <td>18</td>\n",
       "      <td>Male</td>\n",
       "      <td>14</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>29562</td>\n",
       "      <td>112</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>15</td>\n",
       "      <td>Single</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>31836</td>\n",
       "      <td>75</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Female</td>\n",
       "      <td>14</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>30699</td>\n",
       "      <td>66</td>\n",
       "      <td>teen</td>\n",
       "      <td>Beginners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>12</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>32973</td>\n",
       "      <td>85</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TM195</td>\n",
       "      <td>20</td>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>35247</td>\n",
       "      <td>47</td>\n",
       "      <td>teen</td>\n",
       "      <td>Beginners</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Product  Age  Gender  Education MaritalStatus  Usage  Fitness  Income  \\\n",
       "0   TM195   18    Male         14        Single      3        4   29562   \n",
       "1   TM195   19    Male         15        Single      2        3   31836   \n",
       "2   TM195   19  Female         14     Partnered      4        3   30699   \n",
       "3   TM195   19    Male         12        Single      3        3   32973   \n",
       "4   TM195   20    Male         13     Partnered      4        2   35247   \n",
       "\n",
       "   Miles Age Group       Stamina  \n",
       "0    112      teen  Intermediate  \n",
       "1     75      teen  Intermediate  \n",
       "2     66      teen     Beginners  \n",
       "3     85      teen  Intermediate  \n",
       "4     47      teen     Beginners  "
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Stamina']= pd.cut(data['Miles'], bins=(21,66,114,180),labels=['Beginners','Intermediate','Advanced'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "effde299",
   "metadata": {},
   "source": [
    "#### Step 02: Now plot the running level (defined by miles) with respect to product "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "1b9fb1c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.countplot(data=data, x='Product', hue='Stamina');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b15287da",
   "metadata": {},
   "source": [
    "**Observation:**\n",
    "- <font color='blue'> TM195 </font>is best suited for Beginners and Intermediate runners (who are expected to run **114 miles or less**)\n",
    "- <font color='orange'>TM498 </font>is best suited for Intermediate runners (who are expected to run **between 66 & 114 miles**)\n",
    "- <font color='red'>TM798 </font>is best suited for Advanced runners awho are expected to run **above 114 miles**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8ff7bbd",
   "metadata": {},
   "source": [
    "#### 4- Exploring if the customers marital status affect the choice of product\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "1ae90fb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "sns.countplot(data=data, x='Product', hue='MaritalStatus');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20b961e9",
   "metadata": {},
   "source": [
    "**Observation:**\n",
    "- TM195 & TM498 & TM798 are purchased more by partnered customers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7dad9be",
   "metadata": {},
   "source": [
    "### 5- Exploring if the income level effect on product choice:\n",
    "#### Step 01: Bin data set into 4 different income levels (Derived from the box plot below):\n",
    "- 20K to 40K : Low Income\n",
    "- 40K to 50K : Medium Income\n",
    "- 50K to 60K : High Income\n",
    "- 60K to 105K : Very High Income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "bd87b6d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Binning the data set into income levels\n",
    "data['Income Level']= pd.cut(data['Income'], bins=(20000,40000,50000,60000,105000),labels=['Low In','Med In','High In','V.High In'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "b535a510",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Education</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>Usage</th>\n",
       "      <th>Fitness</th>\n",
       "      <th>Income</th>\n",
       "      <th>Miles</th>\n",
       "      <th>Age Group</th>\n",
       "      <th>Stamina</th>\n",
       "      <th>Income Level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TM195</td>\n",
       "      <td>18</td>\n",
       "      <td>Male</td>\n",
       "      <td>14</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>29562</td>\n",
       "      <td>112</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "      <td>Low In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>15</td>\n",
       "      <td>Single</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>31836</td>\n",
       "      <td>75</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "      <td>Low In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Female</td>\n",
       "      <td>14</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>30699</td>\n",
       "      <td>66</td>\n",
       "      <td>teen</td>\n",
       "      <td>Beginners</td>\n",
       "      <td>Low In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TM195</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>12</td>\n",
       "      <td>Single</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>32973</td>\n",
       "      <td>85</td>\n",
       "      <td>teen</td>\n",
       "      <td>Intermediate</td>\n",
       "      <td>Low In</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TM195</td>\n",
       "      <td>20</td>\n",
       "      <td>Male</td>\n",
       "      <td>13</td>\n",
       "      <td>Partnered</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>35247</td>\n",
       "      <td>47</td>\n",
       "      <td>teen</td>\n",
       "      <td>Beginners</td>\n",
       "      <td>Low In</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Product  Age  Gender  Education MaritalStatus  Usage  Fitness  Income  \\\n",
       "0   TM195   18    Male         14        Single      3        4   29562   \n",
       "1   TM195   19    Male         15        Single      2        3   31836   \n",
       "2   TM195   19  Female         14     Partnered      4        3   30699   \n",
       "3   TM195   19    Male         12        Single      3        3   32973   \n",
       "4   TM195   20    Male         13     Partnered      4        2   35247   \n",
       "\n",
       "   Miles Age Group       Stamina Income Level  \n",
       "0    112      teen  Intermediate       Low In  \n",
       "1     75      teen  Intermediate       Low In  \n",
       "2     66      teen     Beginners       Low In  \n",
       "3     85      teen  Intermediate       Low In  \n",
       "4     47      teen     Beginners       Low In  "
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#view the data set to ensure the column is added correctly\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21729044",
   "metadata": {},
   "source": [
    "#### Step 02: Plot product against income level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "a08f5611",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.countplot(data=data, x='Product', hue='Income Level');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e937108",
   "metadata": {},
   "source": [
    "**Observation:**\n",
    "- <font color='blue'> TM195 </font>: Seems to be an affordable option hence it is preferred for Low-Med-High income levels (yet not preferred by V.High Income level)\n",
    "- <font color='orange'>  TM498 </font>: Most preferred for medium and high income levels\n",
    "- <font color='red'> TM798 </font>: Highly preffereed by V.High income levels and not at all by low income level customers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a75cc97",
   "metadata": {},
   "source": [
    "### 6- Exploring if the education level effect on product choice:\n",
    "#### Step 01: Bin data set into 4 different education levels (Derived from the basic statistics info table above):\n",
    "- 12 to 14 years: Basic Education\n",
    "- 14 to 16 years: Medium Education\n",
    "- 16 to 18 years: High Education\n",
    "- 18 to 21 years: Very High Education"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "aa0d143f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Binning the data set into education levels\n",
    "data['Education Level']= pd.cut(data['Education'], bins=(11,14,16,18,21),labels=['Basic Edu','Med Edu','High Ed','V.High Ed'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f464da00",
   "metadata": {},
   "source": [
    "#### Step 02: Plot product against education level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "3f06a776",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.countplot(data=data, x='Product', hue='Education Level');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c9735a3",
   "metadata": {},
   "source": [
    "**Observation**:\n",
    "- <font color='blue'>TM195 </font>& <font color='orange'> TM498 </font>: Preferred most by Basic and Medium educated\n",
    "- <font color='red'>TM798</font> is the only product bought by the V.High Educated and highly preferrable by the High education compared to TM195 & TM498"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ffb2f8",
   "metadata": {},
   "source": [
    "### 7- Exploring if the customer expected usage effect on product choice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "898e3cda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.countplot(data=data, x='Product', hue='Usage');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a8b5026",
   "metadata": {},
   "source": [
    "**Observation**:\n",
    "- <font color='blue'>TM195 </font>& <font color='orange'> TM498 </font>: Mostly expected to be used 3 times per week\n",
    "- <font color='red'>TM798</font> Mostly expected to be used 3 times per week and is the only product with customers expected to use up to 7 times a week"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a24c551",
   "metadata": {},
   "source": [
    "# Key Insights and Observations:\n",
    "\n",
    "- The dominant age group for purchasing all product is the 20s\n",
    "- The dominant fitness criteria for TM798 are the most fit customers who can run 114 mile and above\n",
    "- Male & Females are equaly interested in TM195 & TM498 yet males are much more interested in TM798 \n",
    "- TM195 & TM498 & TM798 are purchased more by partnered customers\n",
    "- TM195 Is the most affordable choice\n",
    "- TM798 Is the most expensive choice preferred highly by the V.High Income, Education and fitness level customers\n",
    "\n",
    "\n",
    "### Product's Popularity (in terms of sales)\n",
    "- <font color='blue'> TM195 </font>  is the most popular with approx sales of **44%** from total sales\n",
    "- <font color='Orange'> TM498 </font>  is the next popular with approx sales of **33%** from total sales\n",
    "- <font color='red'> TM798 </font> is the least popular with approx sales of **22%** from total sales\n",
    "\n",
    "\n",
    "### Customer Profiles for each product to be considered for setting a customer targeting merketing plan \n",
    "\n",
    "\n",
    "Product | Age Group | Gender |Marital Status|Education Level | Income Level | Fitness Level | Stamina | Usage\n",
    ":---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:\n",
    "**TM195** | teens to 40s | Males & Females |Partnered & Single| Basic to High| Low to V.High | 1 to 5 |Beginner to Advanced|2-5\n",
    "**TM498** | teens to 40s | Males & Females|Partnered & Single|Basic to High|Low to V.High|1 to 4|Beginner to Advanced|2-5\n",
    "**TM798** | 20s to 40s | Males& Females|Partnered & Single|Basic to V.High|Medium to V.High |3 to 5|Intermediate to Advanced|3-7\n",
    "\n",
    "\n",
    "### Insights \n",
    "- <font color='blue'>TM195 </font> is the most suitable choice for the majority of fitness,education and income levels, hence most popular\n",
    "- <font color='red'>TM798 </font> is the most suitable choice for elite athelits hence it is expected to have a higher level of technology and quality hence it seems to be set at a higher price level which tightens its target customers to V.High income levels.\n",
    "- <font color='orange'>TM498 </font> stands in a middle ground between <font color='blue'> TM195</font> and <font color='red'>TM798</font>\n",
    "\n",
    "### Recommendations:\n",
    "- <font color='blue'>TM195 </font> requires a generalized marketing campaign and requires to be available in stock to sustain the demand\n",
    "- <font color='orange'>TM498 </font> and <font color='blue'>TM195 </font> customer profiles are very close hence it requires more marketing to the beginner and advanced fitness level customers\n",
    "- <font color='red'>TM798 </font> shares the intermediate fitness level interest with <font color='blue'>TM195 </font> and <font color='orange'>TM498 </font> hence can grow its customer base by reducing the price point to fit the income level customers noting that quality has to be maintained\n",
    "\n",
    "\n",
    "#### Key to customer profiles table:\n",
    "**(1) Age Groups**\n",
    "- 15-20 = Teens\n",
    "- 20-30=20s\n",
    "- 30-40=30s\n",
    "- 40-50=40s\n",
    "\n",
    "**(2) Education Levels**\n",
    "- 12 to 14 years: Basic Education\n",
    "- 14 to 16 years: Medium Education\n",
    "- 16 to 18 years: High Education\n",
    "- 18 to 21 years: Very High Education\n",
    "\n",
    "**(3) Income Levels**\n",
    "- 20K to 40K : Low Income\n",
    "- 40K to 50K : Medium Income\n",
    "- 50K to 60K : High Income\n",
    "- 60K to 105K : Very High Income\n",
    "\n",
    "**(4) Stamina**\n",
    "- 21  - 66  Miles: Beginners\n",
    "- 66  - 114 Miles: Intermediates\n",
    "- 114 - 180 Miles: Advanced\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5ee28e4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "423252a2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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