Medina_PCA_and_tSNE_Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eT8ztZbiu4Dk"
   },
   "source": [
    "-----------------------------\n",
    "## Objective: \n",
    "-----------------------------\n",
    "The objective of this problem is to explore the data and reduce the number of features by using dimensionality reduction techniques like PCA and TSNE and generate meaningful insights. \n",
    "\n",
    "-----------------------------\n",
    "## Dataset: \n",
    "-----------------------------\n",
    "There are 8 variables in the data: \n",
    "\n",
    "- mpg: miles per gallon\n",
    "- cyl: number of cylinders\n",
    "- disp: engine displacement (cu. inches) or engine size\n",
    "- hp: horsepower\n",
    "- wt: vehicle weight (lbs.)\n",
    "- acc: time taken to accelerate from O to 60 mph (sec.)\n",
    "- yr: model year\n",
    "- car name: car model name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e7YUSFfGu4Du"
   },
   "source": [
    "## Importing necessary libraries and overview of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "aVFeA7eWu4Dv"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#to scale the data using z-score \n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "#importing PCA and TSNE\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "g2bXBiAivujY"
   },
   "source": [
    "#### Loading data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "MuQU1BD-u4Dx"
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"auto-mpg.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "KczGshrVu4Dy",
    "outputId": "f93467ba-526b-4d6c-e0cd-b45a565bcf5d"
   },
   "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>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model year</th>\n",
       "      <th>car name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>buick skylark 320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>plymouth satellite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>amc rebel sst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>ford torino</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cylinders  displacement horsepower  weight  acceleration  model year  \\\n",
       "0  18.0          8         307.0        130    3504          12.0          70   \n",
       "1  15.0          8         350.0        165    3693          11.5          70   \n",
       "2  18.0          8         318.0        150    3436          11.0          70   \n",
       "3  16.0          8         304.0        150    3433          12.0          70   \n",
       "4  17.0          8         302.0        140    3449          10.5          70   \n",
       "\n",
       "                    car name  \n",
       "0  chevrolet chevelle malibu  \n",
       "1          buick skylark 320  \n",
       "2         plymouth satellite  \n",
       "3              amc rebel sst  \n",
       "4                ford torino  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sTXXY0cVvuja"
   },
   "source": [
    "#### Check the info of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "iNuAIXhqvuja",
    "outputId": "9b8f4ee0-1f3c-4cb0-acbe-6ec39b89b859"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 398 entries, 0 to 397\n",
      "Data columns (total 8 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   mpg           398 non-null    float64\n",
      " 1   cylinders     398 non-null    int64  \n",
      " 2   displacement  398 non-null    float64\n",
      " 3   horsepower    398 non-null    object \n",
      " 4   weight        398 non-null    int64  \n",
      " 5   acceleration  398 non-null    float64\n",
      " 6   model year    398 non-null    int64  \n",
      " 7   car name      398 non-null    object \n",
      "dtypes: float64(3), int64(3), object(2)\n",
      "memory usage: 25.0+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yfUl_sjHvujb"
   },
   "source": [
    "**Observations:**\n",
    "\n",
    "- There are 398 observations and 8 columns in the data.\n",
    "- All variables except horsepower and car name are of numeric data type.\n",
    "- The horsepower must be a numeric data type. We will explore this further."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1B_nVTGSvujb"
   },
   "source": [
    "## Data Preprocessing and Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "xwmALVCRvujb",
    "outputId": "7d593b59-02d9-4612-8f44-acac854c64dd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "305"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"car name\"].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HtksWvFgu4Dz"
   },
   "source": [
    "- The column 'car name' is of object data type containing a lot of unique entries and would not add values to our analysis. We can drop this column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "x_gzOWz7u4D0"
   },
   "outputs": [],
   "source": [
    "# dropping car_name\n",
    "data1 = data.copy()\n",
    "data = data.drop(['car name'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5h4vat2Wvujc"
   },
   "source": [
    "#### Checking values in horsepower column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "S7lk2lGQvujc",
    "outputId": "49039370-367d-424a-dd3e-ada47832ce3e"
   },
   "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>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2046</td>\n",
       "      <td>19.0</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>200.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2875</td>\n",
       "      <td>17.0</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>40.9</td>\n",
       "      <td>4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>?</td>\n",
       "      <td>1835</td>\n",
       "      <td>17.3</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>336</th>\n",
       "      <td>23.6</td>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2905</td>\n",
       "      <td>14.3</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>34.5</td>\n",
       "      <td>4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2320</td>\n",
       "      <td>15.8</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>23.0</td>\n",
       "      <td>4</td>\n",
       "      <td>151.0</td>\n",
       "      <td>?</td>\n",
       "      <td>3035</td>\n",
       "      <td>20.5</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mpg  cylinders  displacement horsepower  weight  acceleration  \\\n",
       "32   25.0          4          98.0          ?    2046          19.0   \n",
       "126  21.0          6         200.0          ?    2875          17.0   \n",
       "330  40.9          4          85.0          ?    1835          17.3   \n",
       "336  23.6          4         140.0          ?    2905          14.3   \n",
       "354  34.5          4         100.0          ?    2320          15.8   \n",
       "374  23.0          4         151.0          ?    3035          20.5   \n",
       "\n",
       "     model year  \n",
       "32           71  \n",
       "126          74  \n",
       "330          80  \n",
       "336          80  \n",
       "354          81  \n",
       "374          82  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking if there are values other than digits in the column 'horsepower' \n",
    "hpIsDigit = pd.DataFrame(data.horsepower.str.isdigit())  # if the string is made of digits store True else False\n",
    "\n",
    "# print isDigit = False!\n",
    "data[hpIsDigit['horsepower'] == False]   # from temp take only those rows where hp has false"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z1qqm_S0vujd"
   },
   "source": [
    "**Observations:**\n",
    "- There are 6 observations where horsepower is ?.\n",
    "- We can consider these values as missing values.\n",
    "- Let's impute these missing values and change the data type of horsepower column.\n",
    "- First we need to replace the ? with np.nan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "xWvn0LhBvujd",
    "outputId": "47f8a323-e978-4cf0-d31e-87242594abe8"
   },
   "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>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2046</td>\n",
       "      <td>19.0</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2875</td>\n",
       "      <td>17.0</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>40.9</td>\n",
       "      <td>4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1835</td>\n",
       "      <td>17.3</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>336</th>\n",
       "      <td>23.6</td>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2905</td>\n",
       "      <td>14.3</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>34.5</td>\n",
       "      <td>4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2320</td>\n",
       "      <td>15.8</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>23.0</td>\n",
       "      <td>4</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3035</td>\n",
       "      <td>20.5</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mpg  cylinders  displacement horsepower  weight  acceleration  \\\n",
       "32   25.0          4          98.0        NaN    2046          19.0   \n",
       "126  21.0          6         200.0        NaN    2875          17.0   \n",
       "330  40.9          4          85.0        NaN    1835          17.3   \n",
       "336  23.6          4         140.0        NaN    2905          14.3   \n",
       "354  34.5          4         100.0        NaN    2320          15.8   \n",
       "374  23.0          4         151.0        NaN    3035          20.5   \n",
       "\n",
       "     model year  \n",
       "32           71  \n",
       "126          74  \n",
       "330          80  \n",
       "336          80  \n",
       "354          81  \n",
       "374          82  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Relacing ? with np.nan\n",
    "data = data.replace('?', np.nan)\n",
    "data[hpIsDigit['horsepower'] == False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "w56loeKtvujd"
   },
   "outputs": [],
   "source": [
    "# Imputing the missing values with median value\n",
    "data.horsepower.fillna(data.horsepower.median(), inplace=True)\n",
    "data['horsepower'] = data['horsepower'].astype('float64')  # converting the hp column from object data type to float"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ejfe_eP4vuje"
   },
   "source": [
    "#### Summary Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "bK37aYa5vuje"
   },
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>398.0</td>\n",
       "      <td>23.514573</td>\n",
       "      <td>7.815984</td>\n",
       "      <td>9.0</td>\n",
       "      <td>17.500</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.000</td>\n",
       "      <td>46.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cylinders</th>\n",
       "      <td>398.0</td>\n",
       "      <td>5.454774</td>\n",
       "      <td>1.701004</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.000</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>displacement</th>\n",
       "      <td>398.0</td>\n",
       "      <td>193.425879</td>\n",
       "      <td>104.269838</td>\n",
       "      <td>68.0</td>\n",
       "      <td>104.250</td>\n",
       "      <td>148.5</td>\n",
       "      <td>262.000</td>\n",
       "      <td>455.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horsepower</th>\n",
       "      <td>398.0</td>\n",
       "      <td>104.304020</td>\n",
       "      <td>38.222625</td>\n",
       "      <td>46.0</td>\n",
       "      <td>76.000</td>\n",
       "      <td>93.5</td>\n",
       "      <td>125.000</td>\n",
       "      <td>230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight</th>\n",
       "      <td>398.0</td>\n",
       "      <td>2970.424623</td>\n",
       "      <td>846.841774</td>\n",
       "      <td>1613.0</td>\n",
       "      <td>2223.750</td>\n",
       "      <td>2803.5</td>\n",
       "      <td>3608.000</td>\n",
       "      <td>5140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acceleration</th>\n",
       "      <td>398.0</td>\n",
       "      <td>15.568090</td>\n",
       "      <td>2.757689</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.825</td>\n",
       "      <td>15.5</td>\n",
       "      <td>17.175</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model year</th>\n",
       "      <td>398.0</td>\n",
       "      <td>76.010050</td>\n",
       "      <td>3.697627</td>\n",
       "      <td>70.0</td>\n",
       "      <td>73.000</td>\n",
       "      <td>76.0</td>\n",
       "      <td>79.000</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count         mean         std     min       25%     50%  \\\n",
       "mpg           398.0    23.514573    7.815984     9.0    17.500    23.0   \n",
       "cylinders     398.0     5.454774    1.701004     3.0     4.000     4.0   \n",
       "displacement  398.0   193.425879  104.269838    68.0   104.250   148.5   \n",
       "horsepower    398.0   104.304020   38.222625    46.0    76.000    93.5   \n",
       "weight        398.0  2970.424623  846.841774  1613.0  2223.750  2803.5   \n",
       "acceleration  398.0    15.568090    2.757689     8.0    13.825    15.5   \n",
       "model year    398.0    76.010050    3.697627    70.0    73.000    76.0   \n",
       "\n",
       "                   75%     max  \n",
       "mpg             29.000    46.6  \n",
       "cylinders        8.000     8.0  \n",
       "displacement   262.000   455.0  \n",
       "horsepower     125.000   230.0  \n",
       "weight        3608.000  5140.0  \n",
       "acceleration    17.175    24.8  \n",
       "model year      79.000    82.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Write your code here\n",
    "data.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "q1uzRW5Rxtfy"
   },
   "source": [
    "**Observations:________**\n",
    "- MPG has an mean of 23.5 mph and standard deviation of 7.8 mph\n",
    "- Cylinders has a mean of 5.45 and standard deviation of 1.7 (not a ton of variation)\n",
    "- Horespower (mean of 104, std dev of 38) and displacement (mean of 193.4 and st dev of 104) have a good amount of variation, weight as well.\n",
    "- Model year ranges from 1970 (min) and 1982 (max), with a mean of 1976.\n",
    "- Acceleration has a mean of 15.5 and std dev of 2.75.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kNOc_6aZvujf"
   },
   "source": [
    "#### Let's check the distribution and outliers for each column in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "w21FDMJSvujf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mpg\n",
      "Skew : 0.46\n",
      "Median is 23.0 and Mean is 23.51\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cylinders\n",
      "Skew : 0.53\n",
      "Median is 4.0 and Mean is 5.45\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "displacement\n",
      "Skew : 0.72\n",
      "Median is 148.5 and Mean is 193.43\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "horsepower\n",
      "Skew : 1.11\n",
      "Median is 93.5 and Mean is 104.3\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "weight\n",
      "Skew : 0.53\n",
      "Median is 2803.5 and Mean is 2970.42\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "acceleration\n",
      "Skew : 0.28\n",
      "Median is 15.5 and Mean is 15.57\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model year\n",
      "Skew : 0.01\n",
      "Median is 76.0 and Mean is 76.01\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Uncomment and complete the code by filling the blanks \n",
    "\n",
    "for col in data.columns:\n",
    "    print(col)\n",
    "    print('Skew :',round(data[col].skew(),2))\n",
    "    plt.figure(figsize=(15,4))\n",
    "    plt.subplot(1,2,1)\n",
    "    data[col].hist()\n",
    "    plt.ylabel('count')\n",
    "    plt.subplot(1,2,2)\n",
    "    sns.boxplot(x=data[col])\n",
    "    print(f'Median is {data[col].median()} and Mean is {round(data[col].mean(),2)}')\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ny5YaZhvvujf"
   },
   "source": [
    "**Observations:_____________**\n",
    "\n",
    "\n",
    "- **mpg** - distribution similar to Weibull, with one outlier (> 45). Median = 23.0\n",
    "- **cylinders** - lacks symmetry, largely dominated by cylinder = 4, 6, or 8 (interquartile range (IQR). Median = 4\n",
    "- **displacement** - skewed left IQR between 100 and 250 and median of 150). Median = 148.5, and mean of 193.4\n",
    "- **horsepower** - skewed slightly left, distribution similar to Weibull, several outlier beyond upper whisker. IQR between 75 and 125. Median = 93.5\n",
    "- **weight** - skewed slightly left, distribution similar to Weibull.  Median of 2803.5 and mean of 2970.42\n",
    "- **Acceleration** appears to be normally distribution. This is roughly confirmed by the fact that the median is 15.5 and mean of 15.57 (nearly the same). There are a few outliers below and above the whiskers of the boxplot\n",
    "- **Model year** appear roughly uniformly distributed - with a median of 76 and mean of 76.01\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "d6Vqxb0-u4D4"
   },
   "source": [
    "#### Checking correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "VP3jF_XJvujg",
    "outputId": "888a9007-0881-4fbc-fe60-8d1bdcb21afd"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "sns.heatmap(data.corr(), annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "a71M7-jdvujg"
   },
   "source": [
    "**Observations:**\n",
    "- The variable mpg has strong negative correlation with cylinders, displacement, horsepower, and weight.\n",
    "- horsepower and acceleration are negatively correlated.\n",
    "- The variable weight has strong positively correlation with horsepower, displacement and cylinders\n",
    "- model year is positively correlated with mpg."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WVuQ8rRuvujg"
   },
   "source": [
    "#### Scaling the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "PWPOuZzwu4D5"
   },
   "outputs": [],
   "source": [
    "# scaling the data\n",
    "scaler=StandardScaler()\n",
    "data_scaled=pd.DataFrame(scaler.fit_transform(data), columns=data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "zj6upuANvujh",
    "outputId": "f2ebdab6-9906-46fb-8782-55eb129965e1"
   },
   "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>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.498191</td>\n",
       "      <td>1.090604</td>\n",
       "      <td>0.673118</td>\n",
       "      <td>0.630870</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>-1.627426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.090751</td>\n",
       "      <td>1.498191</td>\n",
       "      <td>1.503514</td>\n",
       "      <td>1.589958</td>\n",
       "      <td>0.854333</td>\n",
       "      <td>-1.477038</td>\n",
       "      <td>-1.627426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.498191</td>\n",
       "      <td>1.196232</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.550470</td>\n",
       "      <td>-1.658577</td>\n",
       "      <td>-1.627426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.962647</td>\n",
       "      <td>1.498191</td>\n",
       "      <td>1.061796</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.546923</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>-1.627426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.834543</td>\n",
       "      <td>1.498191</td>\n",
       "      <td>1.042591</td>\n",
       "      <td>0.935072</td>\n",
       "      <td>0.565841</td>\n",
       "      <td>-1.840117</td>\n",
       "      <td>-1.627426</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        mpg  cylinders  displacement  horsepower    weight  acceleration  \\\n",
       "0 -0.706439   1.498191      1.090604    0.673118  0.630870     -1.295498   \n",
       "1 -1.090751   1.498191      1.503514    1.589958  0.854333     -1.477038   \n",
       "2 -0.706439   1.498191      1.196232    1.197027  0.550470     -1.658577   \n",
       "3 -0.962647   1.498191      1.061796    1.197027  0.546923     -1.295498   \n",
       "4 -0.834543   1.498191      1.042591    0.935072  0.565841     -1.840117   \n",
       "\n",
       "   model year  \n",
       "0   -1.627426  \n",
       "1   -1.627426  \n",
       "2   -1.627426  \n",
       "3   -1.627426  \n",
       "4   -1.627426  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_scaled.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eIAZ2xZuvujh"
   },
   "source": [
    "## Principal Component Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "id": "SqS_ahV0vuji"
   },
   "outputs": [],
   "source": [
    "#Defining the number of principal components to generate \n",
    "n=data_scaled.shape[1]\n",
    "\n",
    "#Finding principal components for the data\n",
    "pca = PCA(n_components=n, random_state=1)\n",
    "data_pca1 = pd.DataFrame(pca.fit_transform(data_scaled))\n",
    "\n",
    "#The percentage of variance explained by each principal component\n",
    "exp_var = pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "id": "1OiDLM52vuji",
    "outputId": "a19b17aa-644e-457f-ce5b-df84a4c792ae"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Cumulative Explained Variance')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the explained variance by individual components\n",
    "plt.figure(figsize = (10,10))\n",
    "plt.plot(range(1,8), exp_var.cumsum(), marker = 'o', linestyle = '--')\n",
    "plt.title(\"Explained Variances by Components\")\n",
    "plt.xlabel(\"Number of Components\")\n",
    "plt.ylabel(\"Cumulative Explained Variance\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "id": "qclnWlJ9vujj",
    "outputId": "d0a90e0f-be3d-4cd0-ca40-5e506efb09d3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of PCs that explain at least 90% variance:  3\n"
     ]
    }
   ],
   "source": [
    "# find the least number of components that can explain more than 90% variance\n",
    "sum = 0\n",
    "for ix, i in enumerate(exp_var):\n",
    "  sum = sum + i\n",
    "  if(sum>0.90):\n",
    "    print(\"Number of PCs that explain at least 90% variance: \", ix+1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-P3Hl-3Pvujj"
   },
   "source": [
    "**Observations:___________________**\n",
    "\n",
    "-  We can see that out of the 7 original features, we can reduced the number of features through principal components to 3 (elbow of chart), these components explain approximately 95% of the original variance.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "id": "_G_-CsZJvujj",
    "outputId": "bcdbe123-e1f6-470b-ded9-91d18eeaf1a1"
   },
   "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>PC1</th>\n",
       "      <th>PC2</th>\n",
       "      <th>PC3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>-0.40</td>\n",
       "      <td>-0.21</td>\n",
       "      <td>-0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cylinders</th>\n",
       "      <td>0.42</td>\n",
       "      <td>-0.19</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>displacement</th>\n",
       "      <td>0.43</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horsepower</th>\n",
       "      <td>0.42</td>\n",
       "      <td>-0.09</td>\n",
       "      <td>-0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight</th>\n",
       "      <td>0.41</td>\n",
       "      <td>-0.22</td>\n",
       "      <td>0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acceleration</th>\n",
       "      <td>-0.28</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model year</th>\n",
       "      <td>-0.23</td>\n",
       "      <td>-0.91</td>\n",
       "      <td>-0.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               PC1   PC2   PC3\n",
       "mpg          -0.40 -0.21 -0.26\n",
       "cylinders     0.42 -0.19  0.14\n",
       "displacement  0.43 -0.18  0.10\n",
       "horsepower    0.42 -0.09 -0.17\n",
       "weight        0.41 -0.22  0.28\n",
       "acceleration -0.28  0.02  0.89\n",
       "model year   -0.23 -0.91 -0.02"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pc_comps = ['PC1','PC2','PC3']\n",
    "data_pca = pd.DataFrame(np.round(pca.components_[:3,:],2),index=pc_comps,columns=data_scaled.columns)\n",
    "data_pca.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "id": "mi16_6Bxvujk",
    "outputId": "5a1d6297-5d23-4588-d369-64a694b72b18"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "#T_fe53f_row0_col0,#T_fe53f_row6_col1{\n",
       "            background:  pink;\n",
       "        }#T_fe53f_row1_col0,#T_fe53f_row2_col0,#T_fe53f_row3_col0,#T_fe53f_row4_col0,#T_fe53f_row5_col2{\n",
       "            background:  skyblue;\n",
       "        }</style><table id=\"T_fe53f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >PC1</th>        <th class=\"col_heading level0 col1\" >PC2</th>        <th class=\"col_heading level0 col2\" >PC3</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_fe53f_level0_row0\" class=\"row_heading level0 row0\" >mpg</th>\n",
       "                        <td id=\"T_fe53f_row0_col0\" class=\"data row0 col0\" >-0.400000</td>\n",
       "                        <td id=\"T_fe53f_row0_col1\" class=\"data row0 col1\" >-0.210000</td>\n",
       "                        <td id=\"T_fe53f_row0_col2\" class=\"data row0 col2\" >-0.260000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row1\" class=\"row_heading level0 row1\" >cylinders</th>\n",
       "                        <td id=\"T_fe53f_row1_col0\" class=\"data row1 col0\" >0.420000</td>\n",
       "                        <td id=\"T_fe53f_row1_col1\" class=\"data row1 col1\" >-0.190000</td>\n",
       "                        <td id=\"T_fe53f_row1_col2\" class=\"data row1 col2\" >0.140000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row2\" class=\"row_heading level0 row2\" >displacement</th>\n",
       "                        <td id=\"T_fe53f_row2_col0\" class=\"data row2 col0\" >0.430000</td>\n",
       "                        <td id=\"T_fe53f_row2_col1\" class=\"data row2 col1\" >-0.180000</td>\n",
       "                        <td id=\"T_fe53f_row2_col2\" class=\"data row2 col2\" >0.100000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row3\" class=\"row_heading level0 row3\" >horsepower</th>\n",
       "                        <td id=\"T_fe53f_row3_col0\" class=\"data row3 col0\" >0.420000</td>\n",
       "                        <td id=\"T_fe53f_row3_col1\" class=\"data row3 col1\" >-0.090000</td>\n",
       "                        <td id=\"T_fe53f_row3_col2\" class=\"data row3 col2\" >-0.170000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row4\" class=\"row_heading level0 row4\" >weight</th>\n",
       "                        <td id=\"T_fe53f_row4_col0\" class=\"data row4 col0\" >0.410000</td>\n",
       "                        <td id=\"T_fe53f_row4_col1\" class=\"data row4 col1\" >-0.220000</td>\n",
       "                        <td id=\"T_fe53f_row4_col2\" class=\"data row4 col2\" >0.280000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row5\" class=\"row_heading level0 row5\" >acceleration</th>\n",
       "                        <td id=\"T_fe53f_row5_col0\" class=\"data row5 col0\" >-0.280000</td>\n",
       "                        <td id=\"T_fe53f_row5_col1\" class=\"data row5 col1\" >0.020000</td>\n",
       "                        <td id=\"T_fe53f_row5_col2\" class=\"data row5 col2\" >0.890000</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_fe53f_level0_row6\" class=\"row_heading level0 row6\" >model year</th>\n",
       "                        <td id=\"T_fe53f_row6_col0\" class=\"data row6 col0\" >-0.230000</td>\n",
       "                        <td id=\"T_fe53f_row6_col1\" class=\"data row6 col1\" >-0.910000</td>\n",
       "                        <td id=\"T_fe53f_row6_col2\" class=\"data row6 col2\" >-0.020000</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fbb20caa340>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def color_high(val):\n",
    "    if val <= -0.40: # you can decide any value as per your understanding\n",
    "        return 'background: pink'\n",
    "    elif val >= 0.40:\n",
    "        return 'background: skyblue'   \n",
    "    \n",
    "data_pca.T.style.applymap(color_high)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oG5orJKGvujk"
   },
   "source": [
    "**Observations:__________________**\n",
    "\n",
    "- The first princicipal component, PC1, is related the higher values of cylinders, displacement, horsepower, and weight, which are negatively correlated to mpg. This component seems to capture the design/make up of the car\n",
    "- The second principal component, PC2, is highly negatively correlated to model_year (.91) and seems to capture the technology/advancement component of model year\n",
    "- THe third principal component, PC3, is highly positively correlated to acceleration, and seems to capture the impact of acceleration \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jZo1h9pNvujk"
   },
   "source": [
    "#### We can also visualize the data in 2 dimensions using first two principal components "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "id": "7iWxTqHfvujl",
    "outputId": "c19271e0-592d-4875-896c-5b476f22bf20"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (7,7))\n",
    "sns.scatterplot(x=data_pca1[0],y=data_pca1[1])\n",
    "plt.xlabel(\"PC1\")\n",
    "plt.ylabel(\"PC2\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eH9VeKRBvujl"
   },
   "source": [
    "**Let's try adding hue to the scatter plot**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "id": "VrB1kzKpvujl"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_concat = pd.concat([data_pca1, data], axis=1)\n",
    "\n",
    "plt.figure(figsize = (7,7))\n",
    "#Create a scatter plot with x=0 and y=1 using df_concat dataframe\n",
    "sns.scatterplot(x = 0, y=1, hue='cylinders', data = df_concat)\n",
    "plt.xlabel(\"PC1\")\n",
    "plt.ylabel(\"PC2\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v1i8nQCevujl"
   },
   "source": [
    "**Observations:___________**\n",
    "\n",
    "- It appears that the most defined clusters are with cylinders 8, and clynders 6. The efficiency of these configurations seem to be markedly different than cylinders 3 and 4. Since PC1 is inversly related to MPG, these appears to confirm that the higher the cylinders, the worst the MPG. \n",
    "- Note that PC2 was primarily related to model year - but the pattern seems to be more influenced by cylinder than by model year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4TY5Sh719iVg"
   },
   "source": [
    "## t-SNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "id": "dW1jMGn7u4D7"
   },
   "outputs": [],
   "source": [
    "tsne = TSNE(n_components = 2, random_state=1)  #Apply the TSNE algorithm with random state = 1\n",
    "data_tsne = tsne.fit_transform(data_scaled) #Fit and transform tsne function on the scaled data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "id": "gC17thkgu4D7",
    "outputId": "bcfb2a47-d252-40e7-bfad-b7959472ed4e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(398, 2)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_tsne.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "id": "Gfybekuyu4D8"
   },
   "outputs": [],
   "source": [
    "data_tsne = pd.DataFrame(data = data_tsne, columns = ['Component 1', 'Component 2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "id": "oNoqqDg5u4D8",
    "outputId": "18f48a19-17fe-4e23-80d9-3877d752ee9b"
   },
   "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>Component 1</th>\n",
       "      <th>Component 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-38.088413</td>\n",
       "      <td>-15.912958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-37.404369</td>\n",
       "      <td>-17.995850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-38.050472</td>\n",
       "      <td>-17.063194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-37.718334</td>\n",
       "      <td>-16.476006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-38.404663</td>\n",
       "      <td>-16.763493</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Component 1  Component 2\n",
       "0   -38.088413   -15.912958\n",
       "1   -37.404369   -17.995850\n",
       "2   -38.050472   -17.063194\n",
       "3   -37.718334   -16.476006\n",
       "4   -38.404663   -16.763493"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_tsne.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "id": "Ix_OL7AIu4D9",
    "outputId": "3fee5301-ea4f-41d5-fc37-79ec5d61f877"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=data_tsne.iloc[:,0],y=data_tsne.iloc[:,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "id": "WW3GQboou4D9",
    "outputId": "72fec8c5-1ea3-4418-be0a-dbad1788bf78"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's see scatter plot of the data w.r.t number of cylinders\n",
    "sns.scatterplot(x=data_tsne.iloc[:,0],y=data_tsne.iloc[:,1],hue=data.cylinders)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PEfKLZkou4D-"
   },
   "source": [
    "**Observations:______________**\n",
    "\n",
    "- In the first scatter plot, we can see some clear clusters are formed, but we are unable to dintinguish what may be driving these - only that in the lower left cluster - entries are associated with highly negative component 1 and component 2, and slightly less in the second cluster and third.\n",
    "\n",
    "- In the second scatterplot, once we shade based on number of cylinders, we quickly see that clusters are largely characterized by cylinders and their negative impact on MPG ( with 8 being the least efficient), 6 and 5 cylinders being the next least efficient, and 4 and 3 being most efficient\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "id": "aLTJSNBvu4D_"
   },
   "outputs": [],
   "source": [
    "# Let's assign points to 3 different groups\n",
    "def grouping(x):\n",
    "    first_component = x['Component 1']\n",
    "    second_component = x['Component 2']\n",
    "    if (first_component> 0) and (second_component >0): \n",
    "        return 'group_1'\n",
    "    if (first_component >-20 ) and (first_component < 5):\n",
    "        return 'group_2'\n",
    "    else: \n",
    "        return 'group_3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "id": "R6rWEgPPu4EA"
   },
   "outputs": [],
   "source": [
    "data_tsne['groups'] = data_tsne.apply(grouping,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "id": "RX-r_I0-u4EA",
    "outputId": "ca9011cf-b67e-4376-be11-4692ebfe1326"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=data_tsne.iloc[:,0],y=data_tsne.iloc[:,1],hue=data_tsne.iloc[:,2])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "id": "hHh5_G9iu4EB"
   },
   "outputs": [],
   "source": [
    "data['groups'] = data_tsne['groups'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "id": "TycHswKhu4EB",
    "outputId": "0aa3d1f1-5f73-4cbc-b603-1aac27b3a874"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_col = data.columns.tolist()\n",
    "plt.figure(figsize=(20, 20))\n",
    "\n",
    "for i, variable in enumerate(all_col):\n",
    "    if i==7:\n",
    "        break\n",
    "    plt.subplot(4, 2, i + 1)\n",
    "    #Create boxplot with groups on the x-axis and variable on the y-axis (use the dataframe data)\n",
    "    sns.boxplot(x='groups', y=variable, data=data)\n",
    "    plt.tight_layout()\n",
    "    plt.title(variable)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "37KSsbmSu4EC"
   },
   "source": [
    "**Observations:___________**\n",
    "\n",
    ">  **group 1**\n",
    ">  - has the best MPG, and have some of the newest model_years\n",
    ">  - lowest displacement, weight, and horsepower , cylinder count\n",
    "\n",
    "> **group 3**\n",
    ">  - has the worst MPG, and the oldest range of model_years\n",
    ">  - highest displacement, weight, and horsepower, cylinder count\n",
    "\n",
    "> **group 2** \n",
    "> - is essentially the middle of the road group fitting somewhere in between group 1 and 3 in most measures."
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Learner_Notebook_PCA_and_tSNE_Project.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}