zomato_data_analytics_project.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOGrx1A2JVqD63xEyEE+v+5",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/aniketakumari/Zomato-Data-Analysis/blob/main/zomato_data_analytics_project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "4-c7F3gKMzkY"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe = pd.read_csv(\"Zomato data .csv\")\n",
        "print(dataframe.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TrP8RuQ2dMa2",
        "outputId": "13696122-05d5-467d-804c-99c8094a615a"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                    name online_order book_table   rate  votes  \\\n",
            "0                  Jalsa          Yes        Yes  4.1/5    775   \n",
            "1         Spice Elephant          Yes         No  4.1/5    787   \n",
            "2        San Churro Cafe          Yes         No  3.8/5    918   \n",
            "3  Addhuri Udupi Bhojana           No         No  3.7/5     88   \n",
            "4          Grand Village           No         No  3.8/5    166   \n",
            "\n",
            "   approx_cost(for two people) listed_in(type)  \n",
            "0                          800          Buffet  \n",
            "1                          800          Buffet  \n",
            "2                          800          Buffet  \n",
            "3                          300          Buffet  \n",
            "4                          600          Buffet  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe = pd.read_csv(\"Zomato data .csv\")\n",
        "print(dataframe)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hqZOArCDdh-Y",
        "outputId": "08cf35ac-ceb0-4b2a-b9bd-4a6e6d7247c0"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                      name online_order book_table   rate  votes  \\\n",
            "0                    Jalsa          Yes        Yes  4.1/5    775   \n",
            "1           Spice Elephant          Yes         No  4.1/5    787   \n",
            "2          San Churro Cafe          Yes         No  3.8/5    918   \n",
            "3    Addhuri Udupi Bhojana           No         No  3.7/5     88   \n",
            "4            Grand Village           No         No  3.8/5    166   \n",
            "..                     ...          ...        ...    ...    ...   \n",
            "143       Melting Melodies           No         No  3.3/5      0   \n",
            "144        New Indraprasta           No         No  3.3/5      0   \n",
            "145           Anna Kuteera          Yes         No  4.0/5    771   \n",
            "146                 Darbar           No         No  3.0/5     98   \n",
            "147          Vijayalakshmi          Yes         No  3.9/5     47   \n",
            "\n",
            "     approx_cost(for two people) listed_in(type)  \n",
            "0                            800          Buffet  \n",
            "1                            800          Buffet  \n",
            "2                            800          Buffet  \n",
            "3                            300          Buffet  \n",
            "4                            600          Buffet  \n",
            "..                           ...             ...  \n",
            "143                          100          Dining  \n",
            "144                          150          Dining  \n",
            "145                          450          Dining  \n",
            "146                          800          Dining  \n",
            "147                          200          Dining  \n",
            "\n",
            "[148 rows x 7 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **1**. **Converting the data type of the \"rate\" column to float**"
      ],
      "metadata": {
        "id": "aX6ZFAsVdzj4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **2**. **Remove the denominator.**"
      ],
      "metadata": {
        "id": "42I0SJr9ed0n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def handleRate(value) :\n",
        "  value = str(value).split(\"/\")\n",
        "  value = value[0]\n",
        "  return float(value)\n",
        "\n",
        "dataframe[\"rate\"] = dataframe[\"rate\"].apply(handleRate)\n",
        "print(dataframe.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ktzFZd2ceVNt",
        "outputId": "a87b7bac-6eb9-4083-b733-8e6cce9bcb58"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                    name online_order book_table  rate  votes  \\\n",
            "0                  Jalsa          Yes        Yes   4.1    775   \n",
            "1         Spice Elephant          Yes         No   4.1    787   \n",
            "2        San Churro Cafe          Yes         No   3.8    918   \n",
            "3  Addhuri Udupi Bhojana           No         No   3.7     88   \n",
            "4          Grand Village           No         No   3.8    166   \n",
            "\n",
            "   approx_cost(for two people) listed_in(type)  \n",
            "0                          800          Buffet  \n",
            "1                          800          Buffet  \n",
            "2                          800          Buffet  \n",
            "3                          300          Buffet  \n",
            "4                          600          Buffet  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **3**. **Summary of Dataframe.**"
      ],
      "metadata": {
        "id": "SkNvQMypfO6_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EJCPFJxJfWsg",
        "outputId": "d698bd2e-619f-434f-bff4-1f9a40e24c36"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 148 entries, 0 to 147\n",
            "Data columns (total 7 columns):\n",
            " #   Column                       Non-Null Count  Dtype  \n",
            "---  ------                       --------------  -----  \n",
            " 0   name                         148 non-null    object \n",
            " 1   online_order                 148 non-null    object \n",
            " 2   book_table                   148 non-null    object \n",
            " 3   rate                         148 non-null    float64\n",
            " 4   votes                        148 non-null    int64  \n",
            " 5   approx_cost(for two people)  148 non-null    int64  \n",
            " 6   listed_in(type)              148 non-null    object \n",
            "dtypes: float64(1), int64(2), object(4)\n",
            "memory usage: 8.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Conclusion from the above dataframe info summary that there is no null values in the data frame.**"
      ],
      "metadata": {
        "id": "U_k8VRhsfb-b"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Queries and Exploratory Data Analysis on the modified dataframe.**"
      ],
      "metadata": {
        "id": "ItFh4sBhf4He"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 1**. Type of restaurant majority of customers order food from."
      ],
      "metadata": {
        "id": "-BMVFHwkgUk_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x=dataframe[\"listed_in(type)\"])\n",
        "plt.xlabel(\"Type of Restaurant\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "O2LYamPIgPmI",
        "outputId": "e5166e8e-f057-4881-93d9-dfef0202b339"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Type of Restaurant')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : Most orders from Dining Category."
      ],
      "metadata": {
        "id": "xUc_YTM8g9Mo"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 2**. Votes each type of restaurant from the customers."
      ],
      "metadata": {
        "id": "TI-Gk1IDjXRu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "grouped_data = dataframe.groupby(\"listed_in(type)\")[\"votes\"].sum()\n",
        "result = pd.DataFrame({\"votes\" : grouped_data})\n",
        "\n",
        "plt.plot(result, c=\"green\", marker=\"o\")\n",
        "plt.xlabel(\"Type of Restaurant\", c=\"red\", size=20)\n",
        "plt.ylabel(\"Votes\", c=\"red\", size=20)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 463
        },
        "id": "ywyhItuElgHk",
        "outputId": "5a75b49d-f875-4b43-9d15-e2cb16e17920"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : Highest voting to Dining category restaurants."
      ],
      "metadata": {
        "id": "Nl-zLR4PkiXy"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 3**. The rating of the majority of the restaurants has been received."
      ],
      "metadata": {
        "id": "3g_TdtS8i_VE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.hist(dataframe[\"rate\"], bins=5)\n",
        "plt.title(\"Rating Distribution\")\n",
        "plt.xlabel(\"Rating\")\n",
        "plt.ylabel(\"Frequency\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "m0ZqEjysmn7n",
        "outputId": "174922b9-ee48-45df-c565-0032a042600e"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : The majority of restaurants received ratings in the range of 4 to 4.25."
      ],
      "metadata": {
        "id": "fTvZRzi2kiwY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 4**. The average spending of the couples on each other who order food online for their partner."
      ],
      "metadata": {
        "id": "znSXVZecj_iN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "couple_data = dataframe[\"approx_cost(for two people)\"][dataframe[\"online_order\"] == \"Yes\"]\n",
        "sns.countplot(x=couple_data)\n",
        "plt.xlabel(\"Average Spending By The Couples\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "OXaRHWG6vHIr",
        "outputId": "364dff08-34e6-41f5-d81f-7b5fbf90dc71"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Average Spending By The Couples')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : Couples are spending from range 500 to 600 rupees on their partner on online food ordering."
      ],
      "metadata": {
        "id": "snUzhcffkmEr"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 5**. Which mode [Offline or Online] received the maximum rating."
      ],
      "metadata": {
        "id": "wFVWIsqXkpqo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(6, 6))\n",
        "sns.boxplot(y=\"rate\", x=\"online_order\", data=dataframe)\n",
        "plt.ylabel(\"Rating\")\n",
        "plt.xlabel(\"Online Ordering\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "kmsd9NGGwBVP",
        "outputId": "5a22cb74-6a2d-46e2-8f71-7d3dfe3f1fed"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : Offline food ordering has received lower rating as compared to online which has received excellent rating."
      ],
      "metadata": {
        "id": "Er3NZVfZks_Q"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Query 6**. Which type of restaurant received the most no. of offline orders, so that zomato can provide those customers with good offers."
      ],
      "metadata": {
        "id": "Y_TtWcxbkrJi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pivot_table = dataframe.pivot_table(index=\"listed_in(type)\", columns=\"online_order\", values=\"name\", aggfunc=\"count\")\n",
        "#pivot_table.plot(kind=\"bar\", stacked=True)\n",
        "sns.heatmap(pivot_table, annot=True, cmap=\"YlGnBu\", fmt=\"d\")\n",
        "plt.title(\"Heatmap\")\n",
        "plt.xlabel(\"Online Orders\")\n",
        "plt.ylabel(\"Type of Restaurants\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "AR6IBRp3xBCy",
        "outputId": "29eb3046-dbd3-47ae-f238-ba95bd334ac8"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Conclusion** : We concluded that dining restaurant accept offline orders whereas cafes primarily received online orders."
      ],
      "metadata": {
        "id": "EKuz9JLVks2u"
      }
    }
  ]
}