Session_1/(6) Pandas Notebook.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Pandas.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "###**Pandas in Python, An introductory session.**\n",
        "- CVI x Analytics \n",
        "\n",
        "- Session #1\n",
        "\n",
        "- Anirudh Kalyan \n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "bskzZuVpvqHr"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![pandas.jpg](data:image/jpeg;base64,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)"
      ],
      "metadata": {
        "id": "6VGUA0SR_4oA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Getting Started: Let's First import Pandas library**"
      ],
      "metadata": {
        "id": "VjhvZ9qExTbm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import copy"
      ],
      "metadata": {
        "id": "wLrUNncrxQVG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Before we begin with pandas, we would need to import the file \n",
        "\n",
        "###**Our goal in this session is to find the most nutritious cereal under each brand.** "
      ],
      "metadata": {
        "id": "YSDgtMSIwTMj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Link to the dataset being used : https://www.kaggle.com/datasets/crawford/80-cereals"
      ],
      "metadata": {
        "id": "Zcjw5GOS76b7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/cereal.csv') #here we name this as a dataframe. "
      ],
      "metadata": {
        "id": "lgptN5-0v5t1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Note that pandas offers ways to read into excel and text files also. \n",
        "\n",
        "But for the sake of this session we are sticking with CSV.\n",
        "\n"
      ],
      "metadata": {
        "id": "3GCCVzX5-GW1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "7cRaJtW-DP0K"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**More Commands in Pandas**"
      ],
      "metadata": {
        "id": "bWA_PA72CqFL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list(df.columns) #as the name suggests, it provides the name of all the columns in the DataFrame."
      ],
      "metadata": {
        "id": "GbPzRe5gyeEx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now let's try and access rows of a particular column "
      ],
      "metadata": {
        "id": "Zdvix0jvyJ4j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"mfr\"][1 : 5] #The final value is exclusive, remember that!"
      ],
      "metadata": {
        "id": "gwYNV1wHx8xI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now you'd have noticed that there is abbreviations in the columns of the dataset, which makes it tough for viewing. \n",
        "\n",
        "Let's rename the columns. "
      ],
      "metadata": {
        "id": "8CHEvuMFBdz2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.rename(columns={\"mfr\" : \"Manufacturer\", \"potass\":\"Potassium\", \"carbo\":\"Carbohydrates\"},inplace = True)\n"
      ],
      "metadata": {
        "id": "SDbf7OLUBuRx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Question : What is the \"inplace = True\" placed there for?**\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "x62qAZ74B8Zs"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "> It's there to save memory in large scale applications, wherein it will directly discard the old DF and make way for the new one.\n"
      ],
      "metadata": {
        "id": "GZRsrcTKDNY9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now that we have our Cereal columns sorted in place, Let's have another look at this dataset: \n"
      ],
      "metadata": {
        "id": "3CEuYTl6Ddfp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "id": "J8qkda3GEC0O",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 653
        },
        "outputId": "ea825ef2-32d8-444c-ea43-278c6f556b07"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                         name Manufacturer type  calories  protein  fat  \\\n",
              "0                   100% Bran            N    C        70        4    1   \n",
              "1           100% Natural Bran            Q    C       120        3    5   \n",
              "2                    All-Bran            K    C        70        4    1   \n",
              "3   All-Bran with Extra Fiber            K    C        50        4    0   \n",
              "4              Almond Delight            R    C       110        2    2   \n",
              "..                        ...          ...  ...       ...      ...  ...   \n",
              "72                    Triples            G    C       110        2    1   \n",
              "73                       Trix            G    C       110        1    1   \n",
              "74                 Wheat Chex            R    C       100        3    1   \n",
              "75                   Wheaties            G    C       100        3    1   \n",
              "76        Wheaties Honey Gold            G    C       110        2    1   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "0      130   10.0            5.0       6        280        25      3     1.0   \n",
              "1       15    2.0            8.0       8        135         0      3     1.0   \n",
              "2      260    9.0            7.0       5        320        25      3     1.0   \n",
              "3      140   14.0            8.0       0        330        25      3     1.0   \n",
              "4      200    1.0           14.0       8         -1        25      3     1.0   \n",
              "..     ...    ...            ...     ...        ...       ...    ...     ...   \n",
              "72     250    0.0           21.0       3         60        25      3     1.0   \n",
              "73     140    0.0           13.0      12         25        25      2     1.0   \n",
              "74     230    3.0           17.0       3        115        25      1     1.0   \n",
              "75     200    3.0           17.0       3        110        25      1     1.0   \n",
              "76     200    1.0           16.0       8         60        25      1     1.0   \n",
              "\n",
              "    cups     rating  \n",
              "0   0.33  68.402973  \n",
              "1   1.00  33.983679  \n",
              "2   0.33  59.425505  \n",
              "3   0.50  93.704912  \n",
              "4   0.75  34.384843  \n",
              "..   ...        ...  \n",
              "72  0.75  39.106174  \n",
              "73  1.00  27.753301  \n",
              "74  0.67  49.787445  \n",
              "75  1.00  51.592193  \n",
              "76  0.75  36.187559  \n",
              "\n",
              "[77 rows x 16 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5d83fb85-c9ef-423d-9c34-d47c5aef2f2f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100% Bran</td>\n",
              "      <td>N</td>\n",
              "      <td>C</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6</td>\n",
              "      <td>280</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Q</td>\n",
              "      <td>C</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>K</td>\n",
              "      <td>C</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>K</td>\n",
              "      <td>C</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Almond Delight</td>\n",
              "      <td>R</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>-1</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>34.384843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>Triples</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.106174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>Trix</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>27.753301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>Wheat Chex</td>\n",
              "      <td>R</td>\n",
              "      <td>C</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>230</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>115</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.67</td>\n",
              "      <td>49.787445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>Wheaties</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>110</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>51.592193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>Wheaties Honey Gold</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.187559</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>77 rows × 16 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d83fb85-c9ef-423d-9c34-d47c5aef2f2f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5d83fb85-c9ef-423d-9c34-d47c5aef2f2f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5d83fb85-c9ef-423d-9c34-d47c5aef2f2f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Notice that the author of this dataset has gone deep into the abreviations. \n",
        "\n",
        "let's expand them to make it easy for the viewer. \n",
        "\n",
        "A = American Home Food Products\n",
        "\n",
        "G = General Mills\n",
        "\n",
        "K = Kelloggs\n",
        "\n",
        "N = Nabisco\n",
        "\n",
        "P = Post\n",
        "\n",
        "Q = Quaker Oats\n",
        "\n",
        "R = Ralston Purina\n",
        "\n",
        "This is the reference code for the type column. "
      ],
      "metadata": {
        "id": "kRpI-dn1EU6k"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[df['type'] == 'C', 'type'] = 'Cold' #taking care of the type column. \n",
        "df.loc[df[\"type\"]==\"H\",\"type\"] = 'Hot'\n",
        "\n",
        "df.loc[df[\"Manufacturer\"]=='N',\"Manufacturer\"]=\"Nabisco\"\n",
        "df.loc[df[\"Manufacturer\"]=='A',\"Manufacturer\"]=\"American Home Food Products\"\n",
        "df.loc[df[\"Manufacturer\"]=='K',\"Manufacturer\"]=\"Kelloggs\"\n",
        "df.loc[df[\"Manufacturer\"]=='G',\"Manufacturer\"]=\"General Mills\"\n",
        "df.loc[df[\"Manufacturer\"]=='P',\"Manufacturer\"]=\"Post\"\n",
        "df.loc[df[\"Manufacturer\"]=='Q',\"Manufacturer\"]=\"Quaker Oats\"\n",
        "df.loc[df[\"Manufacturer\"]=='R',\"Manufacturer\"]=\"Ralston Purina\" \n",
        "#taking care of expanding the \"manufacturer\" Column \n",
        "\n",
        "\n",
        "df\n"
      ],
      "metadata": {
        "id": "kS_6aEunEn70",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 653
        },
        "outputId": "03254501-8f2c-48a9-86d0-92eaffa7db60"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                         name    Manufacturer  type  calories  protein  fat  \\\n",
              "0                   100% Bran         Nabisco  Cold        70        4    1   \n",
              "1           100% Natural Bran     Quaker Oats  Cold       120        3    5   \n",
              "2                    All-Bran        Kelloggs  Cold        70        4    1   \n",
              "3   All-Bran with Extra Fiber        Kelloggs  Cold        50        4    0   \n",
              "4              Almond Delight  Ralston Purina  Cold       110        2    2   \n",
              "..                        ...             ...   ...       ...      ...  ...   \n",
              "72                    Triples   General Mills  Cold       110        2    1   \n",
              "73                       Trix   General Mills  Cold       110        1    1   \n",
              "74                 Wheat Chex  Ralston Purina  Cold       100        3    1   \n",
              "75                   Wheaties   General Mills  Cold       100        3    1   \n",
              "76        Wheaties Honey Gold   General Mills  Cold       110        2    1   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "0      130   10.0            5.0       6        280        25      3     1.0   \n",
              "1       15    2.0            8.0       8        135         0      3     1.0   \n",
              "2      260    9.0            7.0       5        320        25      3     1.0   \n",
              "3      140   14.0            8.0       0        330        25      3     1.0   \n",
              "4      200    1.0           14.0       8         -1        25      3     1.0   \n",
              "..     ...    ...            ...     ...        ...       ...    ...     ...   \n",
              "72     250    0.0           21.0       3         60        25      3     1.0   \n",
              "73     140    0.0           13.0      12         25        25      2     1.0   \n",
              "74     230    3.0           17.0       3        115        25      1     1.0   \n",
              "75     200    3.0           17.0       3        110        25      1     1.0   \n",
              "76     200    1.0           16.0       8         60        25      1     1.0   \n",
              "\n",
              "    cups     rating  \n",
              "0   0.33  68.402973  \n",
              "1   1.00  33.983679  \n",
              "2   0.33  59.425505  \n",
              "3   0.50  93.704912  \n",
              "4   0.75  34.384843  \n",
              "..   ...        ...  \n",
              "72  0.75  39.106174  \n",
              "73  1.00  27.753301  \n",
              "74  0.67  49.787445  \n",
              "75  1.00  51.592193  \n",
              "76  0.75  36.187559  \n",
              "\n",
              "[77 rows x 16 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-772710de-9aac-41bb-88a2-6d3989474950\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100% Bran</td>\n",
              "      <td>Nabisco</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6</td>\n",
              "      <td>280</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Almond Delight</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>-1</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>34.384843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>Triples</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.106174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>Trix</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>27.753301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>Wheat Chex</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>230</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>115</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.67</td>\n",
              "      <td>49.787445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>Wheaties</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>110</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>51.592193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>Wheaties Honey Gold</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.187559</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>77 rows × 16 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-772710de-9aac-41bb-88a2-6d3989474950')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-772710de-9aac-41bb-88a2-6d3989474950 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-772710de-9aac-41bb-88a2-6d3989474950');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Pay attention to the fact that we are using the \"loc\" function, which is based on locating based on labels of the rows and columns. \n",
        "\n",
        "It's cousin, \"iloc\" is used to reference and access elements using integers. "
      ],
      "metadata": {
        "id": "Du4GFKV-HBcp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[1,5] #A particular coordinate \n",
        "df.iloc[1:5] #A particular range of rows"
      ],
      "metadata": {
        "id": "WObOTW2JHeDb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "outputId": "94208139-6b08-47f7-e15d-a87979912579"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        name    Manufacturer  type  calories  protein  fat  \\\n",
              "1          100% Natural Bran     Quaker Oats  Cold       120        3    5   \n",
              "2                   All-Bran        Kelloggs  Cold        70        4    1   \n",
              "3  All-Bran with Extra Fiber        Kelloggs  Cold        50        4    0   \n",
              "4             Almond Delight  Ralston Purina  Cold       110        2    2   \n",
              "\n",
              "   sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "1      15    2.0            8.0       8        135         0      3     1.0   \n",
              "2     260    9.0            7.0       5        320        25      3     1.0   \n",
              "3     140   14.0            8.0       0        330        25      3     1.0   \n",
              "4     200    1.0           14.0       8         -1        25      3     1.0   \n",
              "\n",
              "   cups     rating  \n",
              "1  1.00  33.983679  \n",
              "2  0.33  59.425505  \n",
              "3  0.50  93.704912  \n",
              "4  0.75  34.384843  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-84abe708-e0ae-4618-8611-9e2d4b529d33\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Almond Delight</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>-1</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>34.384843</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-84abe708-e0ae-4618-8611-9e2d4b529d33')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-84abe708-e0ae-4618-8611-9e2d4b529d33 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-84abe708-e0ae-4618-8611-9e2d4b529d33');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now let's say that we want to find all the cereals that are made by Kelloggs in this list. \n",
        "\n",
        "How does Pandas help us with that?"
      ],
      "metadata": {
        "id": "PlJB2WF9H9XF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "(df.loc[df[\"Manufacturer\"]==\"Kelloggs\"])\n"
      ],
      "metadata": {
        "id": "XGCw5A9JISR2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 806
        },
        "outputId": "0b8c5faf-2660-4339-836e-a4dba36889c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                           name Manufacturer  type  calories  protein  fat  \\\n",
              "2                      All-Bran     Kelloggs  Cold        70        4    1   \n",
              "3     All-Bran with Extra Fiber     Kelloggs  Cold        50        4    0   \n",
              "6                   Apple Jacks     Kelloggs  Cold       110        2    0   \n",
              "16                  Corn Flakes     Kelloggs  Cold       100        2    0   \n",
              "17                    Corn Pops     Kelloggs  Cold       110        1    0   \n",
              "19           Cracklin' Oat Bran     Kelloggs  Cold       110        3    3   \n",
              "21                      Crispix     Kelloggs  Cold       110        2    0   \n",
              "24                  Froot Loops     Kelloggs  Cold       110        2    1   \n",
              "25               Frosted Flakes     Kelloggs  Cold       110        1    0   \n",
              "26          Frosted Mini-Wheats     Kelloggs  Cold       100        3    0   \n",
              "28                Fruitful Bran     Kelloggs  Cold       120        3    0   \n",
              "38  Just Right Crunchy  Nuggets     Kelloggs  Cold       110        2    1   \n",
              "39       Just Right Fruit & Nut     Kelloggs  Cold       140        3    1   \n",
              "46         Mueslix Crispy Blend     Kelloggs  Cold       160        3    2   \n",
              "48             Nut&Honey Crunch     Kelloggs  Cold       120        2    1   \n",
              "49    Nutri-Grain Almond-Raisin     Kelloggs  Cold       140        3    2   \n",
              "50            Nutri-grain Wheat     Kelloggs  Cold        90        3    0   \n",
              "53                   Product 19     Kelloggs  Cold       100        3    0   \n",
              "58                  Raisin Bran     Kelloggs  Cold       120        3    1   \n",
              "60               Raisin Squares     Kelloggs  Cold        90        2    0   \n",
              "62                Rice Krispies     Kelloggs  Cold       110        2    0   \n",
              "66                       Smacks     Kelloggs  Cold       110        2    1   \n",
              "67                    Special K     Kelloggs  Cold       110        6    0   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "2      260    9.0            7.0       5        320        25      3    1.00   \n",
              "3      140   14.0            8.0       0        330        25      3    1.00   \n",
              "6      125    1.0           11.0      14         30        25      2    1.00   \n",
              "16     290    1.0           21.0       2         35        25      1    1.00   \n",
              "17      90    1.0           13.0      12         20        25      2    1.00   \n",
              "19     140    4.0           10.0       7        160        25      3    1.00   \n",
              "21     220    1.0           21.0       3         30        25      3    1.00   \n",
              "24     125    1.0           11.0      13         30        25      2    1.00   \n",
              "25     200    1.0           14.0      11         25        25      1    1.00   \n",
              "26       0    3.0           14.0       7        100        25      2    1.00   \n",
              "28     240    5.0           14.0      12        190        25      3    1.33   \n",
              "38     170    1.0           17.0       6         60       100      3    1.00   \n",
              "39     170    2.0           20.0       9         95       100      3    1.30   \n",
              "46     150    3.0           17.0      13        160        25      3    1.50   \n",
              "48     190    0.0           15.0       9         40        25      2    1.00   \n",
              "49     220    3.0           21.0       7        130        25      3    1.33   \n",
              "50     170    3.0           18.0       2         90        25      3    1.00   \n",
              "53     320    1.0           20.0       3         45       100      3    1.00   \n",
              "58     210    5.0           14.0      12        240        25      2    1.33   \n",
              "60       0    2.0           15.0       6        110        25      3    1.00   \n",
              "62     290    0.0           22.0       3         35        25      1    1.00   \n",
              "66      70    1.0            9.0      15         40        25      2    1.00   \n",
              "67     230    1.0           16.0       3         55        25      1    1.00   \n",
              "\n",
              "    cups     rating  \n",
              "2   0.33  59.425505  \n",
              "3   0.50  93.704912  \n",
              "6   1.00  33.174094  \n",
              "16  1.00  45.863324  \n",
              "17  1.00  35.782791  \n",
              "19  0.50  40.448772  \n",
              "21  1.00  46.895644  \n",
              "24  1.00  32.207582  \n",
              "25  0.75  31.435973  \n",
              "26  0.80  58.345141  \n",
              "28  0.67  41.015492  \n",
              "38  1.00  36.523683  \n",
              "39  0.75  36.471512  \n",
              "46  0.67  30.313351  \n",
              "48  0.67  29.924285  \n",
              "49  0.67  40.692320  \n",
              "50  1.00  59.642837  \n",
              "53  1.00  41.503540  \n",
              "58  0.75  39.259197  \n",
              "60  0.50  55.333142  \n",
              "62  1.00  40.560159  \n",
              "66  0.75  31.230054  \n",
              "67  1.00  53.131324  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a1baacf4-c502-4515-a90a-ac3671116cf0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Apple Jacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.174094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Corn Flakes</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>290</td>\n",
              "      <td>1.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>2</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>45.863324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Corn Pops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>90</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>20</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>35.782791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Cracklin' Oat Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>140</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>40.448772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Crispix</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>220</td>\n",
              "      <td>1.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>46.895644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Froot Loops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>13</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>32.207582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Frosted Flakes</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>11</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.435973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Frosted Mini-Wheats</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>7</td>\n",
              "      <td>100</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.80</td>\n",
              "      <td>58.345141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Fruitful Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>240</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>190</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>41.015492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Just Right Crunchy  Nuggets</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>170</td>\n",
              "      <td>1.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>6</td>\n",
              "      <td>60</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>36.523683</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Just Right Fruit &amp; Nut</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>170</td>\n",
              "      <td>2.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>9</td>\n",
              "      <td>95</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.30</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.471512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Mueslix Crispy Blend</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>160</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>150</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>13</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.50</td>\n",
              "      <td>0.67</td>\n",
              "      <td>30.313351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Nut&amp;Honey Crunch</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>190</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>9</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>29.924285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>Nutri-Grain Almond-Raisin</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>220</td>\n",
              "      <td>3.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7</td>\n",
              "      <td>130</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>40.692320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>Nutri-grain Wheat</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>170</td>\n",
              "      <td>3.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2</td>\n",
              "      <td>90</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>59.642837</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Product 19</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>320</td>\n",
              "      <td>1.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>3</td>\n",
              "      <td>45</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>41.503540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>Raisin Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>210</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>240</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.259197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>Raisin Squares</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>6</td>\n",
              "      <td>110</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>55.333142</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>Rice Krispies</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>290</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>3</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>40.560159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>Smacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>70</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>15</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.230054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>Special K</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>230</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>3</td>\n",
              "      <td>55</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>53.131324</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a1baacf4-c502-4515-a90a-ac3671116cf0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a1baacf4-c502-4515-a90a-ac3671116cf0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a1baacf4-c502-4515-a90a-ac3671116cf0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 121
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The interesting thing about this is that we can take multiple booleans like this and display the final output. "
      ],
      "metadata": {
        "id": "cNt0g4OLJTRB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now that we learnt how to seperate by brand, let's work on sorting by brand. "
      ],
      "metadata": {
        "id": "fFmHrmHyKGjX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = df.loc[df[\"Manufacturer\"]==\"Kelloggs\"] #creates a seperate dataframe that contains only Kelloggs info. \n",
        "df2.sort_values([\"fiber\"], ascending = False) #sorts all data based on fiber values, in descending order. \n",
        "\n"
      ],
      "metadata": {
        "id": "ajNWoyANyFHZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 806
        },
        "outputId": "8658e14c-777a-45a4-da43-6b6d058e8142"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                           name Manufacturer  type  calories  protein  fat  \\\n",
              "3     All-Bran with Extra Fiber     Kelloggs  Cold        50        4    0   \n",
              "2                      All-Bran     Kelloggs  Cold        70        4    1   \n",
              "58                  Raisin Bran     Kelloggs  Cold       120        3    1   \n",
              "28                Fruitful Bran     Kelloggs  Cold       120        3    0   \n",
              "19           Cracklin' Oat Bran     Kelloggs  Cold       110        3    3   \n",
              "46         Mueslix Crispy Blend     Kelloggs  Cold       160        3    2   \n",
              "50            Nutri-grain Wheat     Kelloggs  Cold        90        3    0   \n",
              "49    Nutri-Grain Almond-Raisin     Kelloggs  Cold       140        3    2   \n",
              "26          Frosted Mini-Wheats     Kelloggs  Cold       100        3    0   \n",
              "60               Raisin Squares     Kelloggs  Cold        90        2    0   \n",
              "39       Just Right Fruit & Nut     Kelloggs  Cold       140        3    1   \n",
              "66                       Smacks     Kelloggs  Cold       110        2    1   \n",
              "53                   Product 19     Kelloggs  Cold       100        3    0   \n",
              "38  Just Right Crunchy  Nuggets     Kelloggs  Cold       110        2    1   \n",
              "25               Frosted Flakes     Kelloggs  Cold       110        1    0   \n",
              "24                  Froot Loops     Kelloggs  Cold       110        2    1   \n",
              "21                      Crispix     Kelloggs  Cold       110        2    0   \n",
              "17                    Corn Pops     Kelloggs  Cold       110        1    0   \n",
              "16                  Corn Flakes     Kelloggs  Cold       100        2    0   \n",
              "6                   Apple Jacks     Kelloggs  Cold       110        2    0   \n",
              "67                    Special K     Kelloggs  Cold       110        6    0   \n",
              "48             Nut&Honey Crunch     Kelloggs  Cold       120        2    1   \n",
              "62                Rice Krispies     Kelloggs  Cold       110        2    0   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "3      140   14.0            8.0       0        330        25      3    1.00   \n",
              "2      260    9.0            7.0       5        320        25      3    1.00   \n",
              "58     210    5.0           14.0      12        240        25      2    1.33   \n",
              "28     240    5.0           14.0      12        190        25      3    1.33   \n",
              "19     140    4.0           10.0       7        160        25      3    1.00   \n",
              "46     150    3.0           17.0      13        160        25      3    1.50   \n",
              "50     170    3.0           18.0       2         90        25      3    1.00   \n",
              "49     220    3.0           21.0       7        130        25      3    1.33   \n",
              "26       0    3.0           14.0       7        100        25      2    1.00   \n",
              "60       0    2.0           15.0       6        110        25      3    1.00   \n",
              "39     170    2.0           20.0       9         95       100      3    1.30   \n",
              "66      70    1.0            9.0      15         40        25      2    1.00   \n",
              "53     320    1.0           20.0       3         45       100      3    1.00   \n",
              "38     170    1.0           17.0       6         60       100      3    1.00   \n",
              "25     200    1.0           14.0      11         25        25      1    1.00   \n",
              "24     125    1.0           11.0      13         30        25      2    1.00   \n",
              "21     220    1.0           21.0       3         30        25      3    1.00   \n",
              "17      90    1.0           13.0      12         20        25      2    1.00   \n",
              "16     290    1.0           21.0       2         35        25      1    1.00   \n",
              "6      125    1.0           11.0      14         30        25      2    1.00   \n",
              "67     230    1.0           16.0       3         55        25      1    1.00   \n",
              "48     190    0.0           15.0       9         40        25      2    1.00   \n",
              "62     290    0.0           22.0       3         35        25      1    1.00   \n",
              "\n",
              "    cups     rating  \n",
              "3   0.50  93.704912  \n",
              "2   0.33  59.425505  \n",
              "58  0.75  39.259197  \n",
              "28  0.67  41.015492  \n",
              "19  0.50  40.448772  \n",
              "46  0.67  30.313351  \n",
              "50  1.00  59.642837  \n",
              "49  0.67  40.692320  \n",
              "26  0.80  58.345141  \n",
              "60  0.50  55.333142  \n",
              "39  0.75  36.471512  \n",
              "66  0.75  31.230054  \n",
              "53  1.00  41.503540  \n",
              "38  1.00  36.523683  \n",
              "25  0.75  31.435973  \n",
              "24  1.00  32.207582  \n",
              "21  1.00  46.895644  \n",
              "17  1.00  35.782791  \n",
              "16  1.00  45.863324  \n",
              "6   1.00  33.174094  \n",
              "67  1.00  53.131324  \n",
              "48  0.67  29.924285  \n",
              "62  1.00  40.560159  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6d3d6e9d-f224-4f45-b790-e09ba31104e6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>Raisin Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>210</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>240</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.259197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Fruitful Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>240</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>190</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>41.015492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Cracklin' Oat Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>140</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>40.448772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Mueslix Crispy Blend</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>160</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>150</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>13</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.50</td>\n",
              "      <td>0.67</td>\n",
              "      <td>30.313351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>Nutri-grain Wheat</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>170</td>\n",
              "      <td>3.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2</td>\n",
              "      <td>90</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>59.642837</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>Nutri-Grain Almond-Raisin</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>220</td>\n",
              "      <td>3.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>7</td>\n",
              "      <td>130</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>40.692320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Frosted Mini-Wheats</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>7</td>\n",
              "      <td>100</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.80</td>\n",
              "      <td>58.345141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>Raisin Squares</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>6</td>\n",
              "      <td>110</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>55.333142</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Just Right Fruit &amp; Nut</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>170</td>\n",
              "      <td>2.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>9</td>\n",
              "      <td>95</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.30</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.471512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>Smacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>70</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>15</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.230054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Product 19</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>320</td>\n",
              "      <td>1.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>3</td>\n",
              "      <td>45</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>41.503540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Just Right Crunchy  Nuggets</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>170</td>\n",
              "      <td>1.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>6</td>\n",
              "      <td>60</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>36.523683</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Frosted Flakes</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>11</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.435973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Froot Loops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>13</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>32.207582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Crispix</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>220</td>\n",
              "      <td>1.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>46.895644</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Corn Pops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>90</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>20</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>35.782791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Corn Flakes</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>290</td>\n",
              "      <td>1.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>2</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>45.863324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Apple Jacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.174094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>Special K</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>230</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>3</td>\n",
              "      <td>55</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>53.131324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Nut&amp;Honey Crunch</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>190</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>9</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>29.924285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>Rice Krispies</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>290</td>\n",
              "      <td>0.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>3</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>40.560159</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6d3d6e9d-f224-4f45-b790-e09ba31104e6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6d3d6e9d-f224-4f45-b790-e09ba31104e6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6d3d6e9d-f224-4f45-b790-e09ba31104e6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now as we saw with the dataset, the amount of Hot cereal is less than the amount of cold cereal, so let's say we want to only look at the hot cereal..."
      ],
      "metadata": {
        "id": "X7F6Koop0fvW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[(df[\"type\"]==\"Hot\")] #any logical operator that returns a boolean value can be used here. \n",
        "df.loc[(df[\"type\"]==\"Hot\") & (df[\"protein\"]>3)] "
      ],
      "metadata": {
        "id": "JpTnpPjo00Pm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 189
        },
        "outputId": "6a805e89-81fd-4b8c-9f4a-f085fe0a3ad0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              name                 Manufacturer type  calories  protein  fat  \\\n",
              "43           Maypo  American Home Food Products  Hot       100        4    1   \n",
              "57  Quaker Oatmeal                  Quaker Oats  Hot       100        5    2   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "43       0    0.0           16.0       3         95        25      2     1.0   \n",
              "57       0    2.7           -1.0      -1        110         0      1     1.0   \n",
              "\n",
              "    cups     rating  \n",
              "43  1.00  54.850917  \n",
              "57  0.67  50.828392  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-263c8ad6-b29c-4606-b07b-d6775a2521b1\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>Maypo</td>\n",
              "      <td>American Home Food Products</td>\n",
              "      <td>Hot</td>\n",
              "      <td>100</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>3</td>\n",
              "      <td>95</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>54.850917</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>Quaker Oatmeal</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Hot</td>\n",
              "      <td>100</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2.7</td>\n",
              "      <td>-1.0</td>\n",
              "      <td>-1</td>\n",
              "      <td>110</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.67</td>\n",
              "      <td>50.828392</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-263c8ad6-b29c-4606-b07b-d6775a2521b1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-263c8ad6-b29c-4606-b07b-d6775a2521b1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-263c8ad6-b29c-4606-b07b-d6775a2521b1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "Now let's do one thing, let's sort data by amount of sugar present, and classify based on brand. "
      ],
      "metadata": {
        "id": "aKaxnYhN26KI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df3 = df.loc[(df[\"sugars\"]>8)].sort_values([\"sugars\"], ascending = False)\n",
        "df3"
      ],
      "metadata": {
        "id": "Esvqu4NL3XQF",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "4879dc77-f40a-4b4e-cca2-f0543cbe0d8d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                      name    Manufacturer  type  calories  \\\n",
              "66                                  Smacks        Kelloggs  Cold       110   \n",
              "30                            Golden Crisp            Post  Cold       100   \n",
              "6                              Apple Jacks        Kelloggs  Cold       110   \n",
              "70                       Total Raisin Bran   General Mills  Cold       140   \n",
              "52                   Post Nat. Raisin Bran            Post  Cold       120   \n",
              "14                             Cocoa Puffs   General Mills  Cold       110   \n",
              "46                    Mueslix Crispy Blend        Kelloggs  Cold       160   \n",
              "18                           Count Chocula   General Mills  Cold       110   \n",
              "24                             Froot Loops        Kelloggs  Cold       110   \n",
              "73                                    Trix   General Mills  Cold       110   \n",
              "29                          Fruity Pebbles            Post  Cold       110   \n",
              "58                             Raisin Bran        Kelloggs  Cold       120   \n",
              "28                           Fruitful Bran        Kelloggs  Cold       120   \n",
              "42                            Lucky Charms   General Mills  Cold       110   \n",
              "17                               Corn Pops        Kelloggs  Cold       110   \n",
              "10                            Cap'n'Crunch     Quaker Oats  Cold       120   \n",
              "45       Muesli Raisins; Peaches; & Pecans  Ralston Purina  Cold       150   \n",
              "44        Muesli Raisins; Dates; & Almonds  Ralston Purina  Cold       150   \n",
              "35                        Honey Graham Ohs     Quaker Oats  Cold       120   \n",
              "37                              Honey-comb            Post  Cold       110   \n",
              "25                          Frosted Flakes        Kelloggs  Cold       110   \n",
              "36                      Honey Nut Cheerios   General Mills  Cold       110   \n",
              "51                    Oatmeal Raisin Crisp   General Mills  Cold       130   \n",
              "27  Fruit & Fibre Dates; Walnuts; and Oats            Post  Cold       120   \n",
              "22                  Crispy Wheat & Raisins   General Mills  Cold       100   \n",
              "5                  Apple Cinnamon Cheerios   General Mills  Cold       110   \n",
              "39                  Just Right Fruit & Nut        Kelloggs  Cold       140   \n",
              "31                          Golden Grahams   General Mills  Cold       110   \n",
              "48                        Nut&Honey Crunch        Kelloggs  Cold       120   \n",
              "12                   Cinnamon Toast Crunch   General Mills  Cold       120   \n",
              "\n",
              "    protein  fat  sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  \\\n",
              "66        2    1      70    1.0            9.0      15         40        25   \n",
              "30        2    0      45    0.0           11.0      15         40        25   \n",
              "6         2    0     125    1.0           11.0      14         30        25   \n",
              "70        3    1     190    4.0           15.0      14        230       100   \n",
              "52        3    1     200    6.0           11.0      14        260        25   \n",
              "14        1    1     180    0.0           12.0      13         55        25   \n",
              "46        3    2     150    3.0           17.0      13        160        25   \n",
              "18        1    1     180    0.0           12.0      13         65        25   \n",
              "24        2    1     125    1.0           11.0      13         30        25   \n",
              "73        1    1     140    0.0           13.0      12         25        25   \n",
              "29        1    1     135    0.0           13.0      12         25        25   \n",
              "58        3    1     210    5.0           14.0      12        240        25   \n",
              "28        3    0     240    5.0           14.0      12        190        25   \n",
              "42        2    1     180    0.0           12.0      12         55        25   \n",
              "17        1    0      90    1.0           13.0      12         20        25   \n",
              "10        1    2     220    0.0           12.0      12         35        25   \n",
              "45        4    3     150    3.0           16.0      11        170        25   \n",
              "44        4    3      95    3.0           16.0      11        170        25   \n",
              "35        1    2     220    1.0           12.0      11         45        25   \n",
              "37        1    0     180    0.0           14.0      11         35        25   \n",
              "25        1    0     200    1.0           14.0      11         25        25   \n",
              "36        3    1     250    1.5           11.5      10         90        25   \n",
              "51        3    2     170    1.5           13.5      10        120        25   \n",
              "27        3    2     160    5.0           12.0      10        200        25   \n",
              "22        2    1     140    2.0           11.0      10        120        25   \n",
              "5         2    2     180    1.5           10.5      10         70        25   \n",
              "39        3    1     170    2.0           20.0       9         95       100   \n",
              "31        1    1     280    0.0           15.0       9         45        25   \n",
              "48        2    1     190    0.0           15.0       9         40        25   \n",
              "12        1    3     210    0.0           13.0       9         45        25   \n",
              "\n",
              "    shelf  weight  cups     rating  \n",
              "66      2    1.00  0.75  31.230054  \n",
              "30      1    1.00  0.88  35.252444  \n",
              "6       2    1.00  1.00  33.174094  \n",
              "70      3    1.50  1.00  28.592785  \n",
              "52      3    1.33  0.67  37.840594  \n",
              "14      2    1.00  1.00  22.736446  \n",
              "46      3    1.50  0.67  30.313351  \n",
              "18      2    1.00  1.00  22.396513  \n",
              "24      2    1.00  1.00  32.207582  \n",
              "73      2    1.00  1.00  27.753301  \n",
              "29      2    1.00  0.75  28.025765  \n",
              "58      2    1.33  0.75  39.259197  \n",
              "28      3    1.33  0.67  41.015492  \n",
              "42      2    1.00  1.00  26.734515  \n",
              "17      2    1.00  1.00  35.782791  \n",
              "10      2    1.00  0.75  18.042851  \n",
              "45      3    1.00  1.00  34.139765  \n",
              "44      3    1.00  1.00  37.136863  \n",
              "35      2    1.00  1.00  21.871292  \n",
              "37      1    1.00  1.33  28.742414  \n",
              "25      1    1.00  0.75  31.435973  \n",
              "36      1    1.00  0.75  31.072217  \n",
              "51      3    1.25  0.50  30.450843  \n",
              "27      3    1.25  0.67  40.917047  \n",
              "22      3    1.00  0.75  36.176196  \n",
              "5       1    1.00  0.75  29.509541  \n",
              "39      3    1.30  0.75  36.471512  \n",
              "31      2    1.00  0.75  23.804043  \n",
              "48      2    1.00  0.67  29.924285  \n",
              "12      2    1.00  0.75  19.823573  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9fd8df64-9556-4264-9689-01bb89b0f715\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>Smacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>70</td>\n",
              "      <td>1.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>15</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.230054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Golden Crisp</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>45</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>15</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.88</td>\n",
              "      <td>35.252444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Apple Jacks</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.174094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>Total Raisin Bran</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>190</td>\n",
              "      <td>4.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>14</td>\n",
              "      <td>230</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.50</td>\n",
              "      <td>1.00</td>\n",
              "      <td>28.592785</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>Post Nat. Raisin Bran</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>6.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14</td>\n",
              "      <td>260</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>37.840594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Cocoa Puffs</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>180</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>13</td>\n",
              "      <td>55</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>22.736446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Mueslix Crispy Blend</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>160</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>150</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>13</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.50</td>\n",
              "      <td>0.67</td>\n",
              "      <td>30.313351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Count Chocula</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>180</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>13</td>\n",
              "      <td>65</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>22.396513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Froot Loops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "      <td>1.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>13</td>\n",
              "      <td>30</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>32.207582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>Trix</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>27.753301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Fruity Pebbles</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>135</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>28.025765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>Raisin Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>210</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>240</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.259197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Fruitful Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>240</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>190</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>41.015492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Lucky Charms</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>180</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12</td>\n",
              "      <td>55</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>26.734515</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Corn Pops</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>90</td>\n",
              "      <td>1.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>20</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>35.782791</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Cap'n'Crunch</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>220</td>\n",
              "      <td>0.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>12</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>18.042851</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Muesli Raisins; Peaches; &amp; Pecans</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>150</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>150</td>\n",
              "      <td>3.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>11</td>\n",
              "      <td>170</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>34.139765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Muesli Raisins; Dates; &amp; Almonds</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>150</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>95</td>\n",
              "      <td>3.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>11</td>\n",
              "      <td>170</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>37.136863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Honey Graham Ohs</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>220</td>\n",
              "      <td>1.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>11</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>21.871292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Honey-comb</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>180</td>\n",
              "      <td>0.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>11</td>\n",
              "      <td>35</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.33</td>\n",
              "      <td>28.742414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Frosted Flakes</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>11</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.435973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Honey Nut Cheerios</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>1.5</td>\n",
              "      <td>11.5</td>\n",
              "      <td>10</td>\n",
              "      <td>90</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>31.072217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>Oatmeal Raisin Crisp</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>130</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>170</td>\n",
              "      <td>1.5</td>\n",
              "      <td>13.5</td>\n",
              "      <td>10</td>\n",
              "      <td>120</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.25</td>\n",
              "      <td>0.50</td>\n",
              "      <td>30.450843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Fruit &amp; Fibre Dates; Walnuts; and Oats</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>160</td>\n",
              "      <td>5.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>10</td>\n",
              "      <td>200</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.25</td>\n",
              "      <td>0.67</td>\n",
              "      <td>40.917047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Crispy Wheat &amp; Raisins</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>2.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>10</td>\n",
              "      <td>120</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.176196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Apple Cinnamon Cheerios</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>180</td>\n",
              "      <td>1.5</td>\n",
              "      <td>10.5</td>\n",
              "      <td>10</td>\n",
              "      <td>70</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>29.509541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Just Right Fruit &amp; Nut</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>170</td>\n",
              "      <td>2.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>9</td>\n",
              "      <td>95</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.30</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.471512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Golden Grahams</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>280</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>9</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>23.804043</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Nut&amp;Honey Crunch</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>190</td>\n",
              "      <td>0.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>9</td>\n",
              "      <td>40</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>29.924285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Cinnamon Toast Crunch</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>210</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>9</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>19.823573</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9fd8df64-9556-4264-9689-01bb89b0f715')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9fd8df64-9556-4264-9689-01bb89b0f715 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9fd8df64-9556-4264-9689-01bb89b0f715');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In marketing applications, the name of the cereal plays a big role in increasing the appeal of the cereal. \n",
        "\n",
        "So let's see how much common names like \"Crunch\" and \"Bran\" are used. Now how do we do this?"
      ],
      "metadata": {
        "id": "h6cVV65Q_i0c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[df[\"name\"].str.contains(\"Crunch\")]\n",
        "\n",
        "df.loc[df[\"name\"].str.contains(\"Bran\")].reset_index() #reset_index also allows us to be more efficient when reading content. "
      ],
      "metadata": {
        "id": "tkz4sML-_6GS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "outputId": "4a1047d0-f2d6-4033-a0da-84b436f87d0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    index                       name    Manufacturer  type  calories  protein  \\\n",
              "0       0                  100% Bran         Nabisco  Cold        70        4   \n",
              "1       1          100% Natural Bran     Quaker Oats  Cold       120        3   \n",
              "2       2                   All-Bran        Kelloggs  Cold        70        4   \n",
              "3       3  All-Bran with Extra Fiber        Kelloggs  Cold        50        4   \n",
              "4       8                  Bran Chex  Ralston Purina  Cold        90        2   \n",
              "5       9                Bran Flakes            Post  Cold        90        3   \n",
              "6      19         Cracklin' Oat Bran        Kelloggs  Cold       110        3   \n",
              "7      28              Fruitful Bran        Kelloggs  Cold       120        3   \n",
              "8      52      Post Nat. Raisin Bran            Post  Cold       120        3   \n",
              "9      58                Raisin Bran        Kelloggs  Cold       120        3   \n",
              "10     59            Raisin Nut Bran   General Mills  Cold       100        3   \n",
              "11     64     Shredded Wheat 'n'Bran         Nabisco  Cold        90        3   \n",
              "12     70          Total Raisin Bran   General Mills  Cold       140        3   \n",
              "\n",
              "    fat  sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  \\\n",
              "0     1     130   10.0            5.0       6        280        25      3   \n",
              "1     5      15    2.0            8.0       8        135         0      3   \n",
              "2     1     260    9.0            7.0       5        320        25      3   \n",
              "3     0     140   14.0            8.0       0        330        25      3   \n",
              "4     1     200    4.0           15.0       6        125        25      1   \n",
              "5     0     210    5.0           13.0       5        190        25      3   \n",
              "6     3     140    4.0           10.0       7        160        25      3   \n",
              "7     0     240    5.0           14.0      12        190        25      3   \n",
              "8     1     200    6.0           11.0      14        260        25      3   \n",
              "9     1     210    5.0           14.0      12        240        25      2   \n",
              "10    2     140    2.5           10.5       8        140        25      3   \n",
              "11    0       0    4.0           19.0       0        140         0      1   \n",
              "12    1     190    4.0           15.0      14        230       100      3   \n",
              "\n",
              "    weight  cups     rating  \n",
              "0     1.00  0.33  68.402973  \n",
              "1     1.00  1.00  33.983679  \n",
              "2     1.00  0.33  59.425505  \n",
              "3     1.00  0.50  93.704912  \n",
              "4     1.00  0.67  49.120253  \n",
              "5     1.00  0.67  53.313813  \n",
              "6     1.00  0.50  40.448772  \n",
              "7     1.33  0.67  41.015492  \n",
              "8     1.33  0.67  37.840594  \n",
              "9     1.33  0.75  39.259197  \n",
              "10    1.00  0.50  39.703400  \n",
              "11    1.00  0.67  74.472949  \n",
              "12    1.50  1.00  28.592785  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0049e2c6-b3d0-40e7-8586-95fcbcf49ecf\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>100% Bran</td>\n",
              "      <td>Nabisco</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6</td>\n",
              "      <td>280</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.33</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8</td>\n",
              "      <td>Bran Chex</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>4.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>6</td>\n",
              "      <td>125</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>49.120253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>9</td>\n",
              "      <td>Bran Flakes</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>210</td>\n",
              "      <td>5.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>5</td>\n",
              "      <td>190</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>53.313813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>19</td>\n",
              "      <td>Cracklin' Oat Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>140</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7</td>\n",
              "      <td>160</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>40.448772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>28</td>\n",
              "      <td>Fruitful Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>240</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>190</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>41.015492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>52</td>\n",
              "      <td>Post Nat. Raisin Bran</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>6.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14</td>\n",
              "      <td>260</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.67</td>\n",
              "      <td>37.840594</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>58</td>\n",
              "      <td>Raisin Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>210</td>\n",
              "      <td>5.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12</td>\n",
              "      <td>240</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.259197</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>59</td>\n",
              "      <td>Raisin Nut Bran</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>140</td>\n",
              "      <td>2.5</td>\n",
              "      <td>10.5</td>\n",
              "      <td>8</td>\n",
              "      <td>140</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.50</td>\n",
              "      <td>39.703400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>64</td>\n",
              "      <td>Shredded Wheat 'n'Bran</td>\n",
              "      <td>Nabisco</td>\n",
              "      <td>Cold</td>\n",
              "      <td>90</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>19.0</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.67</td>\n",
              "      <td>74.472949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>70</td>\n",
              "      <td>Total Raisin Bran</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>140</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>190</td>\n",
              "      <td>4.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>14</td>\n",
              "      <td>230</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1.50</td>\n",
              "      <td>1.00</td>\n",
              "      <td>28.592785</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0049e2c6-b3d0-40e7-8586-95fcbcf49ecf')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0049e2c6-b3d0-40e7-8586-95fcbcf49ecf button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0049e2c6-b3d0-40e7-8586-95fcbcf49ecf');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 126
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df4 = copy.deepcopy(df) #ensuring that the orignal dataframe is not lost"
      ],
      "metadata": {
        "id": "Eoz-0XiBJCpg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "pVARlK0PPAMR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To continue with our analysis of cereals, let's now **normalise** the data. \n",
        "\n",
        "Again notice that the portion sizes of the \"cups\" are sometimes less than 1, thus making them look healthier than they are. Let's first normalise this. \n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "FhVQYjbHAf9u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for index, rows in df4.iterrows():\n",
        "  for i in range(3,14):\n",
        "    df4.iloc[index,i]=((df4.iloc[index,i])/rows[14])\n",
        "    df4.iloc[index,14]=1;"
      ],
      "metadata": {
        "id": "pHI7LEQNAw4A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "We can make the data easier on the eyes by Converting to integer and sorting them by descending order of calories\n",
        "\n"
      ],
      "metadata": {
        "id": "_lkcd67fHtFd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df4.sort_values([\"calories\"],ascending = False)\n",
        "df4"
      ],
      "metadata": {
        "id": "LLN571qBOBz0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 463
        },
        "outputId": "f1a4442a-286a-47d4-c344-cd8309f62289"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                         name    Manufacturer  type  calories  protein  fat  \\\n",
              "0                   100% Bran         Nabisco  Cold        70        4    1   \n",
              "1           100% Natural Bran     Quaker Oats  Cold       120        3    5   \n",
              "2                    All-Bran        Kelloggs  Cold        70        4    1   \n",
              "3   All-Bran with Extra Fiber        Kelloggs  Cold        50        4    0   \n",
              "4              Almond Delight  Ralston Purina  Cold       110        2    2   \n",
              "..                        ...             ...   ...       ...      ...  ...   \n",
              "72                    Triples   General Mills  Cold       110        2    1   \n",
              "73                       Trix   General Mills  Cold       110        1    1   \n",
              "74                 Wheat Chex  Ralston Purina  Cold       100        3    1   \n",
              "75                   Wheaties   General Mills  Cold       100        3    1   \n",
              "76        Wheaties Honey Gold   General Mills  Cold       110        2    1   \n",
              "\n",
              "    sodium  fiber  Carbohydrates  sugars  Potassium  vitamins  shelf  weight  \\\n",
              "0      130   10.0            5.0       6        280        25      3     1.0   \n",
              "1       15    2.0            8.0       8        135         0      3     1.0   \n",
              "2      260    9.0            7.0       5        320        25      3     1.0   \n",
              "3      140   14.0            8.0       0        330        25      3     1.0   \n",
              "4      200    1.0           14.0       8         -1        25      3     1.0   \n",
              "..     ...    ...            ...     ...        ...       ...    ...     ...   \n",
              "72     250    0.0           21.0       3         60        25      3     1.0   \n",
              "73     140    0.0           13.0      12         25        25      2     1.0   \n",
              "74     230    3.0           17.0       3        115        25      1     1.0   \n",
              "75     200    3.0           17.0       3        110        25      1     1.0   \n",
              "76     200    1.0           16.0       8         60        25      1     1.0   \n",
              "\n",
              "    cups     rating  \n",
              "0   0.33  68.402973  \n",
              "1   1.00  33.983679  \n",
              "2   0.33  59.425505  \n",
              "3   0.50  93.704912  \n",
              "4   0.75  34.384843  \n",
              "..   ...        ...  \n",
              "72  0.75  39.106174  \n",
              "73  1.00  27.753301  \n",
              "74  0.67  49.787445  \n",
              "75  1.00  51.592193  \n",
              "76  0.75  36.187559  \n",
              "\n",
              "[77 rows x 16 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e242bf3b-1a56-4a30-bf55-2aafc564f9e4\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100% Bran</td>\n",
              "      <td>Nabisco</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6</td>\n",
              "      <td>280</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Almond Delight</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>-1</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>34.384843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>Triples</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.106174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>Trix</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>27.753301</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>Wheat Chex</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>230</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>115</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.67</td>\n",
              "      <td>49.787445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>Wheaties</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>110</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>51.592193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>Wheaties Honey Gold</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>60</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.187559</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>77 rows × 16 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e242bf3b-1a56-4a30-bf55-2aafc564f9e4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e242bf3b-1a56-4a30-bf55-2aafc564f9e4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e242bf3b-1a56-4a30-bf55-2aafc564f9e4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 128
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now, to finish this off, let's classify the **unhealthiest** cereal based on brands, and calculate average calories per brand. \n",
        "\n",
        ">We do this by splitting the dataframes by brand, and then sorting them, and then proceeding to concatenate them. \n",
        "\n",
        "Once again, brands for reference: \n",
        "\n",
        "\n",
        "A = American Home Food Products\n",
        "\n",
        "G = General Mills\n",
        "\n",
        "K = Kelloggs\n",
        "\n",
        "N = Nabisco\n",
        "\n",
        "P = Post\n",
        "\n",
        "Q = Quaker Oats\n",
        "\n",
        "R = Ralston Purina\n",
        "\n"
      ],
      "metadata": {
        "id": "1MmK7ye_PK0R"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dfkel = df4.loc[df[\"Manufacturer\"]==\"Kelloggs\"]\n",
        "dfg = df4.loc[df[\"Manufacturer\"]==\"General Mills\"]\n",
        "dfa = df4.loc[df[\"Manufacturer\"]==\"American Home Food Products\"]\n",
        "dfn = df4.loc[df[\"Manufacturer\"]==\"Nabisco\"]\n",
        "dfp = df4.loc[df[\"Manufacturer\"]==\"Post\"]\n",
        "dfq = df4.loc[df[\"Manufacturer\"]==\"Quaker Oats\"]\n",
        "dfr = df4.loc[df[\"Manufacturer\"]==\"Ralston Purina\"]\n"
      ],
      "metadata": {
        "id": "RuVEt_4OP2uI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "dfkel = dfkel.loc[(dfkel[\"calories\"]== dfkel[\"calories\"].max())]\n",
        "\n",
        "\n",
        "\n",
        "dfg = dfg.loc[(dfg[\"calories\"]== dfg[\"calories\"].max())]\n",
        "dfa = dfa.loc[(dfa[\"calories\"]== dfa[\"calories\"].max())]\n",
        "dfn = dfn.loc[(dfn[\"calories\"]== dfn[\"calories\"].max())]\n",
        "dfp =dfp.loc[(dfp[\"calories\"]== dfp[\"calories\"].max())]\n",
        "dfq = dfq.loc[(dfq[\"calories\"]== dfq[\"calories\"].max())]\n",
        "dfr = dfr.loc[(dfr[\"calories\"]== dfr[\"calories\"].max())]\n",
        "\n",
        "dfnet = pd.concat([dfkel,dfg,dfa,dfn,dfp,dfq,dfr], axis=0) #new\n",
        "\n",
        "dfnet.sort_values([\"calories\"], ascending = False)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "tdMvzigmRrwN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "outputId": "e38ef4bd-a8a4-465f-b0c3-1ff1a7974ee4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 name                 Manufacturer  type  \\\n",
              "33                         Grape-Nuts                         Post  Cold   \n",
              "51               Oatmeal Raisin Crisp                General Mills  Cold   \n",
              "46               Mueslix Crispy Blend                     Kelloggs  Cold   \n",
              "0                           100% Bran                      Nabisco  Cold   \n",
              "56                 Quaker Oat Squares                  Quaker Oats  Cold   \n",
              "44   Muesli Raisins; Dates; & Almonds               Ralston Purina  Cold   \n",
              "45  Muesli Raisins; Peaches; & Pecans               Ralston Purina  Cold   \n",
              "43                              Maypo  American Home Food Products   Hot   \n",
              "\n",
              "    calories  protein  fat  sodium  fiber  Carbohydrates  sugars  Potassium  \\\n",
              "33       440       12    0     680     12             68      12        360   \n",
              "51       260        6    4     340      3             27      20        240   \n",
              "46       238        4    2     223      4             25      19        238   \n",
              "0        212       12    3     393     30             15      18        848   \n",
              "56       200        8    2     270      4             28      12        220   \n",
              "44       150        4    3      95      3             16      11        170   \n",
              "45       150        4    3     150      3             16      11        170   \n",
              "43       100        4    1       0      0             16       3         95   \n",
              "\n",
              "    vitamins  shelf  weight  cups     rating  \n",
              "33       100     12       4   1.0  53.371007  \n",
              "51        50      6       2   1.0  30.450843  \n",
              "46        37      4       2   1.0  30.313351  \n",
              "0         75      9       3   1.0  68.402973  \n",
              "56        50      6       2   1.0  49.511874  \n",
              "44        25      3       1   1.0  37.136863  \n",
              "45        25      3       1   1.0  34.139765  \n",
              "43        25      2       1   1.0  54.850917  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-df3f7e63-d767-4e59-8b75-4df57bb01f3a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>name</th>\n",
              "      <th>Manufacturer</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>Carbohydrates</th>\n",
              "      <th>sugars</th>\n",
              "      <th>Potassium</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Grape-Nuts</td>\n",
              "      <td>Post</td>\n",
              "      <td>Cold</td>\n",
              "      <td>440</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>680</td>\n",
              "      <td>12</td>\n",
              "      <td>68</td>\n",
              "      <td>12</td>\n",
              "      <td>360</td>\n",
              "      <td>100</td>\n",
              "      <td>12</td>\n",
              "      <td>4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>53.371007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>Oatmeal Raisin Crisp</td>\n",
              "      <td>General Mills</td>\n",
              "      <td>Cold</td>\n",
              "      <td>260</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>340</td>\n",
              "      <td>3</td>\n",
              "      <td>27</td>\n",
              "      <td>20</td>\n",
              "      <td>240</td>\n",
              "      <td>50</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>30.450843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Mueslix Crispy Blend</td>\n",
              "      <td>Kelloggs</td>\n",
              "      <td>Cold</td>\n",
              "      <td>238</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>223</td>\n",
              "      <td>4</td>\n",
              "      <td>25</td>\n",
              "      <td>19</td>\n",
              "      <td>238</td>\n",
              "      <td>37</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>30.313351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100% Bran</td>\n",
              "      <td>Nabisco</td>\n",
              "      <td>Cold</td>\n",
              "      <td>212</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>393</td>\n",
              "      <td>30</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>848</td>\n",
              "      <td>75</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>Quaker Oat Squares</td>\n",
              "      <td>Quaker Oats</td>\n",
              "      <td>Cold</td>\n",
              "      <td>200</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>270</td>\n",
              "      <td>4</td>\n",
              "      <td>28</td>\n",
              "      <td>12</td>\n",
              "      <td>220</td>\n",
              "      <td>50</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>49.511874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Muesli Raisins; Dates; &amp; Almonds</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>150</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>95</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "      <td>170</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>37.136863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Muesli Raisins; Peaches; &amp; Pecans</td>\n",
              "      <td>Ralston Purina</td>\n",
              "      <td>Cold</td>\n",
              "      <td>150</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>150</td>\n",
              "      <td>3</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "      <td>170</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>34.139765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>Maypo</td>\n",
              "      <td>American Home Food Products</td>\n",
              "      <td>Hot</td>\n",
              "      <td>100</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>3</td>\n",
              "      <td>95</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>54.850917</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-df3f7e63-d767-4e59-8b75-4df57bb01f3a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-df3f7e63-d767-4e59-8b75-4df57bb01f3a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-df3f7e63-d767-4e59-8b75-4df57bb01f3a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 129
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally let's check the average amount of sugar and calories every manufacturer adds to their Cereals. "
      ],
      "metadata": {
        "id": "IOR4pMKXUxzM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Kelloggs:\",dfkel.iloc[:,3].mean())\n",
        "\n",
        "print(\"\\nAmerican Home Food Products: \\t\",dfa.iloc[:,3].mean(),\"\\n\\nNabisco: \\t\",dfn.iloc[:,3].mean(),\"\\n\\nPost: \\t\",dfp.iloc[:,3].mean(),\"\\n\\nQuaker: \\t\",dfq.iloc[:,3].mean(),\"\\n\\nRalston Purina: \\t\",dfr.iloc[:,3].mean())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fUS65ycfU4bc",
        "outputId": "42048e1a-436b-48a6-986f-4d8e5d4348a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Kelloggs: 108.69565217391305\n",
            "\n",
            "American Home Food Products: \t 100.0 \n",
            "\n",
            "Nabisco: \t 86.66666666666667 \n",
            "\n",
            "Post: \t 108.88888888888889 \n",
            "\n",
            "Quaker: \t 95.0 \n",
            "\n",
            "Ralston Purina: \t 115.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To end this analysis, let's store all of what we've done in a CSV file."
      ],
      "metadata": {
        "id": "amWaul8laOAg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dfnet.to_csv('modified.csv',index= True)"
      ],
      "metadata": {
        "id": "QEZUjB7xaVJd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "oaWUY7YBappO"
      }
    }
  ]
}