DV0101EN-Final-Assignment-Part1-v2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\">\n",
    "    </a>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Create visualizations using Matplotib, Seaborn and Folium** \n",
    "\n",
    "Estimated time needed: **40** minutes\n",
    "\n",
    "In this assignment, you will have the opportunity to demonstrate the skills you have acquired in creating visualizations using *Matplotlib, Seaborn, Folium*.\n",
    "<br>\n",
    "<br>\n",
    "<span style=\"color:red\">After each task you will be required to save your plots as an image or screenshot using the filenames specified.  You will be uploading these images during your final project submission so they can be evaluated by your peers. </span>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# __Table of Contents__\n",
    "\n",
    "<ol>\n",
    "    <li><a href=\"#Objectives\">Objectives</a></li>\n",
    "    <li>\n",
    "        <a href=\"#Setup\">Setup</a>\n",
    "        <ol>\n",
    "            <li><a href=\"#Installing-Required-Libraries\">Installing Required Libraries</a></li>\n",
    "            <li><a href=\"#Importing-Required-Libraries\">Importing Required Libraries</a></li>\n",
    "            </ol>\n",
    "    </li>\n",
    "    <li>\n",
    "        <a href=\"#Scenario\">Scenario</a>\n",
    "        <ol>\n",
    "            <li><a href=\"#Data Description\">Data Description</a></li>\n",
    "        </ol>\n",
    "    </li>\n",
    "    <li><a href=\"#Importing Data\">Importing data</a></li>\n",
    "    <li><a href=\"#Creating Visualizations for Data Analysis\">Creating Visualizations for Data Analysis</a></li>\n",
    "</ol>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Objectives\n",
    "\n",
    "After completing this lab you will be able to:\n",
    "\n",
    "- Create informative and visually appealing plots with Matplotlib and Seaborn.\n",
    "- Apply visualization to communicate insights from the data.\n",
    "- Analyze data through using visualizations.\n",
    "- Customize visualizations\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this lab, we will be using the following libraries:\n",
    "\n",
    "*   [`pandas`](https://pandas.pydata.org/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMML0187ENSkillsNetwork31430127-2021-01-01) for managing the data.\n",
    "*   [`numpy`](https://numpy.org/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMML0187ENSkillsNetwork31430127-2021-01-01) for mathematical operations.\n",
    "*   [`matplotlib`](https://matplotlib.org/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMML0187ENSkillsNetwork31430127-2021-01-01) for plotting.\n",
    "*   [`seaborn`](https://seaborn.pydata.org/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMML0187ENSkillsNetwork31430127-2021-01-01) for plotting.\n",
    "*  [`Folium`](https://python-visualization.github.io/folium/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMML0187ENSkillsNetwork31430127-2021-01-01) for plotting.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Installing Required Libraries\n",
    "\n",
    "The following required libraries are pre-installed in the Skills Network Labs environment. However, if you run these notebook commands in a different Jupyter environment (e.g. Watson Studio or Ananconda), you will need to install these libraries by removing the `#` sign before `%pip` in the code cell below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# All Libraries required for this lab are listed below. The libraries pre-installed on Skills Network Labs are commented.\n",
    "# %pip install -qy pandas==1.3.4 numpy==1.21.4 matplotlib==3.5.0 seaborn folium\n",
    "# Note: If your environment doesn't support \"%pip install\", use \"!mamba install\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: seaborn in /usr/local/lib/python3.9/dist-packages (0.12.2)\n",
      "Requirement already satisfied: matplotlib!=3.6.1,>=3.1 in /usr/local/lib/python3.9/dist-packages (from seaborn) (3.7.2)\n",
      "Requirement already satisfied: pandas>=0.25 in /home/rod/.local/lib/python3.9/site-packages (from seaborn) (2.2.1)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.17 in /home/rod/.local/lib/python3.9/site-packages (from seaborn) (1.25.2)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (0.11.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /home/rod/.local/lib/python3.9/site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (2.8.2)\n",
      "Requirement already satisfied: importlib-resources>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (6.0.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (4.42.0)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (1.3.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (1.4.4)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (10.4.0)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/rod/.local/lib/python3.9/site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (23.1)\n",
      "Requirement already satisfied: pyparsing<3.1,>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (3.0.9)\n",
      "Requirement already satisfied: zipp>=3.1.0 in /home/rod/.local/lib/python3.9/site-packages (from importlib-resources>=3.2.0->matplotlib!=3.6.1,>=3.1->seaborn) (3.15.0)\n",
      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.9/dist-packages (from pandas>=0.25->seaborn) (2023.3)\n",
      "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.9/dist-packages (from pandas>=0.25->seaborn) (2023.3)\n",
      "Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.1->seaborn) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: folium in /home/rod/.local/lib/python3.9/site-packages (0.18.0)\n",
      "Requirement already satisfied: requests in /home/rod/.local/lib/python3.9/site-packages (from folium) (2.31.0)\n",
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      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->folium) (2024.8.30)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/lib/python3/dist-packages (from requests->folium) (1.26.5)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests->folium) (2.10)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install seaborn\n",
    "%pip install folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Required Libraries\n",
    "\n",
    "_We recommend you import all required libraries in one place (here):_\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import folium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "You will require:-\n",
    "<br>Numpy for many scientific computing in Python\n",
    "<br>Pandas for creating and working on dataframe, also for plotting directly on dataframe/series\n",
    "<br>The inline backend to generate the plots within the browser [%matplotlib inline]\n",
    "<br>Matplotlib and its pyplot pacakge for plotting\n",
    "<br>Seaborn for plotting\n",
    "</details>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<details><summary>Click here for python solution</summary>\n",
    "\n",
    "```python\n",
    "    #Import Primary Modules:\n",
    "    import numpy as np\n",
    "    import pandas as pd\n",
    "    %matplotlib inline\n",
    "    import matplotlib as mpl\n",
    "    import matplotlib.pyplot as plt\n",
    "    import seaborn as sns\n",
    "    import folium\n",
    "```\n",
    "\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "# Scenario\n",
    "\n",
    "In this assignment you will be tasked with creating plots which answer questions for analysing \"historical_automobile_sales\" data to understand the historical trends in automobile sales during recession periods.<br>\n",
    "recession period 1 - year 1980 <br>\n",
    "recession period 2 - year 1981 to 1982<br>\n",
    "recession period 3 - year 1991<br>\n",
    "recession period 4 - year 2000 to 2001<br>\n",
    "recession period 5 - year end 2007 to mid 2009<br>\n",
    "recession period 6 - year 2020 -Feb to April (Covid-19 Impact)<br>\n",
    "\n",
    "# Data Description\n",
    "\n",
    "The dataset used for this visualization assignment contains *historical_automobile_sales* data representing automobile sales and related variables during recession and non-recession period. \n",
    "\n",
    "The dataset includes the following variables:\n",
    "<br>1. Date: The date of the observation.\n",
    "<br>2. Recession: A binary variable indicating recession perion; 1 means it was recession, 0 means it was normal.\n",
    "<br>3. Automobile_Sales: The number of vehicles sold during the period.\n",
    "<br>4. GDP: The per capita GDP value in USD.\n",
    "<br>5. Unemployment_Rate: The monthly unemployment rate.\n",
    "<br>6. Consumer_Confidence: A synthetic index representing consumer confidence, which can impact consumer spending and automobile purchases.\n",
    "<br>7. Seasonality_Weight: The weight representing the seasonality effect on automobile sales during the period.\n",
    "<br>8. Price: The average vehicle price during the period.\n",
    "<br>9. Advertising_Expenditure: The advertising expenditure of the company.\n",
    "<br>10.Vehicle_Type: The type of vehicles sold; Supperminicar, Smallfamiliycar,                 Mediumfamilycar, Executivecar, Sports.\n",
    "<br>11.Competition: The measure of competition in the market, such as the number of competitors or market share of major manufacturers.\n",
    "<br>12.Month: Month of the observation extracted from Date..\n",
    "<br>13.Year: Year of the observation extracted from Date.\n",
    "<br>\n",
    "By examining various factors mentioned above from the dataset, you aim to gain insights into how recessions impacted automobile sales for your company.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### For your convenience, we have already written code to import the data below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data downloaded and read into a dataframe!\n",
      "        Date  Year Month  Recession  Consumer_Confidence  Seasonality_Weight  \\\n",
      "0  1/31/1980  1980   Jan          1               108.24                0.50   \n",
      "1  2/29/1980  1980   Feb          1                98.75                0.75   \n",
      "2  3/31/1980  1980   Mar          1               107.48                0.20   \n",
      "3  4/30/1980  1980   Apr          1               115.01                1.00   \n",
      "4  5/31/1980  1980   May          1                98.72                0.20   \n",
      "\n",
      "       Price  Advertising_Expenditure  Competition     GDP  Growth_Rate  \\\n",
      "0  27483.571                     1558            7  60.223     0.010000   \n",
      "1  24308.678                     3048            4  45.986    -0.309594   \n",
      "2  28238.443                     3137            3  35.141    -0.308614   \n",
      "3  32615.149                     1653            7  45.673     0.230596   \n",
      "4  23829.233                     1319            4  52.997     0.138197   \n",
      "\n",
      "   unemployment_rate  Automobile_Sales     Vehicle_Type        City  \n",
      "0                5.4             456.0    Supperminicar     Georgia  \n",
      "1                4.8             555.9    Supperminicar    New York  \n",
      "2                3.4             620.0  Mediumfamilycar    New York  \n",
      "3                4.2             702.8    Supperminicar    Illinois  \n",
      "4                5.3             770.4  Smallfamiliycar  California  \n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import io\n",
    "import pandas as pd\n",
    "\n",
    "# URL of the CSV file\n",
    "URL = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/historical_automobile_sales.csv\"\n",
    "\n",
    "# Fetch the data from the URL\n",
    "response = requests.get(URL)\n",
    "\n",
    "# Raise an error if the request failed\n",
    "response.raise_for_status()\n",
    "\n",
    "# Convert the response content into a readable format for pandas\n",
    "csv_content = io.StringIO(response.text)\n",
    "\n",
    "# Read the CSV data into a pandas dataframe\n",
    "df = pd.read_csv(csv_content)\n",
    "\n",
    "# Print confirmation\n",
    "print('Data downloaded and read into a dataframe!')\n",
    "\n",
    "# Optional: Show the first few rows of the dataframe\n",
    "print(df.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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",
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       "\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>Year</th>\n",
       "      <th>Recession</th>\n",
       "      <th>Consumer_Confidence</th>\n",
       "      <th>Seasonality_Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Advertising_Expenditure</th>\n",
       "      <th>Competition</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Growth_Rate</th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>Automobile_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "      <td>528.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2001.500000</td>\n",
       "      <td>0.214015</td>\n",
       "      <td>101.140170</td>\n",
       "      <td>0.575795</td>\n",
       "      <td>24964.991956</td>\n",
       "      <td>3067.456439</td>\n",
       "      <td>6.064394</td>\n",
       "      <td>40.073903</td>\n",
       "      <td>-0.242001</td>\n",
       "      <td>2.453977</td>\n",
       "      <td>2352.718068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.710467</td>\n",
       "      <td>0.410526</td>\n",
       "      <td>10.601154</td>\n",
       "      <td>0.454477</td>\n",
       "      <td>4888.073433</td>\n",
       "      <td>1139.564637</td>\n",
       "      <td>1.968350</td>\n",
       "      <td>16.249714</td>\n",
       "      <td>0.861268</td>\n",
       "      <td>1.119019</td>\n",
       "      <td>1645.321284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1980.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>73.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8793.663000</td>\n",
       "      <td>1009.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>12.508000</td>\n",
       "      <td>-4.227601</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>102.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1990.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.035000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>21453.300500</td>\n",
       "      <td>2083.500000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>27.237500</td>\n",
       "      <td>-0.574049</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>793.950000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2001.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.740000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>25038.691500</td>\n",
       "      <td>3072.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>39.214500</td>\n",
       "      <td>-0.013162</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>2182.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2012.250000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>108.240000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>28131.684750</td>\n",
       "      <td>4067.250000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>53.506500</td>\n",
       "      <td>0.388932</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>3614.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2023.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>131.670000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>44263.657000</td>\n",
       "      <td>4983.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>70.374000</td>\n",
       "      <td>0.815074</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>21147.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year   Recession  Consumer_Confidence  Seasonality_Weight  \\\n",
       "count   528.000000  528.000000           528.000000          528.000000   \n",
       "mean   2001.500000    0.214015           101.140170            0.575795   \n",
       "std      12.710467    0.410526            10.601154            0.454477   \n",
       "min    1980.000000    0.000000            73.900000            0.000000   \n",
       "25%    1990.750000    0.000000            94.035000            0.250000   \n",
       "50%    2001.500000    0.000000           100.740000            0.500000   \n",
       "75%    2012.250000    0.000000           108.240000            0.750000   \n",
       "max    2023.000000    1.000000           131.670000            1.500000   \n",
       "\n",
       "              Price  Advertising_Expenditure  Competition         GDP  \\\n",
       "count    528.000000               528.000000   528.000000  528.000000   \n",
       "mean   24964.991956              3067.456439     6.064394   40.073903   \n",
       "std     4888.073433              1139.564637     1.968350   16.249714   \n",
       "min     8793.663000              1009.000000     3.000000   12.508000   \n",
       "25%    21453.300500              2083.500000     4.000000   27.237500   \n",
       "50%    25038.691500              3072.000000     6.000000   39.214500   \n",
       "75%    28131.684750              4067.250000     8.000000   53.506500   \n",
       "max    44263.657000              4983.000000     9.000000   70.374000   \n",
       "\n",
       "       Growth_Rate  unemployment_rate  Automobile_Sales  \n",
       "count   528.000000         528.000000        528.000000  \n",
       "mean     -0.242001           2.453977       2352.718068  \n",
       "std       0.861268           1.119019       1645.321284  \n",
       "min      -4.227601           1.000000        102.000000  \n",
       "25%      -0.574049           1.600000        793.950000  \n",
       "50%      -0.013162           2.300000       2182.600000  \n",
       "75%       0.388932           2.900000       3614.800000  \n",
       "max       0.815074           6.000000      21147.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Year', 'Month', 'Recession', 'Consumer_Confidence',\n",
       "       'Seasonality_Weight', 'Price', 'Advertising_Expenditure', 'Competition',\n",
       "       'GDP', 'Growth_Rate', 'unemployment_rate', 'Automobile_Sales',\n",
       "       'Vehicle_Type', 'City'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# saving data to local (extra)\n",
    "df.to_csv('historical_automobile_sales.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Recession</th>\n",
       "      <th>Consumer_Confidence</th>\n",
       "      <th>Seasonality_Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Advertising_Expenditure</th>\n",
       "      <th>Competition</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Growth_Rate</th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>Automobile_Sales</th>\n",
       "      <th>Vehicle_Type</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/31/1980</td>\n",
       "      <td>1980</td>\n",
       "      <td>Jan</td>\n",
       "      <td>1</td>\n",
       "      <td>108.24</td>\n",
       "      <td>0.50</td>\n",
       "      <td>27483.571</td>\n",
       "      <td>1558</td>\n",
       "      <td>7</td>\n",
       "      <td>60.223</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>5.4</td>\n",
       "      <td>456.0</td>\n",
       "      <td>Supperminicar</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/29/1980</td>\n",
       "      <td>1980</td>\n",
       "      <td>Feb</td>\n",
       "      <td>1</td>\n",
       "      <td>98.75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>24308.678</td>\n",
       "      <td>3048</td>\n",
       "      <td>4</td>\n",
       "      <td>45.986</td>\n",
       "      <td>-0.309594</td>\n",
       "      <td>4.8</td>\n",
       "      <td>555.9</td>\n",
       "      <td>Supperminicar</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3/31/1980</td>\n",
       "      <td>1980</td>\n",
       "      <td>Mar</td>\n",
       "      <td>1</td>\n",
       "      <td>107.48</td>\n",
       "      <td>0.20</td>\n",
       "      <td>28238.443</td>\n",
       "      <td>3137</td>\n",
       "      <td>3</td>\n",
       "      <td>35.141</td>\n",
       "      <td>-0.308614</td>\n",
       "      <td>3.4</td>\n",
       "      <td>620.0</td>\n",
       "      <td>Mediumfamilycar</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/30/1980</td>\n",
       "      <td>1980</td>\n",
       "      <td>Apr</td>\n",
       "      <td>1</td>\n",
       "      <td>115.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>32615.149</td>\n",
       "      <td>1653</td>\n",
       "      <td>7</td>\n",
       "      <td>45.673</td>\n",
       "      <td>0.230596</td>\n",
       "      <td>4.2</td>\n",
       "      <td>702.8</td>\n",
       "      <td>Supperminicar</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5/31/1980</td>\n",
       "      <td>1980</td>\n",
       "      <td>May</td>\n",
       "      <td>1</td>\n",
       "      <td>98.72</td>\n",
       "      <td>0.20</td>\n",
       "      <td>23829.233</td>\n",
       "      <td>1319</td>\n",
       "      <td>4</td>\n",
       "      <td>52.997</td>\n",
       "      <td>0.138197</td>\n",
       "      <td>5.3</td>\n",
       "      <td>770.4</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Year Month  Recession  Consumer_Confidence  Seasonality_Weight  \\\n",
       "0  1/31/1980  1980   Jan          1               108.24                0.50   \n",
       "1  2/29/1980  1980   Feb          1                98.75                0.75   \n",
       "2  3/31/1980  1980   Mar          1               107.48                0.20   \n",
       "3  4/30/1980  1980   Apr          1               115.01                1.00   \n",
       "4  5/31/1980  1980   May          1                98.72                0.20   \n",
       "\n",
       "       Price  Advertising_Expenditure  Competition     GDP  Growth_Rate  \\\n",
       "0  27483.571                     1558            7  60.223     0.010000   \n",
       "1  24308.678                     3048            4  45.986    -0.309594   \n",
       "2  28238.443                     3137            3  35.141    -0.308614   \n",
       "3  32615.149                     1653            7  45.673     0.230596   \n",
       "4  23829.233                     1319            4  52.997     0.138197   \n",
       "\n",
       "   unemployment_rate  Automobile_Sales     Vehicle_Type        City  \n",
       "0                5.4             456.0    Supperminicar     Georgia  \n",
       "1                4.8             555.9    Supperminicar    New York  \n",
       "2                3.4             620.0  Mediumfamilycar    New York  \n",
       "3                4.2             702.8    Supperminicar    Illinois  \n",
       "4                5.3             770.4  Smallfamiliycar  California  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 528 entries, 0 to 527\n",
      "Data columns (total 15 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   Date                     528 non-null    object \n",
      " 1   Year                     528 non-null    int64  \n",
      " 2   Month                    528 non-null    object \n",
      " 3   Recession                528 non-null    int64  \n",
      " 4   Consumer_Confidence      528 non-null    float64\n",
      " 5   Seasonality_Weight       528 non-null    float64\n",
      " 6   Price                    528 non-null    float64\n",
      " 7   Advertising_Expenditure  528 non-null    int64  \n",
      " 8   Competition              528 non-null    int64  \n",
      " 9   GDP                      528 non-null    float64\n",
      " 10  Growth_Rate              528 non-null    float64\n",
      " 11  unemployment_rate        528 non-null    float64\n",
      " 12  Automobile_Sales         528 non-null    float64\n",
      " 13  Vehicle_Type             528 non-null    object \n",
      " 14  City                     528 non-null    object \n",
      "dtypes: float64(7), int64(4), object(4)\n",
      "memory usage: 62.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating Visualizations for Data Analysis\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TASK 1.1: Develop a *Line chart* using the functionality of pandas to show how automobile sales fluctuate from year to year\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "You will require:-\n",
    "<br>to group the year and calculate the average on the 'Automobile Sales', as the data has years and months column\n",
    "<br>make use of .plot() with kind = 'line'\n",
    "<br>donot forget to include labels and title\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_line = df.groupby(df['Year'])['Automobile_Sales'].mean()\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "df_line.plot(kind = 'line')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Year Average in Automobile Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a solution template</summary>\n",
    "\n",
    "```python\n",
    "    #create data for plotting\n",
    "    df_line = df.groupby(df['Year'])['Automobile_Sales'].mean()\n",
    "    #create figure\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    df_line.plot(kind = 'line')\n",
    "    plt.xlabel('........')\n",
    "    plt.ylabel('.........')\n",
    "    plt.title('......................')\n",
    "    plt.show()\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Include the following on the plot\n",
    "ticks on x- axis with all the years, to identify the years of recession \n",
    "<br>annotation for at least two years of recession\n",
    "<br>Title as Automobile Sales during Recession\n",
    "<br> \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "    <p>\n",
    "    You can create the list for the range 1980 till 2023 and pass that list to the plt.xticks function or you can directly pass the range to the function.\n",
    "    You might need to rotate the ticks to an angle so that they fit in well on the axis\n",
    "    You can include annotation with plt.text(x, y, 'text to display') \n",
    "    </p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year\n",
       "1980    678.950000\n",
       "1981    633.408333\n",
       "1982    631.150000\n",
       "1991    655.891667\n",
       "2001    692.133333\n",
       "2009    631.691667\n",
       "Name: Automobile_Sales, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recession_df=df.groupby('Year')['Automobile_Sales'].mean().sort_values()\n",
    "recession_df.head(6).sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "df_line = df.groupby(df['Year'])['Automobile_Sales'].mean()\n",
    "df_line.plot(kind = 'line')\n",
    "plt.xticks(list(range(1980,2024)), rotation = 75)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Year Average in Automobile Sales')\n",
    "plt.text(1982, 650, '1981-82 Recession', rotation=45)\n",
    "plt.text(1991, 655, '1991-Recession', rotation=45)\n",
    "plt.text(2001, 693, '2001-Recession', rotation=45)\n",
    "plt.text(2009, 633, '2009-Recession', rotation=45)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    df_line = ...............\n",
    "    df_line.plot(kind = 'line')\n",
    "    plt.xticks(list(range(1980,2024)), rotation = 75)\n",
    "    plt.xlabel('..............')\n",
    "    plt.ylabel('............')\n",
    "    plt.title('...................')\n",
    "    plt.text(1982, 650, '1981-82 Recession')\n",
    "    plt.text(......, ..., '..............')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "```\n",
    "\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\">\n",
    "Save this plot as \"Line_Plot_1.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "####  TASK 1.2: Plot different lines for categories of vehicle type and analyse the trend to answer the question Is there a noticeable difference in sales trends between different vehicle types during recession periods?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "    You will require:-\n",
    "    <br>create a separate dataframe where the column recession has a value of '1'\n",
    "    <br>to group the year, vehicle_type and calculate the average on the 'Automobile Sales'\n",
    "    <br>one way is to -\n",
    "    <br>use as_index as false else you will endup with multiple-indexed datafame\n",
    "    <br>later set year as index and groupby vehicle over Sales and plot\n",
    "    <br>make use of .plot() with kind = 'line'\n",
    "    <br>do not forget to include labels and title\n",
    "</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_rec = df[df['Recession']==1]\n",
    "df_Mline = df_rec.groupby(['Year','Vehicle_Type'], as_index=False)['Automobile_Sales'].mean()\n",
    "df_Mline.set_index('Year', inplace=True)\n",
    "df_Mline = df_Mline.groupby(['Vehicle_Type'])['Automobile_Sales']\n",
    "df_Mline.plot(kind='line')\n",
    "plt.xlabel('Years')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Sales Trend Vehicle-wise during Recession')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    df_rec = df[df['Recession']==1]\n",
    "    df_Mline = df_rec.groupby(['Year','Vehicle_Type'], as_index=False)['Automobile_Sales'].mean()\n",
    "    df_Mline.set_index('Year', inplace=True)\n",
    "    df_Mline = df_Mline.groupby(['Vehicle_Type'])['Automobile_Sales']\n",
    "    df_Mline.plot(kind='line')\n",
    "    plt.xlabel('..............')\n",
    "    plt.ylabel('............')\n",
    "    plt.title('Sales Trend Vehicle-wise during Recession')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From the above plot, what insights have you gained on the sales of various vehicle types?<br> Type in your answer below:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Inference</summary>\n",
    "<p>\n",
    "Inference:\n",
    "From this plot, we can understand that during recession period, the sales for 'Sports type vehicles' declined because of the high cost of the vehicle.<br>while sales of the superminicar and smallfamilycar increased.<br><br>\n",
    "    </p>\n",
    "    </details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\">\n",
    "Save this plot as \"Line_Plot_2.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TASK 1.3: Use the functionality of **Seaborn Library** to create a visualization to compare the sales trend per vehicle type for a recession period with a non-recession period.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     To visualize the average number of vehicles sold during recession and non-recession periods, you can use a bar chart\n",
    "        <br> You will need to group recession average Automobile_Sales and then plot it<br>\n",
    "    Make use of sns.barplot(x=x,y=y, data = df)</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_df = df.groupby(['Recession','Vehicle_Type'])['Automobile_Sales'].mean().reset_index()\n",
    "\n",
    "# Create the bar chart using seaborn\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x='Recession', y='Automobile_Sales', hue='Vehicle_Type',  data=new_df)\n",
    "plt.xlabel('Period')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Average Automobile Sales during Recession and Non-Recession')\n",
    "plt.xticks(ticks=[0, 1], labels=['Non-Recession', 'Recession'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    new_df = df.groupby('Recession')['Automobile_Sales'].mean().reset_index()\n",
    "\n",
    "    # Create the bar chart using seaborn\n",
    "    plt.figure(figsize=(.........., ............)\n",
    "    sns.barplot(x='Recession', y='Automobile_Sales', hue='Recession',  data=new_df)\n",
    "    plt.xlabel('............')\n",
    "    plt.ylabel('...............')\n",
    "    plt.title('Average Automobile Sales during Recession and Non-Recession')\n",
    "    plt.xticks(ticks=[0, 1], labels=['Non-Recession', 'Recession'])\n",
    "    plt.show()\n",
    "```\n",
    "\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now you want to compare the sales of different vehicle types during a recession and a non-recession period\n",
    "<br>We recommend that you use the functionality of **Seaborn Library** to create this visualization\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     To visualize sales of different vehicles during recession and non-recession periods, you can use a bar chart\n",
    "        <br> You will need to group Recession, Vehicle_Type for average Automobile_Sales and then plot it<br>\n",
    "    Make use of sns.barplot(x=x,y=y, data = df)</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# Filter the data for recessionary periods\n",
    "    recession_data = df[df['Recession'] == 1]\n",
    "\n",
    "    dd=df.groupby(['Recession','Vehicle_Type'])['Automobile_Sales'].mean().reset_index()\n",
    "\n",
    "    # Calculate the total sales volume by vehicle type during recessions\n",
    "    #sales_by_vehicle_type = recession_data.groupby('Vehicle_Type')['Automobile_Sales'].sum().reset_index()\n",
    "\n",
    "    # Create the grouped bar chart using seaborn\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    sns.barplot(x='......', y='........', hue='Vehicle_Type', data=dd)\n",
    "    plt.xticks(ticks=[0, 1], labels=['Non-Recession', 'Recession'])\n",
    "    plt.xlabel('.............')\n",
    "    plt.ylabel('..............')\n",
    "    plt.title('Vehicle-Wise Sales during Recession and Non-Recession Period')\n",
    "\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "   # Filter the data for recessionary periods\n",
    "    recession_data = df[df['Recession'] == 1]\n",
    "\n",
    "    dd=df.groupby(['Recession','Vehicle_Type'])['Automobile_Sales'].mean().reset_index()\n",
    "\n",
    "    # Calculate the total sales volume by vehicle type during recessions\n",
    "    #sales_by_vehicle_type = recession_data.groupby('Vehicle_Type')['Automobile_Sales'].sum().reset_index()\n",
    "\n",
    "    # Create the grouped bar chart using seaborn\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    sns.barplot(x='......', y='........', hue='Vehicle_Type', data=dd)\n",
    "    plt.xticks(ticks=[0, 1], labels=['Non-Recession', 'Recession'])\n",
    "    plt.xlabel('.............')\n",
    "    plt.ylabel('..............')\n",
    "    plt.title('Vehicle-Wise Sales during Recession and Non-Recession Period')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From the above chart what insights have you gained on the overall sales of automobiles during recession? <br> Type your answer below:-\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Inference</summary>\n",
    "\n",
    "From this plot, we can understand that there is a drastic decline in the overall sales of the automobiles during recession.<br>However, the most affected type of vehicle is executivecar and sports<br><br>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\">\n",
    "Save this plot as \"Bar_Chart.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TASK 1.4: Use sub plotting to compare the variations in GDP during recession and non-recession period by developing line plots for each period.\n",
    "<br>Now, you want to find more insights from the data to understand the reason. <br>Plot a two line charts using subplotting to answer:-\n",
    "#### How did the GDP vary over time during recession and non-recession periods? \n",
    "<br>Make use of <u>add_subplot()</u> from Matplotlib for this comparision.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rec_data = df[df['Recession'] == 1]\n",
    "non_rec_data = df[df['Recession'] == 0]\n",
    "    \n",
    "#Figure\n",
    "fig=plt.figure(figsize=(12, 6))\n",
    "    \n",
    "#Create different axes for subploting\n",
    "ax0 = fig.add_subplot(1, 2, 1) # add subplot 1 (1 row, 2 columns, first plot)\n",
    "ax1 = fig.add_subplot(1 ,2 ,2 ) # add subplot 2 (1 row, 2 columns, second plot). \n",
    "\n",
    "#plt.subplot(1, 2, 1)\n",
    "sns.lineplot(x='Year', y='GDP', data=rec_data, label='Recession', ax=ax0)\n",
    "ax0.set_xlabel('Year')\n",
    "ax0.set_ylabel('GDP')\n",
    "ax0.set_title('GDP Variation during Recession Period')\n",
    "\n",
    "#plt.subplot(1, 2, 2)\n",
    "sns.lineplot(x='Year', y='GDP', data=non_rec_data, label='Non-Recession',ax=ax1)\n",
    "ax1.set_xlabel('Year')\n",
    "ax1.set_ylabel('GDP')\n",
    "ax1.set_title('GDP Variation during Non-Recession Period')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    #Create dataframes for recession and non-recession period\n",
    "    rec_data = df[df['Recession'] == 1]\n",
    "    non_rec_data = df[df['Recession'] == 0]\n",
    "    \n",
    "    #Figure\n",
    "    fig=plt.figure(figsize=(12, 6))\n",
    "    \n",
    "    #Create different axes for subploting\n",
    "    ax0 = fig.add_subplot(1, 2, 1) # add subplot 1 (1 row, 2 columns, first plot)\n",
    "    ax1 = fig.add_subplot(... ,... ,... ) # add subplot 2 (1 row, 2 columns, second plot). \n",
    "    \n",
    "    #plt.subplot(1, 2, 1)\n",
    "    sns.lineplot(x='Year', y='GDP', data=rec_data, label='Recession', ax=ax0)\n",
    "    ax0.set_xlabel('Year')\n",
    "    ax0.set_ylabel('GDP')\n",
    "    ax0.set_title('GDP Variation during Recession Period')\n",
    "    \n",
    "    #plt.subplot(1, 2, 2)\n",
    "    sns.lineplot(x='......', y='......', data=........, label='.........',ax=...)\n",
    "    ax1.set_xlabel('.....')\n",
    "    ax1.set_ylabel('.......')\n",
    "    ax1.set_title('..........')\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "   #------------------------------------------------Alternatively--------------\n",
    "   #Using subplot()\n",
    "    plt.figure(figsize=(............, ..........))\n",
    "    \n",
    "    #subplot 1\n",
    "    plt.subplot(1, 2, 1)\n",
    "    sns.lineplot(x='.........', y='......', data=.........., label='......')\n",
    "    plt.xlabel('.......')\n",
    "    plt.ylabel('..........')\n",
    "    plt.legend()\n",
    "    #subplot 1\n",
    "    plt.subplot(1, 2, 2)\n",
    "    sns.lineplot(x='.........', y='......', data=.........., label='......')\n",
    "    plt.xlabel('.......')\n",
    "    plt.ylabel('..........')\n",
    "    plt.legend()\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference\n",
    "From this plot, it is evident that during recession, the GDP of the country was in a low range, might have afected the overall sales of the company<br><br>\n",
    "<span style=\"color:red\">\n",
    "Save this plot as \"Subplot.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TASK 1.5: Develop a Bubble plot for displaying the impact of seasonality on Automobile Sales.\n",
    "<br>How has seasonality impacted the sales, in which months the sales were high or low? Check it for non-recession years to understand the trend\n",
    "\n",
    "##### Develop a Bubble plot for displaying Automobile Sales for every month and use Seasonality Weight for representing the size of each bubble<br>\n",
    "Title this plot as 'Seasonality impact on Automobile Sales'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     You can create Bubble Chart by calling the scatter()\n",
    "        <br>Pass the 'Month' and 'Automobile_Sales' to the functions as x and y and then use Seasonality weight for size parameter</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Recession</th>\n",
       "      <th>Consumer_Confidence</th>\n",
       "      <th>Seasonality_Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Advertising_Expenditure</th>\n",
       "      <th>Competition</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Growth_Rate</th>\n",
       "      <th>unemployment_rate</th>\n",
       "      <th>Automobile_Sales</th>\n",
       "      <th>Vehicle_Type</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2/28/1983</td>\n",
       "      <td>1983</td>\n",
       "      <td>Feb</td>\n",
       "      <td>0</td>\n",
       "      <td>126.06</td>\n",
       "      <td>0.75</td>\n",
       "      <td>15201.649</td>\n",
       "      <td>4621</td>\n",
       "      <td>4</td>\n",
       "      <td>12.819</td>\n",
       "      <td>-1.119666</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3799.1</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>3/31/1983</td>\n",
       "      <td>1983</td>\n",
       "      <td>Mar</td>\n",
       "      <td>0</td>\n",
       "      <td>92.67</td>\n",
       "      <td>1.50</td>\n",
       "      <td>18359.070</td>\n",
       "      <td>3038</td>\n",
       "      <td>8</td>\n",
       "      <td>12.945</td>\n",
       "      <td>0.009733</td>\n",
       "      <td>1.5</td>\n",
       "      <td>3533.5</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>4/30/1983</td>\n",
       "      <td>1983</td>\n",
       "      <td>Apr</td>\n",
       "      <td>0</td>\n",
       "      <td>96.39</td>\n",
       "      <td>1.00</td>\n",
       "      <td>25984.306</td>\n",
       "      <td>4490</td>\n",
       "      <td>8</td>\n",
       "      <td>25.206</td>\n",
       "      <td>0.486432</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3240.4</td>\n",
       "      <td>Supperminicar</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>5/31/1983</td>\n",
       "      <td>1983</td>\n",
       "      <td>May</td>\n",
       "      <td>0</td>\n",
       "      <td>91.81</td>\n",
       "      <td>1.50</td>\n",
       "      <td>28692.333</td>\n",
       "      <td>4677</td>\n",
       "      <td>8</td>\n",
       "      <td>14.630</td>\n",
       "      <td>-0.722898</td>\n",
       "      <td>2.3</td>\n",
       "      <td>908.1</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>6/30/1983</td>\n",
       "      <td>1983</td>\n",
       "      <td>Jun</td>\n",
       "      <td>0</td>\n",
       "      <td>106.16</td>\n",
       "      <td>0.75</td>\n",
       "      <td>25856.841</td>\n",
       "      <td>2118</td>\n",
       "      <td>5</td>\n",
       "      <td>18.765</td>\n",
       "      <td>0.220357</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4769.8</td>\n",
       "      <td>Mediumfamilycar</td>\n",
       "      <td>Illinois</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>523</th>\n",
       "      <td>8/31/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Aug</td>\n",
       "      <td>0</td>\n",
       "      <td>103.36</td>\n",
       "      <td>0.25</td>\n",
       "      <td>27852.993</td>\n",
       "      <td>1793</td>\n",
       "      <td>6</td>\n",
       "      <td>57.169</td>\n",
       "      <td>0.764155</td>\n",
       "      <td>2.6</td>\n",
       "      <td>1579.6</td>\n",
       "      <td>Executivecar</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>9/30/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Sep</td>\n",
       "      <td>0</td>\n",
       "      <td>101.55</td>\n",
       "      <td>0.07</td>\n",
       "      <td>21183.704</td>\n",
       "      <td>1028</td>\n",
       "      <td>5</td>\n",
       "      <td>59.315</td>\n",
       "      <td>0.036180</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1123.4</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>10/31/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Oct</td>\n",
       "      <td>0</td>\n",
       "      <td>124.66</td>\n",
       "      <td>0.12</td>\n",
       "      <td>15975.589</td>\n",
       "      <td>1148</td>\n",
       "      <td>9</td>\n",
       "      <td>19.472</td>\n",
       "      <td>-2.046169</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1685.9</td>\n",
       "      <td>Sports</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>11/30/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Nov</td>\n",
       "      <td>0</td>\n",
       "      <td>97.09</td>\n",
       "      <td>0.25</td>\n",
       "      <td>16862.288</td>\n",
       "      <td>4850</td>\n",
       "      <td>5</td>\n",
       "      <td>27.904</td>\n",
       "      <td>0.302179</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2124.6</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>12/31/2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>Dec</td>\n",
       "      <td>0</td>\n",
       "      <td>95.92</td>\n",
       "      <td>0.34</td>\n",
       "      <td>25240.425</td>\n",
       "      <td>2319</td>\n",
       "      <td>3</td>\n",
       "      <td>13.518</td>\n",
       "      <td>-1.064211</td>\n",
       "      <td>2.1</td>\n",
       "      <td>3538.5</td>\n",
       "      <td>Smallfamiliycar</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>415 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  Year Month  Recession  Consumer_Confidence  \\\n",
       "113   2/28/1983  1983   Feb          0               126.06   \n",
       "114   3/31/1983  1983   Mar          0                92.67   \n",
       "115   4/30/1983  1983   Apr          0                96.39   \n",
       "116   5/31/1983  1983   May          0                91.81   \n",
       "117   6/30/1983  1983   Jun          0               106.16   \n",
       "..          ...   ...   ...        ...                  ...   \n",
       "523   8/31/2023  2023   Aug          0               103.36   \n",
       "524   9/30/2023  2023   Sep          0               101.55   \n",
       "525  10/31/2023  2023   Oct          0               124.66   \n",
       "526  11/30/2023  2023   Nov          0                97.09   \n",
       "527  12/31/2023  2023   Dec          0                95.92   \n",
       "\n",
       "     Seasonality_Weight      Price  Advertising_Expenditure  Competition  \\\n",
       "113                0.75  15201.649                     4621            4   \n",
       "114                1.50  18359.070                     3038            8   \n",
       "115                1.00  25984.306                     4490            8   \n",
       "116                1.50  28692.333                     4677            8   \n",
       "117                0.75  25856.841                     2118            5   \n",
       "..                  ...        ...                      ...          ...   \n",
       "523                0.25  27852.993                     1793            6   \n",
       "524                0.07  21183.704                     1028            5   \n",
       "525                0.12  15975.589                     1148            9   \n",
       "526                0.25  16862.288                     4850            5   \n",
       "527                0.34  25240.425                     2319            3   \n",
       "\n",
       "        GDP  Growth_Rate  unemployment_rate  Automobile_Sales  \\\n",
       "113  12.819    -1.119666                2.4            3799.1   \n",
       "114  12.945     0.009733                1.5            3533.5   \n",
       "115  25.206     0.486432                2.0            3240.4   \n",
       "116  14.630    -0.722898                2.3             908.1   \n",
       "117  18.765     0.220357                2.3            4769.8   \n",
       "..      ...          ...                ...               ...   \n",
       "523  57.169     0.764155                2.6            1579.6   \n",
       "524  59.315     0.036180                2.5            1123.4   \n",
       "525  19.472    -2.046169                2.5            1685.9   \n",
       "526  27.904     0.302179                2.9            2124.6   \n",
       "527  13.518    -1.064211                2.1            3538.5   \n",
       "\n",
       "        Vehicle_Type        City  \n",
       "113           Sports     Georgia  \n",
       "114  Smallfamiliycar  California  \n",
       "115    Supperminicar    Illinois  \n",
       "116  Smallfamiliycar  California  \n",
       "117  Mediumfamilycar    Illinois  \n",
       "..               ...         ...  \n",
       "523     Executivecar    New York  \n",
       "524  Smallfamiliycar  California  \n",
       "525           Sports  California  \n",
       "526  Smallfamiliycar     Georgia  \n",
       "527  Smallfamiliycar     Georgia  \n",
       "\n",
       "[415 rows x 15 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_rec_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "non_rec_data = df[df['Recession'] == 0]\n",
    "    \n",
    "size=non_rec_data['Seasonality_Weight'] #for bubble effect\n",
    "    \n",
    "sns.scatterplot(\n",
    "    data=non_rec_data,\n",
    "    x='Month',\n",
    "    y='Automobile_Sales',\n",
    "    size=size,\n",
    "    hue='Seasonality_Weight',\n",
    "    legend=False\n",
    ")\n",
    "    \n",
    "#you can further include hue='Seasonality_Weight', legend=False)\n",
    "\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Automobile_Sales')\n",
    "plt.title('Seasonality impact on Automobile Sales')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    non_rec_data = df[df['Recession'] == 0]\n",
    "    \n",
    "    size=non_rec_data['Seasonality_Weight'] #for bubble effect\n",
    "    \n",
    "    sns.scatterplot(data=non_rec_data, x='........', y='........', size=size)\n",
    "    \n",
    "    #you can further include hue='Seasonality_Weight', legend=False)\n",
    "\n",
    "    plt.xlabel('Month')\n",
    "    plt.ylabel('Automobile_Sales')\n",
    "    plt.title('Seasonality impact on Automobile Sales')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference\n",
    "From this plot, it is evident that seasonality has not affected on the overall sales. However, there is a drastic raise in sales in the month of April<br><br>\n",
    "<span style=\"color:red\">\n",
    "Save this plot as \"Bubble.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ### TASK 1.6: Use the functionality of Matplotlib to develop a scatter plot to identify the correlation between average vehicle price relate to the sales volume during recessions.\n",
    " #### From the data, develop a scatter plot to identify if there a correlation between consumer confidence and automobile sales during recession period? \n",
    " <br> Title this plot as 'Consumer Confidence and Automobile Sales during Recessions'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     You can create dataframe where recession is '1'.\n",
    "        <br>Pass the 'Consumer_Confidence' and 'Automobile_Sales' to the plt.scatter()</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Create dataframes for recession and non-recession period\n",
    "rec_data = df[df['Recession'] == 1]\n",
    "plt.scatter(rec_data['Consumer_Confidence'], rec_data['Automobile_Sales'])\n",
    "\n",
    "plt.xlabel('Consumer Confidence')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Scatter Plot Consumer Confidence vs. Automobile Sales During Recession Periods')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    #Create dataframes for recession and non-recession period\n",
    "    rec_data = df[df['Recession'] == 1]\n",
    "    plt.scatter(rec_data['Consumer_Confidence'], rec_data['Automobile_Sales'])\n",
    "    \n",
    "    plt.xlabel('.....')\n",
    "    plt.ylabel('.......')\n",
    "    plt.title('..........')\n",
    "    plt.show()\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    " ### How does the average vehicle price relate to the sales volume during recessions?\n",
    " <br> Plot another scatter plot and title it as 'Relationship between Average Vehicle Price and Sales during Recessions'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rec_data = df[df['Recession'] == 1]\n",
    "plt.scatter(rec_data['Price'], rec_data['Automobile_Sales'])\n",
    "    \n",
    "plt.xlabel('Price')\n",
    "plt.ylabel('Automobile Sales')\n",
    "plt.title('Scatter Plot Price vs. Automobile Sales During Recession Periods')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    #Create dataframes for recession and non-recession period\n",
    "    rec_data = df[df['Recession'] == 1]\n",
    "    plt.scatter(recession_data['Price'], rec_data['Automobile_Sales'])\n",
    "    \n",
    "    plt.xlabel('.....')\n",
    "    plt.ylabel('.......')\n",
    "    plt.title('..........')\n",
    "    plt.show()\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference\n",
    "There is not much relation!<br><br>\n",
    "<span style=\"color:red\">\n",
    "Save this plot as \"Scatter.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ### TASK 1.7: Create a pie chart to display the portion of advertising expenditure of XYZAutomotives during recession and non-recession periods.\n",
    " <br>How did the advertising expenditure of XYZAutomotives change during recession and non-recession periods? \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     You can create two dataframe for recession and nonreccession period.\n",
    "    <br> Calculate the sum of Advertising_Expenditure for both dataframes\n",
    "    <br> Pass these total values to plt.pie(). May include labels as ['Recession', 'Non-Recession']\n",
    "        <br>Feel Free to customie the pie further\n",
    "    <br>title this plot as  - Advertising Expenditure during Recession and Non-Recession Periods</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filter the data \n",
    "Rdata = df[df['Recession'] == 1]\n",
    "NRdata = df[df['Recession'] == 0]\n",
    "\n",
    "# Calculate the total advertising expenditure for both periods\n",
    "RAtotal = Rdata['Advertising_Expenditure'].sum()\n",
    "NRAtotal = NRdata['Advertising_Expenditure'].sum()\n",
    "\n",
    "# Create a pie chart for the advertising expenditure \n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "labels = ['Recession', 'Non-Recession']\n",
    "sizes = [RAtotal, NRAtotal]\n",
    "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "plt.title('Portion of Advertising Expenditure of XYZAutomotives')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "<summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    # Filter the data \n",
    "    Rdata = df[df['Recession'] == 1]\n",
    "    NRdata = df[df['Recession'] == 0]\n",
    "\n",
    "    # Calculate the total advertising expenditure for both periods\n",
    "    RAtotal = Rdata['...........'].sum()\n",
    "    NRAtotal = NRdata['...........'].sum()\n",
    "\n",
    "    # Create a pie chart for the advertising expenditure \n",
    "    plt.figure(figsize=(8, 6))\n",
    "\n",
    "    labels = ['Recession', 'Non-Recession']\n",
    "    sizes = [RAtotal, NRtotal]\n",
    "    plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "    plt.title('...........................')\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From the above plot, what insights do you find on the advertisement expenditure during recession and non recession periods?<br> Type your answer below:-\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Inference</summary>\n",
    "It seems ABCAutomotives has been spending much more on the advertisements during non-recession periods as compared to during recession times. Fair enough!<br><br></details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\">\n",
    "Save this plot as \"Pie_1.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TASK 1.8: Develop a pie chart to display the total Advertisement expenditure for each vehicle type during recession period.<br>\n",
    "Can we observe the share of each vehicle type in total expenditure during recessions? \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "     You will be required to group vehicle type for sum of advertisement expenditure.\n",
    "    <br> the plot a pie with the data, May include relevant labels\n",
    "    <br>title this plot as  - Share of Each Vehicle Type in Total Expenditure during Recessions</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Filter the data \n",
    "Rdata = df[df['Recession'] == 1]\n",
    "\n",
    "# Calculate the sales volume by vehicle type during recessions\n",
    "VTexpenditure = Rdata.groupby('Vehicle_Type')['Advertising_Expenditure'].sum()\n",
    "\n",
    "# Create a pie chart for the share of each vehicle type in total expenditure during recessions\n",
    "plt.figure(figsize=(12,6))\n",
    "\n",
    "labels = VTexpenditure.index\n",
    "sizes = VTexpenditure.values\n",
    "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "plt.title('Advertisement expenditure for each vehicle type during recession period')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "    # Filter the data \n",
    "    Rdata = df[df['Recession'] == 1]\n",
    "\n",
    "    # Calculate the sales volume by vehicle type during recessions\n",
    "    VTexpenditure = Rdata.groupby('..........')['.............'].sum()\n",
    "\n",
    "    # Create a pie chart for the share of each vehicle type in total expenditure during recessions\n",
    "    plt.figure(figsize=(..., ...))\n",
    "\n",
    "    labels = VTexpenditure.index\n",
    "    sizes = VTexpenditure.values\n",
    "    plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "    plt.title('....................')\n",
    "\n",
    "    plt.show()\n",
    "```\n",
    "    </details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference\n",
    "During recession the advertisements were mostly focued on low price range vehicle. A wise decision!<br><br>\n",
    "<span style=\"color:red\">\n",
    "Save this plot as \"Pie_2.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ### TASK 1.9: Develop a lineplot to analyse the effect of the unemployment rate on vehicle type and sales during the Recession Period.\n",
    " <br>Analyze the effect of the unemployment rate on vehicle type and sales during the Recession Period\n",
    " #### You can create a lineplot and title the plot as 'Effect of Unemployment Rate on Vehicle Type and Sales'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for a hint</summary>\n",
    "\n",
    "<p>\n",
    "    Filter out the data for recession period<br>\n",
    "     Make use of lineplot() from seaborn and pass the relavent data</p>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_106014/2674897019.py:2: UserWarning: \n",
      "The markers list has fewer values (1) than needed (5) and will cycle, which may produce an uninterpretable plot.\n",
      "  sns.lineplot(\n",
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "/usr/local/lib/python3.9/dist-packages/seaborn/_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff8d4527970>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_rec = df[df['Recession']==1]\n",
    "sns.lineplot(\n",
    "    data=df_rec,\n",
    "    x='unemployment_rate',\n",
    "    y='Automobile_Sales',\n",
    "    hue='Vehicle_Type',\n",
    "    style='Vehicle_Type',\n",
    "    markers='o',\n",
    "    err_style=None\n",
    ")\n",
    "\n",
    "plt.ylim(0,850)\n",
    "plt.legend(loc=(0.05,.3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details>\n",
    "    <summary>Click here for Solution template</summary>\n",
    "\n",
    "```python\n",
    "df_rec = df[df['Recession']==1]\n",
    "sns.lineplot(data=df_rec, x='..........', y='.........',\n",
    "             hue='Vehicle_Type', style='Vehicle_Type', markers='o', err_style=None)\n",
    "plt.ylim(0,850)\n",
    "plt.legend(loc=(0.05,.3))\n",
    "```\n",
    "\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### From the above plot, what insights have you gained on the sales of superminicar, smallfamilycar, mediumminicar?<br> Type your answer below:-\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Inference</summary>\n",
    "During recession, buying pattern changed, the sales of low range vehicle like superminicar,smallfamilycar and Mediumminicar<br><br>\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red\">\n",
    "Save this plot as \"line_plot_3.png\"</span><br>\n",
    "*Hint: You can right lick on the plot and then click on \"Save image as\" option to save it on your local machine*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### OPTIONAL : TASK 1.10 Create a map on the hightest sales region/offices of the company during recession period\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "from pyodide.http import pyfetch\n",
    "\n",
    "async def download(url, filename):\n",
    "    response = await pyfetch(url)\n",
    "    if response.status == 200:\n",
    "        with open(filename, \"wb\") as f:\n",
    "            f.write(await response.bytes())\n",
    "\n",
    "path = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/us-states.json'\n",
    "await download(path, \"us-states.json\")\n",
    "\n",
    "filename = \"us-states.json\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/us-states.json'\n",
    "\n",
    "import requests\n",
    "us_states_json = requests.get(path).json()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "#### You found that the datset also contains the location/city for company offices. Now you want to show the recession impact on various offices/city sales by developing a choropleth\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "        \n",
       "    \n",
       "            var tile_layer_75580a118300660b5c97f93e15228f58 = L.tileLayer(\n",
       "                &quot;https://tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 19, &quot;maxZoom&quot;: 19, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            );\n",
       "        \n",
       "    \n",
       "            tile_layer_75580a118300660b5c97f93e15228f58.addTo(map_841e1ef93faa5fef0868f8b56a0389a0);\n",
       "        \n",
       "    \n",
       "            var choropleth_d7e6edd74bec1979339475d543518c44 = L.featureGroup(\n",
       "                {}\n",
       "            );\n",
       "        \n",
       "    \n",
       "        function geo_json_e3b2295f492c383c6ab4f8dda3c4633a_styler(feature) {\n",
       "            switch(feature.id) {\n",
       "                case &quot;AL&quot;: case &quot;AK&quot;: case &quot;AZ&quot;: case &quot;AR&quot;: case &quot;CO&quot;: case &quot;CT&quot;: case &quot;DE&quot;: case &quot;FL&quot;: case &quot;HI&quot;: case &quot;ID&quot;: case &quot;IN&quot;: case &quot;IA&quot;: case &quot;KS&quot;: case &quot;KY&quot;: case &quot;LA&quot;: case &quot;ME&quot;: case &quot;MD&quot;: case &quot;MA&quot;: case &quot;MI&quot;: case &quot;MN&quot;: case &quot;MS&quot;: case &quot;MO&quot;: case &quot;MT&quot;: case &quot;NE&quot;: case &quot;NV&quot;: case &quot;NH&quot;: case &quot;NJ&quot;: case &quot;NM&quot;: case &quot;NC&quot;: case &quot;ND&quot;: case &quot;OH&quot;: case &quot;OK&quot;: case &quot;OR&quot;: case &quot;PA&quot;: case &quot;RI&quot;: case &quot;SC&quot;: case &quot;SD&quot;: case &quot;TN&quot;: case &quot;TX&quot;: case &quot;UT&quot;: case &quot;VT&quot;: case &quot;VA&quot;: case &quot;WA&quot;: case &quot;WV&quot;: case &quot;WI&quot;: case &quot;WY&quot;: \n",
       "                    return {&quot;color&quot;: &quot;black&quot;, &quot;fillColor&quot;: &quot;black&quot;, &quot;fillOpacity&quot;: 0.7, &quot;opacity&quot;: 0.2, &quot;weight&quot;: 1};\n",
       "                case &quot;CA&quot;: \n",
       "                    return {&quot;color&quot;: &quot;black&quot;, &quot;fillColor&quot;: &quot;#f03b20&quot;, &quot;fillOpacity&quot;: 0.7, &quot;opacity&quot;: 0.2, &quot;weight&quot;: 1};\n",
       "                case &quot;GA&quot;: \n",
       "                    return {&quot;color&quot;: &quot;black&quot;, &quot;fillColor&quot;: &quot;#fed976&quot;, &quot;fillOpacity&quot;: 0.7, &quot;opacity&quot;: 0.2, &quot;weight&quot;: 1};\n",
       "                case &quot;IL&quot;: \n",
       "                    return {&quot;color&quot;: &quot;black&quot;, &quot;fillColor&quot;: &quot;#ffffb2&quot;, &quot;fillOpacity&quot;: 0.7, &quot;opacity&quot;: 0.2, &quot;weight&quot;: 1};\n",
       "                default:\n",
       "                    return {&quot;color&quot;: &quot;black&quot;, &quot;fillColor&quot;: &quot;#bd0026&quot;, &quot;fillOpacity&quot;: 0.7, &quot;opacity&quot;: 0.2, &quot;weight&quot;: 1};\n",
       "            }\n",
       "        }\n",
       "\n",
       "        function geo_json_e3b2295f492c383c6ab4f8dda3c4633a_onEachFeature(feature, layer) {\n",
       "            layer.on({\n",
       "            });\n",
       "        };\n",
       "        var geo_json_e3b2295f492c383c6ab4f8dda3c4633a = L.geoJson(null, {\n",
       "                onEachFeature: geo_json_e3b2295f492c383c6ab4f8dda3c4633a_onEachFeature,\n",
       "            \n",
       "                style: geo_json_e3b2295f492c383c6ab4f8dda3c4633a_styler,\n",
       "        });\n",
       "\n",
       "        function geo_json_e3b2295f492c383c6ab4f8dda3c4633a_add (data) {\n",
       "            geo_json_e3b2295f492c383c6ab4f8dda3c4633a\n",
       "                .addData(data);\n",
       "        }\n",
       "            geo_json_e3b2295f492c383c6ab4f8dda3c4633a_add({&quot;features&quot;: [{&quot;geometry&quot;: {&quot;coordinates&quot;: [[[-87.359296, 35.00118], [-85.606675, 34.984749], [-85.431413, 34.124869], [-85.184951, 32.859696], [-85.069935, 32.580372], [-84.960397, 32.421541], [-85.004212, 32.322956], [-84.889196, 32.262709], [-85.058981, 32.13674], [-85.053504, 32.01077], [-85.141136, 31.840985], [-85.042551, 31.539753], [-85.113751, 31.27686], [-85.004212, 31.003013], [-85.497137, 30.997536], [-87.600282, 30.997536], [-87.633143, 30.86609], [-87.408589, 30.674397], [-87.446927, 30.510088], [-87.37025, 30.427934], [-87.518128, 30.280057], [-87.655051, 30.247195], [-87.90699, 30.411504], [-87.934375, 30.657966], [-88.011052, 30.685351], [-88.10416, 30.499135], [-88.137022, 30.318396], [-88.394438, 30.367688], [-88.471115, 31.895754], [-88.241084, 33.796253], [-88.098683, 34.891641], [-88.202745, 34.995703], [-87.359296, 35.00118]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;AL&quot;, &quot;properties&quot;: {&quot;name&quot;: &quot;Alabama&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;geometry&quot;: {&quot;coordinates&quot;: [[[[-131.602021, 55.117982], [-131.569159, 55.28229], [-131.355558, 55.183705], [-131.38842, 55.01392], [-131.645836, 55.035827], [-131.602021, 55.117982]]], [[[-131.832052, 55.42469], [-131.645836, 55.304197], [-131.749898, 55.128935], [-131.832052, 55.189182], [-131.832052, 55.42469]]], [[[-132.976733, 56.437924], [-132.735747, 56.459832], [-132.631685, 56.421493], [-132.664547, 56.273616], [-132.878148, 56.240754], [-133.069841, 56.333862], [-132.976733, 56.437924]]], [[[-133.595627, 56.350293], [-133.162949, 56.317431], [-133.05341, 56.125739], [-132.620732, 55.912138], [-132.472854, 55.780691], [-132.4619, 55.671152], [-132.357838, 55.649245], [-132.341408, 55.506844], [-132.166146, 55.364444], [-132.144238, 55.238474], [-132.029222, 55.276813], [-131.97993, 55.178228], [-131.958022, 54.789365], 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       "\n",
       "        \n",
       "    \n",
       "    geo_json_e3b2295f492c383c6ab4f8dda3c4633a.bindTooltip(\n",
       "    function(layer){\n",
       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
       "    \n",
       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
       "    let fields = [&quot;name&quot;];\n",
       "    let aliases = [&quot;name&quot;];\n",
       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
       "        String(\n",
       "        fields.map(\n",
       "        (v,i)=&gt;\n",
       "        `&lt;tr&gt;\n",
       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
       "            \n",
       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
       "    +&#x27;&lt;/table&gt;&#x27;;\n",
       "    div.innerHTML=table;\n",
       "    \n",
       "    return div\n",
       "    }\n",
       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
       "                     \n",
       "    \n",
       "            geo_json_e3b2295f492c383c6ab4f8dda3c4633a.addTo(choropleth_d7e6edd74bec1979339475d543518c44);\n",
       "        \n",
       "    \n",
       "    var color_map_723809c1943d690200388837a7a464c5 = {};\n",
       "\n",
       "    \n",
       "    color_map_723809c1943d690200388837a7a464c5.color = d3.scale.threshold()\n",
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       "    \n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.x = d3.scale.linear()\n",
       "              .domain([16874.7, 19954.6])\n",
       "              .range([0, 450 - 50]);\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.legend = L.control({position: &#x27;topright&#x27;});\n",
       "    color_map_723809c1943d690200388837a7a464c5.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
       "    color_map_723809c1943d690200388837a7a464c5.legend.addTo(map_841e1ef93faa5fef0868f8b56a0389a0);\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.xAxis = d3.svg.axis()\n",
       "        .scale(color_map_723809c1943d690200388837a7a464c5.x)\n",
       "        .orient(&quot;top&quot;)\n",
       "        .tickSize(1)\n",
       "        .tickValues([16874.7, 17388.016666666666, 17901.333333333332, 18414.65, 18927.966666666667, 19441.283333333333, 19954.6]);\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
       "        .attr(&quot;width&quot;, 450)\n",
       "        .attr(&quot;height&quot;, 40);\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.g = color_map_723809c1943d690200388837a7a464c5.svg.append(&quot;g&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
       "        .attr(&quot;fill&quot;, &quot;black&quot;)\n",
       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.g.selectAll(&quot;rect&quot;)\n",
       "        .data(color_map_723809c1943d690200388837a7a464c5.color.range().map(function(d, i) {\n",
       "          return {\n",
       "            x0: i ? color_map_723809c1943d690200388837a7a464c5.x(color_map_723809c1943d690200388837a7a464c5.color.domain()[i - 1]) : color_map_723809c1943d690200388837a7a464c5.x.range()[0],\n",
       "            x1: i &lt; color_map_723809c1943d690200388837a7a464c5.color.domain().length ? color_map_723809c1943d690200388837a7a464c5.x(color_map_723809c1943d690200388837a7a464c5.color.domain()[i]) : color_map_723809c1943d690200388837a7a464c5.x.range()[1],\n",
       "            z: d\n",
       "          };\n",
       "        }))\n",
       "      .enter().append(&quot;rect&quot;)\n",
       "        .attr(&quot;height&quot;, 40 - 30)\n",
       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
       "\n",
       "    color_map_723809c1943d690200388837a7a464c5.g.call(color_map_723809c1943d690200388837a7a464c5.xAxis).append(&quot;text&quot;)\n",
       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
       "        .attr(&quot;y&quot;, 21)\n",
       "        .attr(&quot;fill&quot;, &quot;black&quot;)\n",
       "        .text(&quot;Automobile Sales during Recession&quot;);\n",
       "    \n",
       "            choropleth_d7e6edd74bec1979339475d543518c44.addTo(map_841e1ef93faa5fef0868f8b56a0389a0);\n",
       "        \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7ff8d4162460>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recession_data = df[df['Recession'] == 1]\n",
    "\n",
    "# Calculate the total sales by city\n",
    "sales_by_city = recession_data.groupby('City')['Automobile_Sales'].sum().reset_index()\n",
    "\n",
    "# Create a base map centered on the United States\n",
    "map1 = folium.Map(location=[37.0902, -95.7129], zoom_start=4)\n",
    "\n",
    "# Create a choropleth layer using Folium\n",
    "choropleth = folium.Choropleth(\n",
    "    geo_data= us_states_json,  # GeoJSON file with state boundaries\n",
    "    data=sales_by_city,\n",
    "    columns=['City', 'Automobile_Sales'],\n",
    "    key_on='feature.properties.name',\n",
    "    fill_color='YlOrRd',\n",
    "    fill_opacity=0.7,\n",
    "    line_opacity=0.2,\n",
    "    legend_name='Automobile Sales during Recession').add_to(map1)\n",
    "\n",
    "\n",
    "# Add tooltips to the choropleth layer\n",
    "choropleth.geojson.add_child(\n",
    "    folium.features.GeoJsonTooltip(['name'], labels=True)\n",
    ")\n",
    "\n",
    "# Display the map\n",
    "map1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click for Solution</summary>\n",
    "    \n",
    "```python\n",
    "\n",
    "    # Filter the data for the recession period and specific cities\n",
    "    recession_data = data[data['Recession'] == 1]\n",
    "\n",
    "    # Calculate the total sales by city\n",
    "    sales_by_city = recession_data.groupby('City')['Automobile_Sales'].sum().reset_index()\n",
    "\n",
    "    # Create a base map centered on the United States\n",
    "    map1 = folium.Map(location=[37.0902, -95.7129], zoom_start=4)\n",
    "\n",
    "    # Create a choropleth layer using Folium\n",
    "    choropleth = folium.Choropleth(\n",
    "        geo_data= 'us-states.json',  # GeoJSON file with state boundaries\n",
    "        data=sales_by_city,\n",
    "        columns=['City', 'Automobile_Sales'],\n",
    "        key_on='feature.properties.name',\n",
    "        fill_color='YlOrRd',\n",
    "        fill_opacity=0.7,\n",
    "        line_opacity=0.2,\n",
    "        legend_name='Automobile Sales during Recession'\n",
    "    ).add_to(map1)\n",
    "\n",
    "\n",
    "    # Add tooltips to the choropleth layer\n",
    "    choropleth.geojson.add_child(\n",
    "        folium.features.GeoJsonTooltip(['name'], labels=True)\n",
    "    )\n",
    "\n",
    "    # Display the map\n",
    "    map1\n",
    "\n",
    "```\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Congratulations! You have completed the lab\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Dr. Pooja](author_link)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``` toggle ## Change Log\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!---|Date (YYYY-MM-DD)|Version|Changed By|Change Description|\n",
    "|-|-|-|-|\n",
    "2024-01-05|0.2.1|Sowmyaa Gurusamy|Updated the lab instructions|\n",
    "|2023-06-17|0.2|Pooja|Initial Lab Creation|\n",
    "|2023-05-01|0.1|Shengkai|Create Lab Template|-->\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright © 2023 IBM Corporation. All rights reserved.\n"
   ]
  }
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