Bar Chart Tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "859303be",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from matplotlib import style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9dbe2dab",
   "metadata": {},
   "outputs": [],
   "source": [
    "time_data = {'facebook':120, 'youtube':90, 'instagram':40, 'snapchat':28}\n",
    "social_media = list(time_data.keys())\n",
    "time_spend = list(time_data.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e0e5f472",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Average time spend on social media')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "style.use('ggplot')\n",
    "plt.figure(figsize=(5,5))\n",
    "color = ['royalblue', 'red', 'purple', 'yellow']\n",
    "plt.bar(social_media, time_spend, color=color, width=0.5)\n",
    "plt.xlabel('Social Media')\n",
    "plt.ylabel('Time in Minutes')\n",
    "plt.title('Average time spend on social media')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4141ddbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "fb = (120, 90, 110, 100, 95)\n",
    "yt = (80, 90, 75, 85, 95)\n",
    "ig = (50, 40, 55, 35, 45)\n",
    "sc = (20, 30, 35, 25, 28)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16db7e74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xpos = np.arange(len(fb))\n",
    "xpos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a542d4cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17cbb404d60>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "style.use('ggplot')\n",
    "plt.figure(figsize=(10,7))\n",
    "barWidth = 0.2\n",
    "plt.bar(xpos, fb, color='royalblue', width = barWidth, label='FB')\n",
    "plt.bar(xpos+0.2, yt, color='red', width = barWidth, label='YT')\n",
    "plt.bar(xpos+0.4, ig, color='purple', width = barWidth, label='IG')\n",
    "plt.bar(xpos+0.6, sc, color='yellow', width = barWidth, label='SC')\n",
    "plt.xticks(xpos+0.3, ('Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'))\n",
    "plt.xlabel('Day')\n",
    "plt.ylabel('Time spend in minutes')\n",
    "plt.title('Time spend on social media')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d62fa02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17cbb4acd30>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb = (120, 90, 110, 100, 95)\n",
    "yt = (80, 90, 75, 85, 95)\n",
    "ig = (50, 40, 55, 35, 45)\n",
    "x = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']\n",
    "xpos = np.arange(len(x))\n",
    "barWidth = 0.4\n",
    "plt.figure(figsize=(10,7))\n",
    "plt.bar(xpos, fb, color='royalblue', width= barWidth, label='FB')\n",
    "plt.bar(xpos, yt, bottom=fb, color='red', width= barWidth, label='YT')\n",
    "plt.bar(xpos, ig, bottom=yt, color='purple', width= barWidth, label='IG')\n",
    "plt.xlabel('Day')\n",
    "plt.ylabel('Time spend in minutes')\n",
    "plt.title('Time spend on socia media')\n",
    "plt.xticks(xpos, x)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2ca7d23b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir(r'E:\\The AI & DS Channel\\35_Bar chart\\working file\\data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "829f9084",
   "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>Manufacturer</th>\n",
       "      <th>Model</th>\n",
       "      <th>Sales_in_thousands</th>\n",
       "      <th>__year_resale_value</th>\n",
       "      <th>Vehicle_type</th>\n",
       "      <th>Price_in_thousands</th>\n",
       "      <th>Engine_size</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Wheelbase</th>\n",
       "      <th>Width</th>\n",
       "      <th>Length</th>\n",
       "      <th>Curb_weight</th>\n",
       "      <th>Fuel_capacity</th>\n",
       "      <th>Fuel_efficiency</th>\n",
       "      <th>Latest_Launch</th>\n",
       "      <th>Power_perf_factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acura</td>\n",
       "      <td>Integra</td>\n",
       "      <td>16.919</td>\n",
       "      <td>16.360</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>21.50</td>\n",
       "      <td>1.8</td>\n",
       "      <td>140.0</td>\n",
       "      <td>101.2</td>\n",
       "      <td>67.3</td>\n",
       "      <td>172.4</td>\n",
       "      <td>2.639</td>\n",
       "      <td>13.2</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2/2/2012</td>\n",
       "      <td>58.280150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acura</td>\n",
       "      <td>TL</td>\n",
       "      <td>39.384</td>\n",
       "      <td>19.875</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>28.40</td>\n",
       "      <td>3.2</td>\n",
       "      <td>225.0</td>\n",
       "      <td>108.1</td>\n",
       "      <td>70.3</td>\n",
       "      <td>192.9</td>\n",
       "      <td>3.517</td>\n",
       "      <td>17.2</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6/3/2011</td>\n",
       "      <td>91.370778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acura</td>\n",
       "      <td>CL</td>\n",
       "      <td>14.114</td>\n",
       "      <td>18.225</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.2</td>\n",
       "      <td>225.0</td>\n",
       "      <td>106.9</td>\n",
       "      <td>70.6</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3.470</td>\n",
       "      <td>17.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1/4/2012</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acura</td>\n",
       "      <td>RL</td>\n",
       "      <td>8.588</td>\n",
       "      <td>29.725</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>42.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>210.0</td>\n",
       "      <td>114.6</td>\n",
       "      <td>71.4</td>\n",
       "      <td>196.6</td>\n",
       "      <td>3.850</td>\n",
       "      <td>18.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3/10/2011</td>\n",
       "      <td>91.389779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Audi</td>\n",
       "      <td>A4</td>\n",
       "      <td>20.397</td>\n",
       "      <td>22.255</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1.8</td>\n",
       "      <td>150.0</td>\n",
       "      <td>102.6</td>\n",
       "      <td>68.2</td>\n",
       "      <td>178.0</td>\n",
       "      <td>2.998</td>\n",
       "      <td>16.4</td>\n",
       "      <td>27.0</td>\n",
       "      <td>10/8/2011</td>\n",
       "      <td>62.777639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer    Model  Sales_in_thousands  __year_resale_value Vehicle_type  \\\n",
       "0        Acura  Integra              16.919               16.360    Passenger   \n",
       "1        Acura       TL              39.384               19.875    Passenger   \n",
       "2        Acura       CL              14.114               18.225    Passenger   \n",
       "3        Acura       RL               8.588               29.725    Passenger   \n",
       "4         Audi       A4              20.397               22.255    Passenger   \n",
       "\n",
       "   Price_in_thousands  Engine_size  Horsepower  Wheelbase  Width  Length  \\\n",
       "0               21.50          1.8       140.0      101.2   67.3   172.4   \n",
       "1               28.40          3.2       225.0      108.1   70.3   192.9   \n",
       "2                 NaN          3.2       225.0      106.9   70.6   192.0   \n",
       "3               42.00          3.5       210.0      114.6   71.4   196.6   \n",
       "4               23.99          1.8       150.0      102.6   68.2   178.0   \n",
       "\n",
       "   Curb_weight  Fuel_capacity  Fuel_efficiency Latest_Launch  \\\n",
       "0        2.639           13.2             28.0      2/2/2012   \n",
       "1        3.517           17.2             25.0      6/3/2011   \n",
       "2        3.470           17.2             26.0      1/4/2012   \n",
       "3        3.850           18.0             22.0     3/10/2011   \n",
       "4        2.998           16.4             27.0     10/8/2011   \n",
       "\n",
       "   Power_perf_factor  \n",
       "0          58.280150  \n",
       "1          91.370778  \n",
       "2                NaN  \n",
       "3          91.389779  \n",
       "4          62.777639  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_sales = pd.read_csv('Car_sales.csv')\n",
    "car_sales.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f55979f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "manufacturer = car_sales['Manufacturer']\n",
    "sales = car_sales['Sales_in_thousands']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "890a1d4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,10))\n",
    "plt.bar(manufacturer, sales)\n",
    "plt.xlabel('Car Manufacturer')\n",
    "plt.ylabel('Sale in 1000s')\n",
    "plt.title('Car Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bcb59e5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,10))\n",
    "plt.barh(manufacturer, sales, color='purple')\n",
    "plt.xlabel('Car Manufacturer')\n",
    "plt.ylabel('Sale in 1000s')\n",
    "plt.title('Car Sales')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6f658fc2",
   "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>Manufacturer</th>\n",
       "      <th>Model</th>\n",
       "      <th>Sales_in_thousands</th>\n",
       "      <th>__year_resale_value</th>\n",
       "      <th>Vehicle_type</th>\n",
       "      <th>Price_in_thousands</th>\n",
       "      <th>Engine_size</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Wheelbase</th>\n",
       "      <th>Width</th>\n",
       "      <th>Length</th>\n",
       "      <th>Curb_weight</th>\n",
       "      <th>Fuel_capacity</th>\n",
       "      <th>Fuel_efficiency</th>\n",
       "      <th>Latest_Launch</th>\n",
       "      <th>Power_perf_factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Corolla</td>\n",
       "      <td>142.535</td>\n",
       "      <td>10.025</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>13.108</td>\n",
       "      <td>1.8</td>\n",
       "      <td>120.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>174.0</td>\n",
       "      <td>2.420</td>\n",
       "      <td>13.2</td>\n",
       "      <td>33.0</td>\n",
       "      <td>4/11/2011</td>\n",
       "      <td>47.968972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Camry</td>\n",
       "      <td>247.994</td>\n",
       "      <td>13.245</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>17.518</td>\n",
       "      <td>2.2</td>\n",
       "      <td>133.0</td>\n",
       "      <td>105.2</td>\n",
       "      <td>70.1</td>\n",
       "      <td>188.5</td>\n",
       "      <td>2.998</td>\n",
       "      <td>18.5</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2/10/2011</td>\n",
       "      <td>54.372420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Avalon</td>\n",
       "      <td>63.849</td>\n",
       "      <td>18.140</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>25.545</td>\n",
       "      <td>3.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>107.1</td>\n",
       "      <td>71.7</td>\n",
       "      <td>191.9</td>\n",
       "      <td>3.417</td>\n",
       "      <td>18.5</td>\n",
       "      <td>26.0</td>\n",
       "      <td>8/31/2011</td>\n",
       "      <td>84.911898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Celica</td>\n",
       "      <td>33.269</td>\n",
       "      <td>15.445</td>\n",
       "      <td>Passenger</td>\n",
       "      <td>16.875</td>\n",
       "      <td>1.8</td>\n",
       "      <td>140.0</td>\n",
       "      <td>102.4</td>\n",
       "      <td>68.3</td>\n",
       "      <td>170.5</td>\n",
       "      <td>2.425</td>\n",
       "      <td>14.5</td>\n",
       "      <td>31.0</td>\n",
       "      <td>12/29/2012</td>\n",
       "      <td>56.496030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Tacoma</td>\n",
       "      <td>84.087</td>\n",
       "      <td>9.575</td>\n",
       "      <td>Car</td>\n",
       "      <td>11.528</td>\n",
       "      <td>2.4</td>\n",
       "      <td>142.0</td>\n",
       "      <td>103.3</td>\n",
       "      <td>66.5</td>\n",
       "      <td>178.7</td>\n",
       "      <td>2.580</td>\n",
       "      <td>15.1</td>\n",
       "      <td>23.0</td>\n",
       "      <td>8/1/2011</td>\n",
       "      <td>55.297117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Sienna</td>\n",
       "      <td>65.119</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Car</td>\n",
       "      <td>22.368</td>\n",
       "      <td>3.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>114.2</td>\n",
       "      <td>73.4</td>\n",
       "      <td>193.5</td>\n",
       "      <td>3.759</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>10/5/2012</td>\n",
       "      <td>78.027219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>RAV4</td>\n",
       "      <td>25.106</td>\n",
       "      <td>13.325</td>\n",
       "      <td>Car</td>\n",
       "      <td>16.888</td>\n",
       "      <td>2.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>94.9</td>\n",
       "      <td>66.7</td>\n",
       "      <td>163.8</td>\n",
       "      <td>2.668</td>\n",
       "      <td>15.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>5/6/2011</td>\n",
       "      <td>51.955109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>4Runner</td>\n",
       "      <td>68.411</td>\n",
       "      <td>19.425</td>\n",
       "      <td>Car</td>\n",
       "      <td>22.288</td>\n",
       "      <td>2.7</td>\n",
       "      <td>150.0</td>\n",
       "      <td>105.3</td>\n",
       "      <td>66.5</td>\n",
       "      <td>183.3</td>\n",
       "      <td>3.440</td>\n",
       "      <td>18.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3/7/2011</td>\n",
       "      <td>62.355577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Land Cruiser</td>\n",
       "      <td>9.835</td>\n",
       "      <td>34.080</td>\n",
       "      <td>Car</td>\n",
       "      <td>51.728</td>\n",
       "      <td>4.7</td>\n",
       "      <td>230.0</td>\n",
       "      <td>112.2</td>\n",
       "      <td>76.4</td>\n",
       "      <td>192.5</td>\n",
       "      <td>5.115</td>\n",
       "      <td>25.4</td>\n",
       "      <td>15.0</td>\n",
       "      <td>9/25/2011</td>\n",
       "      <td>102.528984</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Manufacturer         Model  Sales_in_thousands  __year_resale_value  \\\n",
       "136       Toyota       Corolla             142.535               10.025   \n",
       "137       Toyota         Camry             247.994               13.245   \n",
       "138       Toyota        Avalon              63.849               18.140   \n",
       "139       Toyota        Celica              33.269               15.445   \n",
       "140       Toyota        Tacoma              84.087                9.575   \n",
       "141       Toyota        Sienna              65.119                  NaN   \n",
       "142       Toyota          RAV4              25.106               13.325   \n",
       "143       Toyota       4Runner              68.411               19.425   \n",
       "144       Toyota  Land Cruiser               9.835               34.080   \n",
       "\n",
       "    Vehicle_type  Price_in_thousands  Engine_size  Horsepower  Wheelbase  \\\n",
       "136    Passenger              13.108          1.8       120.0       97.0   \n",
       "137    Passenger              17.518          2.2       133.0      105.2   \n",
       "138    Passenger              25.545          3.0       210.0      107.1   \n",
       "139    Passenger              16.875          1.8       140.0      102.4   \n",
       "140          Car              11.528          2.4       142.0      103.3   \n",
       "141          Car              22.368          3.0       194.0      114.2   \n",
       "142          Car              16.888          2.0       127.0       94.9   \n",
       "143          Car              22.288          2.7       150.0      105.3   \n",
       "144          Car              51.728          4.7       230.0      112.2   \n",
       "\n",
       "     Width  Length  Curb_weight  Fuel_capacity  Fuel_efficiency Latest_Launch  \\\n",
       "136   66.7   174.0        2.420           13.2             33.0     4/11/2011   \n",
       "137   70.1   188.5        2.998           18.5             27.0     2/10/2011   \n",
       "138   71.7   191.9        3.417           18.5             26.0     8/31/2011   \n",
       "139   68.3   170.5        2.425           14.5             31.0    12/29/2012   \n",
       "140   66.5   178.7        2.580           15.1             23.0      8/1/2011   \n",
       "141   73.4   193.5        3.759           20.9             22.0     10/5/2012   \n",
       "142   66.7   163.8        2.668           15.3             27.0      5/6/2011   \n",
       "143   66.5   183.3        3.440           18.5             23.0      3/7/2011   \n",
       "144   76.4   192.5        5.115           25.4             15.0     9/25/2011   \n",
       "\n",
       "     Power_perf_factor  \n",
       "136          47.968972  \n",
       "137          54.372420  \n",
       "138          84.911898  \n",
       "139          56.496030  \n",
       "140          55.297117  \n",
       "141          78.027219  \n",
       "142          51.955109  \n",
       "143          62.355577  \n",
       "144         102.528984  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toyota_df = car_sales.groupby('Manufacturer').get_group('Toyota')\n",
    "toyota_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7423c544",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = toyota_df['Model']\n",
    "fuel_capacity = toyota_df['Fuel_capacity']\n",
    "fuel_efficiency = toyota_df['Fuel_efficiency']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8adc5f31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,10))\n",
    "plt.barh(model, fuel_capacity, color='blue', height=0.5, label='Fuel Capacity')\n",
    "plt.barh(model, fuel_efficiency, left=fuel_capacity, color='red', height=0.5, label='Fuel Capacity')\n",
    "plt.ylabel('Car Model')\n",
    "plt.xlabel('Fuel Capacity and Fuel Efficiency')\n",
    "plt.title('Fuel capacity & fuel efficiency of various car models')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cece27a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}