Assigment_1_kush_kumar.ipynb

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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Assigment-1_kush_kumar.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iuO1ciKO8-DM",
        "colab_type": "text"
      },
      "source": [
        "# Assignement- 1  code by **Kush Kumar**\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fX4au-C686Z6",
        "colab_type": "text"
      },
      "source": [
        "## Import Essential Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vEAcI7_t4wno",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8JAxhAYcbwQb",
        "colab_type": "text"
      },
      "source": [
        "Read CSV File"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qjs1XvQU5DNZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "574a42a6-a699-4374-89db-924690e95405"
      },
      "source": [
        "df_brand_details = pd.read_csv('brand_details.csv',sep='\\t')\n",
        "pd.set_option('display.max_rows',df_brand_details.shape[0]+1)\n",
        "# df_brand_details.head()\n",
        "df_brand_details"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Rank</th>\n",
              "      <th>Brand</th>\n",
              "      <th>Brand_Value</th>\n",
              "      <th>Change_LastYr</th>\n",
              "      <th>Brand_Revenue</th>\n",
              "      <th>Company_Advertising</th>\n",
              "      <th>Industry</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Apple</td>\n",
              "      <td>145.3</td>\n",
              "      <td>17</td>\n",
              "      <td>182.3</td>\n",
              "      <td>1.200</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Microsoft</td>\n",
              "      <td>69.3</td>\n",
              "      <td>10</td>\n",
              "      <td>93.3</td>\n",
              "      <td>2.300</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Google</td>\n",
              "      <td>65.6</td>\n",
              "      <td>16</td>\n",
              "      <td>61.8</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Coca-Cola</td>\n",
              "      <td>56.0</td>\n",
              "      <td>0</td>\n",
              "      <td>23.1</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Beverages</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>IBM</td>\n",
              "      <td>49.8</td>\n",
              "      <td>4</td>\n",
              "      <td>92.8</td>\n",
              "      <td>1.300</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>McDonalds</td>\n",
              "      <td>39.5</td>\n",
              "      <td>-1</td>\n",
              "      <td>87.8</td>\n",
              "      <td>0.808</td>\n",
              "      <td>Restaurants</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>Samsung</td>\n",
              "      <td>37.9</td>\n",
              "      <td>8</td>\n",
              "      <td>187.8</td>\n",
              "      <td>3.800</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>Toyota</td>\n",
              "      <td>37.8</td>\n",
              "      <td>21</td>\n",
              "      <td>171.1</td>\n",
              "      <td>3.800</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>10</td>\n",
              "      <td>Facebook</td>\n",
              "      <td>36.5</td>\n",
              "      <td>54</td>\n",
              "      <td>12.1</td>\n",
              "      <td>0.135</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>11</td>\n",
              "      <td>Disney</td>\n",
              "      <td>34.6</td>\n",
              "      <td>26</td>\n",
              "      <td>26.4</td>\n",
              "      <td>2.800</td>\n",
              "      <td>Leisure</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>12</td>\n",
              "      <td>AT&amp;T</td>\n",
              "      <td>29.1</td>\n",
              "      <td>17</td>\n",
              "      <td>132.4</td>\n",
              "      <td>3.300</td>\n",
              "      <td>Telecom</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>13</td>\n",
              "      <td>Amazon</td>\n",
              "      <td>28.1</td>\n",
              "      <td>32</td>\n",
              "      <td>87.5</td>\n",
              "      <td>3.300</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>14</td>\n",
              "      <td>Louis Vuitton</td>\n",
              "      <td>28.1</td>\n",
              "      <td>-6</td>\n",
              "      <td>10.1</td>\n",
              "      <td>4.600</td>\n",
              "      <td>Luxury</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>15</td>\n",
              "      <td>Cisco</td>\n",
              "      <td>27.6</td>\n",
              "      <td>-2</td>\n",
              "      <td>48.1</td>\n",
              "      <td>0.196</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>17</td>\n",
              "      <td>Oracle</td>\n",
              "      <td>26.8</td>\n",
              "      <td>4</td>\n",
              "      <td>38.8</td>\n",
              "      <td>0.079</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>18</td>\n",
              "      <td>NIKE</td>\n",
              "      <td>26.3</td>\n",
              "      <td>19</td>\n",
              "      <td>28.3</td>\n",
              "      <td>3.000</td>\n",
              "      <td>Apparel</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>19</td>\n",
              "      <td>Intel</td>\n",
              "      <td>25.8</td>\n",
              "      <td>-8</td>\n",
              "      <td>55.9</td>\n",
              "      <td>1.800</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>20</td>\n",
              "      <td>Wal-Mart</td>\n",
              "      <td>24.7</td>\n",
              "      <td>6</td>\n",
              "      <td>313.0</td>\n",
              "      <td>2.400</td>\n",
              "      <td>Retail</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>21</td>\n",
              "      <td>Verizon</td>\n",
              "      <td>24.5</td>\n",
              "      <td>14</td>\n",
              "      <td>127.1</td>\n",
              "      <td>2.500</td>\n",
              "      <td>Telecom</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>22</td>\n",
              "      <td>American Express</td>\n",
              "      <td>23.4</td>\n",
              "      <td>13</td>\n",
              "      <td>36.0</td>\n",
              "      <td>3.300</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>23</td>\n",
              "      <td>Honda</td>\n",
              "      <td>22.6</td>\n",
              "      <td>-3</td>\n",
              "      <td>101.3</td>\n",
              "      <td>2.700</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>26</td>\n",
              "      <td>Gillette</td>\n",
              "      <td>20.4</td>\n",
              "      <td>7</td>\n",
              "      <td>7.9</td>\n",
              "      <td>9.200</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>29</td>\n",
              "      <td>Pepsi</td>\n",
              "      <td>19.0</td>\n",
              "      <td>0</td>\n",
              "      <td>12.6</td>\n",
              "      <td>2.300</td>\n",
              "      <td>Beverages</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>30</td>\n",
              "      <td>Visa</td>\n",
              "      <td>18.8</td>\n",
              "      <td>17</td>\n",
              "      <td>12.7</td>\n",
              "      <td>0.900</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>32</td>\n",
              "      <td>ESPN</td>\n",
              "      <td>16.2</td>\n",
              "      <td>10</td>\n",
              "      <td>10.9</td>\n",
              "      <td>2.800</td>\n",
              "      <td>Media</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>35</td>\n",
              "      <td>Hewlett-Packard</td>\n",
              "      <td>14.7</td>\n",
              "      <td>3</td>\n",
              "      <td>111.5</td>\n",
              "      <td>0.784</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>37</td>\n",
              "      <td>Home Depot</td>\n",
              "      <td>13.0</td>\n",
              "      <td>10</td>\n",
              "      <td>83.2</td>\n",
              "      <td>2.300</td>\n",
              "      <td>Retail</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>38</td>\n",
              "      <td>Frito-Lay</td>\n",
              "      <td>13.1</td>\n",
              "      <td>8</td>\n",
              "      <td>11.7</td>\n",
              "      <td>0.884</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>41</td>\n",
              "      <td>Ford</td>\n",
              "      <td>12.5</td>\n",
              "      <td>13</td>\n",
              "      <td>139.3</td>\n",
              "      <td>4.300</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>44</td>\n",
              "      <td>Accenture</td>\n",
              "      <td>12.0</td>\n",
              "      <td>14</td>\n",
              "      <td>32.8</td>\n",
              "      <td>0.088</td>\n",
              "      <td>Business Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>47</td>\n",
              "      <td>Wells Fargo</td>\n",
              "      <td>11.4</td>\n",
              "      <td>13</td>\n",
              "      <td>88.4</td>\n",
              "      <td>0.653</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>48</td>\n",
              "      <td>Fox</td>\n",
              "      <td>11.3</td>\n",
              "      <td>5</td>\n",
              "      <td>13.3</td>\n",
              "      <td>2.900</td>\n",
              "      <td>Media</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>49</td>\n",
              "      <td>Pampers</td>\n",
              "      <td>11.1</td>\n",
              "      <td>8</td>\n",
              "      <td>10.7</td>\n",
              "      <td>9.200</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>50</td>\n",
              "      <td>Ebay</td>\n",
              "      <td>11.0</td>\n",
              "      <td>21</td>\n",
              "      <td>7.6</td>\n",
              "      <td>1.300</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>51</td>\n",
              "      <td>Hermès</td>\n",
              "      <td>10.6</td>\n",
              "      <td>-2</td>\n",
              "      <td>5.3</td>\n",
              "      <td>0.269</td>\n",
              "      <td>Luxury</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>52</td>\n",
              "      <td>Starbucks</td>\n",
              "      <td>10.5</td>\n",
              "      <td>21</td>\n",
              "      <td>16.0</td>\n",
              "      <td>0.199</td>\n",
              "      <td>Restaurants</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>53</td>\n",
              "      <td>MasterCard</td>\n",
              "      <td>10.4</td>\n",
              "      <td>19</td>\n",
              "      <td>9.5</td>\n",
              "      <td>0.862</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>56</td>\n",
              "      <td>J P Morgan</td>\n",
              "      <td>9.5</td>\n",
              "      <td>2</td>\n",
              "      <td>46.7</td>\n",
              "      <td>2.600</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>59</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>9.3</td>\n",
              "      <td>12</td>\n",
              "      <td>6.9</td>\n",
              "      <td>1.100</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>60</td>\n",
              "      <td>Kraft</td>\n",
              "      <td>9.2</td>\n",
              "      <td>4</td>\n",
              "      <td>7.1</td>\n",
              "      <td>0.652</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>61</td>\n",
              "      <td>Colgate</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.800</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>62</td>\n",
              "      <td>Chevrolet</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4</td>\n",
              "      <td>77.7</td>\n",
              "      <td>5.200</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>63</td>\n",
              "      <td>Coach</td>\n",
              "      <td>8.6</td>\n",
              "      <td>-3</td>\n",
              "      <td>4.5</td>\n",
              "      <td>0.130</td>\n",
              "      <td>Luxury</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>64</td>\n",
              "      <td>Hyundai</td>\n",
              "      <td>8.4</td>\n",
              "      <td>7</td>\n",
              "      <td>52.8</td>\n",
              "      <td>1.900</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>69</td>\n",
              "      <td>Santander</td>\n",
              "      <td>7.6</td>\n",
              "      <td>12</td>\n",
              "      <td>52.6</td>\n",
              "      <td>0.834</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>70</td>\n",
              "      <td>John Deere</td>\n",
              "      <td>7.6</td>\n",
              "      <td>6</td>\n",
              "      <td>36.1</td>\n",
              "      <td>0.174</td>\n",
              "      <td>Heavy Equipment</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>71</td>\n",
              "      <td>Chase</td>\n",
              "      <td>7.4</td>\n",
              "      <td>14</td>\n",
              "      <td>51.3</td>\n",
              "      <td>2.600</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>72</td>\n",
              "      <td>Bank of America</td>\n",
              "      <td>7.3</td>\n",
              "      <td>-1</td>\n",
              "      <td>76.8</td>\n",
              "      <td>1.800</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>74</td>\n",
              "      <td>Prada</td>\n",
              "      <td>7.3</td>\n",
              "      <td>-9</td>\n",
              "      <td>3.7</td>\n",
              "      <td>0.218</td>\n",
              "      <td>Luxury</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>75</td>\n",
              "      <td>Nissan</td>\n",
              "      <td>7.3</td>\n",
              "      <td>-10</td>\n",
              "      <td>96.6</td>\n",
              "      <td>2.600</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>79</td>\n",
              "      <td>Sony</td>\n",
              "      <td>6.9</td>\n",
              "      <td>21</td>\n",
              "      <td>63.6</td>\n",
              "      <td>3.200</td>\n",
              "      <td>Technology</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>80</td>\n",
              "      <td>FedEx</td>\n",
              "      <td>6.9</td>\n",
              "      <td>5</td>\n",
              "      <td>47.2</td>\n",
              "      <td>0.407</td>\n",
              "      <td>Transportation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>81</td>\n",
              "      <td>Citi</td>\n",
              "      <td>6.9</td>\n",
              "      <td>16</td>\n",
              "      <td>90.6</td>\n",
              "      <td>1.800</td>\n",
              "      <td>Financial Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>89</td>\n",
              "      <td>Ralph Lauren</td>\n",
              "      <td>6.6</td>\n",
              "      <td>-1</td>\n",
              "      <td>7.1</td>\n",
              "      <td>0.256</td>\n",
              "      <td>Apparel</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>92</td>\n",
              "      <td>Target</td>\n",
              "      <td>6.4</td>\n",
              "      <td>13</td>\n",
              "      <td>72.6</td>\n",
              "      <td>1.600</td>\n",
              "      <td>Retail</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>94</td>\n",
              "      <td>Hershey</td>\n",
              "      <td>6.3</td>\n",
              "      <td>10</td>\n",
              "      <td>4.6</td>\n",
              "      <td>0.570</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>97</td>\n",
              "      <td>KIA Motors</td>\n",
              "      <td>6.2</td>\n",
              "      <td>-11</td>\n",
              "      <td>42.9</td>\n",
              "      <td>0.992</td>\n",
              "      <td>Automotive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>98</td>\n",
              "      <td>Sprite</td>\n",
              "      <td>6.2</td>\n",
              "      <td>2</td>\n",
              "      <td>3.7</td>\n",
              "      <td>3.500</td>\n",
              "      <td>Beverages</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>99</td>\n",
              "      <td>MTV</td>\n",
              "      <td>6.2</td>\n",
              "      <td>6</td>\n",
              "      <td>3.4</td>\n",
              "      <td>1.000</td>\n",
              "      <td>Media</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>100</td>\n",
              "      <td>Estee Lauder</td>\n",
              "      <td>6.1</td>\n",
              "      <td>4</td>\n",
              "      <td>4.5</td>\n",
              "      <td>2.800</td>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Rank             Brand  ...  Company_Advertising                 Industry\n",
              "0      1             Apple  ...                1.200               Technology\n",
              "1      2         Microsoft  ...                2.300               Technology\n",
              "2      3            Google  ...                3.000               Technology\n",
              "3      4         Coca-Cola  ...                3.500                Beverages\n",
              "4      5               IBM  ...                1.300               Technology\n",
              "5      6         McDonalds  ...                0.808              Restaurants\n",
              "6      7           Samsung  ...                3.800               Technology\n",
              "7      8            Toyota  ...                3.800               Automotive\n",
              "8     10          Facebook  ...                0.135               Technology\n",
              "9     11            Disney  ...                2.800                  Leisure\n",
              "10    12              AT&T  ...                3.300                  Telecom\n",
              "11    13            Amazon  ...                3.300               Technology\n",
              "12    14     Louis Vuitton  ...                4.600                   Luxury\n",
              "13    15             Cisco  ...                0.196               Technology\n",
              "14    17            Oracle  ...                0.079               Technology\n",
              "15    18              NIKE  ...                3.000                  Apparel\n",
              "16    19             Intel  ...                1.800               Technology\n",
              "17    20          Wal-Mart  ...                2.400                   Retail\n",
              "18    21           Verizon  ...                2.500                  Telecom\n",
              "19    22  American Express  ...                3.300       Financial Services\n",
              "20    23             Honda  ...                2.700               Automotive\n",
              "21    26          Gillette  ...                9.200  Consumer Packaged Goods\n",
              "22    29             Pepsi  ...                2.300                Beverages\n",
              "23    30              Visa  ...                0.900       Financial Services\n",
              "24    32              ESPN  ...                2.800                    Media\n",
              "25    35   Hewlett-Packard  ...                0.784               Technology\n",
              "26    37        Home Depot  ...                2.300                   Retail\n",
              "27    38         Frito-Lay  ...                0.884  Consumer Packaged Goods\n",
              "28    41              Ford  ...                4.300               Automotive\n",
              "29    44         Accenture  ...                0.088        Business Services\n",
              "30    47       Wells Fargo  ...                0.653       Financial Services\n",
              "31    48               Fox  ...                2.900                    Media\n",
              "32    49           Pampers  ...                9.200  Consumer Packaged Goods\n",
              "33    50              Ebay  ...                1.300               Technology\n",
              "34    51            Hermès  ...                0.269                   Luxury\n",
              "35    52         Starbucks  ...                0.199              Restaurants\n",
              "36    53        MasterCard  ...                0.862       Financial Services\n",
              "37    56        J P Morgan  ...                2.600       Financial Services\n",
              "38    59          Kelloggs  ...                1.100  Consumer Packaged Goods\n",
              "39    60             Kraft  ...                0.652  Consumer Packaged Goods\n",
              "40    61           Colgate  ...                1.800  Consumer Packaged Goods\n",
              "41    62         Chevrolet  ...                5.200               Automotive\n",
              "42    63             Coach  ...                0.130                   Luxury\n",
              "43    64           Hyundai  ...                1.900               Automotive\n",
              "44    69         Santander  ...                0.834       Financial Services\n",
              "45    70        John Deere  ...                0.174          Heavy Equipment\n",
              "46    71             Chase  ...                2.600       Financial Services\n",
              "47    72   Bank of America  ...                1.800       Financial Services\n",
              "48    74             Prada  ...                0.218                   Luxury\n",
              "49    75            Nissan  ...                2.600               Automotive\n",
              "50    79              Sony  ...                3.200               Technology\n",
              "51    80             FedEx  ...                0.407           Transportation\n",
              "52    81              Citi  ...                1.800       Financial Services\n",
              "53    89      Ralph Lauren  ...                0.256                  Apparel\n",
              "54    92            Target  ...                1.600                   Retail\n",
              "55    94           Hershey  ...                0.570  Consumer Packaged Goods\n",
              "56    97        KIA Motors  ...                0.992               Automotive\n",
              "57    98            Sprite  ...                3.500                Beverages\n",
              "58    99               MTV  ...                1.000                    Media\n",
              "59   100      Estee Lauder  ...                2.800  Consumer Packaged Goods\n",
              "\n",
              "[60 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gyqMbBJ--zXt",
        "colab_type": "text"
      },
      "source": [
        "# Problem statement"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3FSrq0Iu_BUw",
        "colab_type": "text"
      },
      "source": [
        "Problem 1 - Which industry has the maximum brands whose Brand_Revenue > 80 Million (Brand revenue is in millions)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uXbmXhmT_H6x",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 229
        },
        "outputId": "29d2671b-2dbc-412a-8ac7-3dbd957c51a6"
      },
      "source": [
        "indus=df_brand_details[df_brand_details[\"Brand_Revenue\"]>float(80)].groupby(['Industry'], as_index = False)['Brand'].count()\n",
        "indus"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Industry</th>\n",
              "      <th>Brand</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Automotive</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Restaurants</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Retail</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Technology</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Telecom</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             Industry  Brand\n",
              "0          Automotive      4\n",
              "1  Financial Services      2\n",
              "2         Restaurants      1\n",
              "3              Retail      2\n",
              "4          Technology      6\n",
              "5             Telecom      2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZcokvkG4VgvT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        },
        "outputId": "3314bce8-2f96-4c93-cbb8-ccd60af231d6"
      },
      "source": [
        "indus[indus['Brand'] == indus['Brand'].max()]"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Industry</th>\n",
              "      <th>Brand</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Technology</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Industry  Brand\n",
              "4  Technology      6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zamEuJw6HFxX",
        "colab_type": "text"
      },
      "source": [
        "Problem 2 - List the companiesd whose Company_Advertising budget is < 3 but Brand_Value is > 20"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3yGMjrPUHSFm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "outputId": "93c4d4f6-0aa5-4fc5-9420-57cb400e8701"
      },
      "source": [
        "df_brand_details.loc[(df_brand_details[\"Company_Advertising\"] < 3) & (df_brand_details[\"Brand_Value\"] > 20)][['Brand', 'Brand_Value',\"Company_Advertising\"]]"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Brand</th>\n",
              "      <th>Brand_Value</th>\n",
              "      <th>Company_Advertising</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Apple</td>\n",
              "      <td>145.3</td>\n",
              "      <td>1.200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Microsoft</td>\n",
              "      <td>69.3</td>\n",
              "      <td>2.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>IBM</td>\n",
              "      <td>49.8</td>\n",
              "      <td>1.300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>McDonalds</td>\n",
              "      <td>39.5</td>\n",
              "      <td>0.808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Facebook</td>\n",
              "      <td>36.5</td>\n",
              "      <td>0.135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Disney</td>\n",
              "      <td>34.6</td>\n",
              "      <td>2.800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Cisco</td>\n",
              "      <td>27.6</td>\n",
              "      <td>0.196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Oracle</td>\n",
              "      <td>26.8</td>\n",
              "      <td>0.079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Intel</td>\n",
              "      <td>25.8</td>\n",
              "      <td>1.800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Wal-Mart</td>\n",
              "      <td>24.7</td>\n",
              "      <td>2.400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Verizon</td>\n",
              "      <td>24.5</td>\n",
              "      <td>2.500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Honda</td>\n",
              "      <td>22.6</td>\n",
              "      <td>2.700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Brand  Brand_Value  Company_Advertising\n",
              "0       Apple        145.3                1.200\n",
              "1   Microsoft         69.3                2.300\n",
              "4         IBM         49.8                1.300\n",
              "5   McDonalds         39.5                0.808\n",
              "8    Facebook         36.5                0.135\n",
              "9      Disney         34.6                2.800\n",
              "13      Cisco         27.6                0.196\n",
              "14     Oracle         26.8                0.079\n",
              "16      Intel         25.8                1.800\n",
              "17   Wal-Mart         24.7                2.400\n",
              "18    Verizon         24.5                2.500\n",
              "20      Honda         22.6                2.700"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PhoeL3n9KCJn",
        "colab_type": "text"
      },
      "source": [
        "Problem 3 - Find out the top 5 Technology Brand that showed maximum positive jump in their position (Use Change_LastYr)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f_I2YtGCKIWf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 199
        },
        "outputId": "dd951b81-1074-41e5-dc33-83fd3226a9d4"
      },
      "source": [
        "df_brand_details[df_brand_details['Industry'] == 'Technology'].nlargest(5, ['Change_LastYr'])[\"Brand\"].reset_index()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>index</th>\n",
              "      <th>Brand</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>Facebook</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>11</td>\n",
              "      <td>Amazon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>33</td>\n",
              "      <td>Ebay</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50</td>\n",
              "      <td>Sony</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>Apple</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index     Brand\n",
              "0      8  Facebook\n",
              "1     11    Amazon\n",
              "2     33      Ebay\n",
              "3     50      Sony\n",
              "4      0     Apple"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NGw7jANgLWJb",
        "colab_type": "text"
      },
      "source": [
        "Problem 4 - Find out the Average Brand_Revenue by Industry"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0LZWcfc6La86",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "30073321-40ff-4312-88b5-bf59a1236015"
      },
      "source": [
        "avg_brand_rev = df_brand_details.groupby(['Industry'],as_index=False)['Brand_Revenue'].mean()\n",
        "avg_brand_rev"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Industry</th>\n",
              "      <th>Brand_Revenue</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Apparel</td>\n",
              "      <td>17.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Automotive</td>\n",
              "      <td>97.385714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Beverages</td>\n",
              "      <td>13.133333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Business Services</td>\n",
              "      <td>32.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Consumer Packaged Goods</td>\n",
              "      <td>7.175000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Financial Services</td>\n",
              "      <td>51.622222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Heavy Equipment</td>\n",
              "      <td>36.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Leisure</td>\n",
              "      <td>26.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Luxury</td>\n",
              "      <td>5.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Media</td>\n",
              "      <td>9.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Restaurants</td>\n",
              "      <td>51.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Retail</td>\n",
              "      <td>156.266667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Technology</td>\n",
              "      <td>80.238462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Telecom</td>\n",
              "      <td>129.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Transportation</td>\n",
              "      <td>47.200000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Industry  Brand_Revenue\n",
              "0                   Apparel      17.700000\n",
              "1                Automotive      97.385714\n",
              "2                 Beverages      13.133333\n",
              "3         Business Services      32.800000\n",
              "4   Consumer Packaged Goods       7.175000\n",
              "5        Financial Services      51.622222\n",
              "6           Heavy Equipment      36.100000\n",
              "7                   Leisure      26.400000\n",
              "8                    Luxury       5.900000\n",
              "9                     Media       9.200000\n",
              "10              Restaurants      51.900000\n",
              "11                   Retail     156.266667\n",
              "12               Technology      80.238462\n",
              "13                  Telecom     129.750000\n",
              "14           Transportation      47.200000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    }
  ]
}