Google_Play_Store_EDA.ipynb

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        "<a href=\"https://colab.research.google.com/github/Harpreetk01/Google_Play_Store_EDA/blob/main/Google_Play_Store_EDA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "execution_count": 1,
      "metadata": {
        "id": "G6kPtzYtRe6w"
      },
      "outputs": [],
      "source": [
        "from google.colab import drive"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "oCDwrI8eTRBe",
        "outputId": "be4b1777-ca83-411a-d6bf-6da48eb5a29f"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "3kvyJr8qTQ9w"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"/content/drive/MyDrive/DA Datasets/googleplaystore.csv\")"
      ],
      "metadata": {
        "id": "UW7hXE0sTQ6F"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
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      "source": [
        "df.head()"
      ],
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        "id": "Cn83GnkLTQ2s",
        "outputId": "5e584dac-d497-4e22-ea5b-baf6cfaac67d"
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              "                                                 App        Category  Rating  \\\n",
              "0     Photo Editor & Candy Camera & Grid & ScrapBook  ART_AND_DESIGN     4.1   \n",
              "1                                Coloring book moana  ART_AND_DESIGN     3.9   \n",
              "2  U Launcher Lite – FREE Live Cool Themes, Hide ...  ART_AND_DESIGN     4.7   \n",
              "3                              Sketch - Draw & Paint  ART_AND_DESIGN     4.5   \n",
              "4              Pixel Draw - Number Art Coloring Book  ART_AND_DESIGN     4.3   \n",
              "\n",
              "  Reviews  Size     Installs  Type Price Content Rating  \\\n",
              "0     159   19M      10,000+  Free     0       Everyone   \n",
              "1     967   14M     500,000+  Free     0       Everyone   \n",
              "2   87510  8.7M   5,000,000+  Free     0       Everyone   \n",
              "3  215644   25M  50,000,000+  Free     0           Teen   \n",
              "4     967  2.8M     100,000+  Free     0       Everyone   \n",
              "\n",
              "                      Genres      Last Updated         Current Ver  \\\n",
              "0               Art & Design   January 7, 2018               1.0.0   \n",
              "1  Art & Design;Pretend Play  January 15, 2018               2.0.0   \n",
              "2               Art & Design    August 1, 2018               1.2.4   \n",
              "3               Art & Design      June 8, 2018  Varies with device   \n",
              "4    Art & Design;Creativity     June 20, 2018                 1.1   \n",
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              "      <td>U Launcher Lite – FREE Live Cool Themes, Hide ...</td>\n",
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              "      <th>4</th>\n",
              "      <td>Pixel Draw - Number Art Coloring Book</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.3</td>\n",
              "      <td>967</td>\n",
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              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design;Creativity</td>\n",
              "      <td>June 20, 2018</td>\n",
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              "                                                 App             Category  \\\n",
              "10836                               Sya9a Maroc - FR               FAMILY   \n",
              "10837               Fr. Mike Schmitz Audio Teachings               FAMILY   \n",
              "10838                         Parkinson Exercices FR              MEDICAL   \n",
              "10839                  The SCP Foundation DB fr nn5n  BOOKS_AND_REFERENCE   \n",
              "10840  iHoroscope - 2018 Daily Horoscope & Astrology            LIFESTYLE   \n",
              "\n",
              "       Rating Reviews                Size     Installs  Type Price  \\\n",
              "10836     4.5      38                 53M       5,000+  Free     0   \n",
              "10837     5.0       4                3.6M         100+  Free     0   \n",
              "10838     NaN       3                9.5M       1,000+  Free     0   \n",
              "10839     4.5     114  Varies with device       1,000+  Free     0   \n",
              "10840     4.5  398307                 19M  10,000,000+  Free     0   \n",
              "\n",
              "      Content Rating             Genres      Last Updated         Current Ver  \\\n",
              "10836       Everyone          Education     July 25, 2017                1.48   \n",
              "10837       Everyone          Education      July 6, 2018                 1.0   \n",
              "10838       Everyone            Medical  January 20, 2017                 1.0   \n",
              "10839     Mature 17+  Books & Reference  January 19, 2015  Varies with device   \n",
              "10840       Everyone          Lifestyle     July 25, 2018  Varies with device   \n",
              "\n",
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              "10836          4.1 and up  \n",
              "10837          4.1 and up  \n",
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              "      <td>The SCP Foundation DB fr nn5n</td>\n",
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              "      <td>4.5</td>\n",
              "      <td>114</td>\n",
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              "      <td>1,000+</td>\n",
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              "      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-d8bfce98-d834-43d9-9795-2f4ddd609368 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-d8bfce98-d834-43d9-9795-2f4ddd609368');\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": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Data Preparation and Cleaning**\n",
        "\n",
        "1. Look at some infromation about the data & the columns\n",
        "2. Fix any missing or incorrect values"
      ],
      "metadata": {
        "id": "9_rlg_4ZT8My"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sscm6fGPTQv5",
        "outputId": "18fef0d6-5ca8-4745-a0b0-f028ecf79553"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10841, 13)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wmkFNFOhTQse",
        "outputId": "2a38d90f-afd0-44eb-b68a-cd940c889ba5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type',\n",
              "       'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver',\n",
              "       'Android Ver'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df.columns)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_hoe8BnsTQoz",
        "outputId": "fa142dce-5288-441f-ef30-10615339238e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CO27-_dYTQlK",
        "outputId": "628f10ad-8315-457a-b301-cc225690668f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 10841 entries, 0 to 10840\n",
            "Data columns (total 13 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   App             10841 non-null  object \n",
            " 1   Category        10841 non-null  object \n",
            " 2   Rating          9367 non-null   float64\n",
            " 3   Reviews         10841 non-null  object \n",
            " 4   Size            10841 non-null  object \n",
            " 5   Installs        10841 non-null  object \n",
            " 6   Type            10840 non-null  object \n",
            " 7   Price           10841 non-null  object \n",
            " 8   Content Rating  10840 non-null  object \n",
            " 9   Genres          10841 non-null  object \n",
            " 10  Last Updated    10841 non-null  object \n",
            " 11  Current Ver     10833 non-null  object \n",
            " 12  Android Ver     10838 non-null  object \n",
            "dtypes: float64(1), object(12)\n",
            "memory usage: 1.1+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Finding Missing Values and Cleaning Data**"
      ],
      "metadata": {
        "id": "Rl8qQ441UVLn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.isnull().sum().sort_values(ascending = False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QMQ83wc4TQhY",
        "outputId": "4644c267-2a42-43cb-c384-9af4bef7ef80"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Rating            1474\n",
              "Current Ver          8\n",
              "Android Ver          3\n",
              "Type                 1\n",
              "Content Rating       1\n",
              "App                  0\n",
              "Category             0\n",
              "Reviews              0\n",
              "Size                 0\n",
              "Installs             0\n",
              "Price                0\n",
              "Genres               0\n",
              "Last Updated         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(df.isnull(), yticklabels = False, cmap = 'Oranges_r')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "pH8DhNz_TQdr",
        "outputId": "6da56365-3207-4188-9a28-8a006517559d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " - Maximum null values is present in the Rating column\n",
        " - And, other data has very less null values, so we can leave it or remove it from data, it doesn't affect the any column or \n",
        "   data at all"
      ],
      "metadata": {
        "id": "UporjTdxUkiH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Droping not usefull columns\n",
        "df = df.drop(['Android Ver', 'Current Ver', 'Last Updated','Size'], axis = 1)"
      ],
      "metadata": {
        "id": "blMtshfhTQZt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "LXB4LwraTQWB",
        "outputId": "a5f4227f-780d-4dbf-d508-941cf46ce539"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 App        Category  Rating  \\\n",
              "0     Photo Editor & Candy Camera & Grid & ScrapBook  ART_AND_DESIGN     4.1   \n",
              "1                                Coloring book moana  ART_AND_DESIGN     3.9   \n",
              "2  U Launcher Lite – FREE Live Cool Themes, Hide ...  ART_AND_DESIGN     4.7   \n",
              "3                              Sketch - Draw & Paint  ART_AND_DESIGN     4.5   \n",
              "4              Pixel Draw - Number Art Coloring Book  ART_AND_DESIGN     4.3   \n",
              "\n",
              "  Reviews     Installs  Type Price Content Rating                     Genres  \n",
              "0     159      10,000+  Free     0       Everyone               Art & Design  \n",
              "1     967     500,000+  Free     0       Everyone  Art & Design;Pretend Play  \n",
              "2   87510   5,000,000+  Free     0       Everyone               Art & Design  \n",
              "3  215644  50,000,000+  Free     0           Teen               Art & Design  \n",
              "4     967     100,000+  Free     0       Everyone    Art & Design;Creativity  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-12495a8c-214d-48a0-9e80-803d06f311d1\">\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>App</th>\n",
              "      <th>Category</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Reviews</th>\n",
              "      <th>Installs</th>\n",
              "      <th>Type</th>\n",
              "      <th>Price</th>\n",
              "      <th>Content Rating</th>\n",
              "      <th>Genres</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Photo Editor &amp; Candy Camera &amp; Grid &amp; ScrapBook</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.1</td>\n",
              "      <td>159</td>\n",
              "      <td>10,000+</td>\n",
              "      <td>Free</td>\n",
              "      <td>0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Coloring book moana</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>3.9</td>\n",
              "      <td>967</td>\n",
              "      <td>500,000+</td>\n",
              "      <td>Free</td>\n",
              "      <td>0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design;Pretend Play</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>U Launcher Lite – FREE Live Cool Themes, Hide ...</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.7</td>\n",
              "      <td>87510</td>\n",
              "      <td>5,000,000+</td>\n",
              "      <td>Free</td>\n",
              "      <td>0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Sketch - Draw &amp; Paint</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>215644</td>\n",
              "      <td>50,000,000+</td>\n",
              "      <td>Free</td>\n",
              "      <td>0</td>\n",
              "      <td>Teen</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Pixel Draw - Number Art Coloring Book</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.3</td>\n",
              "      <td>967</td>\n",
              "      <td>100,000+</td>\n",
              "      <td>Free</td>\n",
              "      <td>0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design;Creativity</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-12495a8c-214d-48a0-9e80-803d06f311d1')\"\n",
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              "  </svg>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-12495a8c-214d-48a0-9e80-803d06f311d1');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Rating'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cTuNUK9eTQPH",
        "outputId": "5e047ccd-62bd-416d-f027-11749065ec2d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 4.1,  3.9,  4.7,  4.5,  4.3,  4.4,  3.8,  4.2,  4.6,  3.2,  4. ,\n",
              "        nan,  4.8,  4.9,  3.6,  3.7,  3.3,  3.4,  3.5,  3.1,  5. ,  2.6,\n",
              "        3. ,  1.9,  2.5,  2.8,  2.7,  1. ,  2.9,  2.3,  2.2,  1.7,  2. ,\n",
              "        1.8,  2.4,  1.6,  2.1,  1.4,  1.5,  1.2, 19. ])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Filling Rating Column with Mean Value**"
      ],
      "metadata": {
        "id": "lUoJbcmVVmc4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Rating'].fillna(df['Rating'].mean(), inplace = True)"
      ],
      "metadata": {
        "id": "fEEXFcDvTQLy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Rating'].isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dWxcTpjPTQHn",
        "outputId": "ea1368f9-7706-4523-8dcd-488668bee96c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Cleaning Installs Columns**"
      ],
      "metadata": {
        "id": "gIOA2LWNabEq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Installs'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YP741YE5TQEZ",
        "outputId": "fefb7e1e-0b33-4041-b05b-95844b54554f"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['10,000+', '500,000+', '5,000,000+', '50,000,000+', '100,000+',\n",
              "       '50,000+', '1,000,000+', '10,000,000+', '5,000+', '100,000,000+',\n",
              "       '1,000,000,000+', '1,000+', '500,000,000+', '50+', '100+', '500+',\n",
              "       '10+', '1+', '5+', '0+', '0', 'Free'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Removing '+' sign \n",
        "#Removing commas ','\n",
        "#Changing datatype\n",
        "#Replace \"Free\" and'Zero\n",
        "df['Installs'] = df['Installs'].apply(lambda x: x.strip('+'))\n",
        "df['Installs'] = df['Installs'].apply(lambda x: x.replace(',', ''))\n",
        "df['Installs'] = df['Installs'].replace(\"Free\", '0')\n",
        "df['Installs']=df['Installs'].astype('int')"
      ],
      "metadata": {
        "id": "DiOfYzonTQAP"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Installs'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sHwMUlKqTP8j",
        "outputId": "81ebd09d-252f-4e01-b91a-d415c180687d"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([     10000,     500000,    5000000,   50000000,     100000,\n",
              "            50000,    1000000,   10000000,       5000,  100000000,\n",
              "       1000000000,       1000,  500000000,         50,        100,\n",
              "              500,         10,          1,          5,          0])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "id": "h33CvgDETP4c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7399f9c1-2d7e-4e1c-8756-e8cfb45198c2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 10841 entries, 0 to 10840\n",
            "Data columns (total 9 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   App             10841 non-null  object \n",
            " 1   Category        10841 non-null  object \n",
            " 2   Rating          10841 non-null  float64\n",
            " 3   Reviews         10841 non-null  object \n",
            " 4   Installs        10841 non-null  int64  \n",
            " 5   Type            10840 non-null  object \n",
            " 6   Price           10841 non-null  object \n",
            " 7   Content Rating  10840 non-null  object \n",
            " 8   Genres          10841 non-null  object \n",
            "dtypes: float64(1), int64(1), object(7)\n",
            "memory usage: 762.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Cleaning Price Columns**"
      ],
      "metadata": {
        "id": "p52GvJnMaiQA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['Price'].unique()"
      ],
      "metadata": {
        "id": "8oXDX2bvTP0z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "94ba5418-f675-4c06-e0d7-eee5b2f29c84"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['0', '$4.99', '$3.99', '$6.99', '$1.49', '$2.99', '$7.99', '$5.99',\n",
              "       '$3.49', '$1.99', '$9.99', '$7.49', '$0.99', '$9.00', '$5.49',\n",
              "       '$10.00', '$24.99', '$11.99', '$79.99', '$16.99', '$14.99',\n",
              "       '$1.00', '$29.99', '$12.99', '$2.49', '$10.99', '$1.50', '$19.99',\n",
              "       '$15.99', '$33.99', '$74.99', '$39.99', '$3.95', '$4.49', '$1.70',\n",
              "       '$8.99', '$2.00', '$3.88', '$25.99', '$399.99', '$17.99',\n",
              "       '$400.00', '$3.02', '$1.76', '$4.84', '$4.77', '$1.61', '$2.50',\n",
              "       '$1.59', '$6.49', '$1.29', '$5.00', '$13.99', '$299.99', '$379.99',\n",
              "       '$37.99', '$18.99', '$389.99', '$19.90', '$8.49', '$1.75',\n",
              "       '$14.00', '$4.85', '$46.99', '$109.99', '$154.99', '$3.08',\n",
              "       '$2.59', '$4.80', '$1.96', '$19.40', '$3.90', '$4.59', '$15.46',\n",
              "       '$3.04', '$4.29', '$2.60', '$3.28', '$4.60', '$28.99', '$2.95',\n",
              "       '$2.90', '$1.97', '$200.00', '$89.99', '$2.56', '$30.99', '$3.61',\n",
              "       '$394.99', '$1.26', 'Everyone', '$1.20', '$1.04'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Remove dollar\"$\" sign\n",
        "#Rplacing 'Everyone' word with '0'\n",
        "#Converting 'String' datatype into 'float'\n",
        "df['Price'] = df['Price'].apply(lambda x : x.strip(\"$\"))\n",
        "df['Price'] = df['Price'].str.replace(\"Everyone\", '0')\n",
        "df['Price'] = df['Price'].astype('float')"
      ],
      "metadata": {
        "id": "j2XHMKV9TPxV"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Price'].unique()"
      ],
      "metadata": {
        "id": "fE9kWB5uTPt8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb81bd81-6886-4bca-b8f0-74b83ddb64db"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  0.  ,   4.99,   3.99,   6.99,   1.49,   2.99,   7.99,   5.99,\n",
              "         3.49,   1.99,   9.99,   7.49,   0.99,   9.  ,   5.49,  10.  ,\n",
              "        24.99,  11.99,  79.99,  16.99,  14.99,   1.  ,  29.99,  12.99,\n",
              "         2.49,  10.99,   1.5 ,  19.99,  15.99,  33.99,  74.99,  39.99,\n",
              "         3.95,   4.49,   1.7 ,   8.99,   2.  ,   3.88,  25.99, 399.99,\n",
              "        17.99, 400.  ,   3.02,   1.76,   4.84,   4.77,   1.61,   2.5 ,\n",
              "         1.59,   6.49,   1.29,   5.  ,  13.99, 299.99, 379.99,  37.99,\n",
              "        18.99, 389.99,  19.9 ,   8.49,   1.75,  14.  ,   4.85,  46.99,\n",
              "       109.99, 154.99,   3.08,   2.59,   4.8 ,   1.96,  19.4 ,   3.9 ,\n",
              "         4.59,  15.46,   3.04,   4.29,   2.6 ,   3.28,   4.6 ,  28.99,\n",
              "         2.95,   2.9 ,   1.97, 200.  ,  89.99,   2.56,  30.99,   3.61,\n",
              "       394.99,   1.26,   1.2 ,   1.04])"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Dropping Null Values**"
      ],
      "metadata": {
        "id": "SwYRHtHfa_hX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.dropna(inplace = True)\n",
        "df.head(8)"
      ],
      "metadata": {
        "id": "JfvRpjVdTPoB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "ee271b8d-ca91-467b-d729-34165de90e18"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 App        Category  Rating  \\\n",
              "0     Photo Editor & Candy Camera & Grid & ScrapBook  ART_AND_DESIGN     4.1   \n",
              "1                                Coloring book moana  ART_AND_DESIGN     3.9   \n",
              "2  U Launcher Lite – FREE Live Cool Themes, Hide ...  ART_AND_DESIGN     4.7   \n",
              "3                              Sketch - Draw & Paint  ART_AND_DESIGN     4.5   \n",
              "4              Pixel Draw - Number Art Coloring Book  ART_AND_DESIGN     4.3   \n",
              "5                         Paper flowers instructions  ART_AND_DESIGN     4.4   \n",
              "6            Smoke Effect Photo Maker - Smoke Editor  ART_AND_DESIGN     3.8   \n",
              "7                                   Infinite Painter  ART_AND_DESIGN     4.1   \n",
              "\n",
              "  Reviews  Installs  Type  Price Content Rating                     Genres  \n",
              "0     159     10000  Free    0.0       Everyone               Art & Design  \n",
              "1     967    500000  Free    0.0       Everyone  Art & Design;Pretend Play  \n",
              "2   87510   5000000  Free    0.0       Everyone               Art & Design  \n",
              "3  215644  50000000  Free    0.0           Teen               Art & Design  \n",
              "4     967    100000  Free    0.0       Everyone    Art & Design;Creativity  \n",
              "5     167     50000  Free    0.0       Everyone               Art & Design  \n",
              "6     178     50000  Free    0.0       Everyone               Art & Design  \n",
              "7   36815   1000000  Free    0.0       Everyone               Art & Design  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6e243fe0-9332-4b2d-8449-e325690ae9fc\">\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>App</th>\n",
              "      <th>Category</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Reviews</th>\n",
              "      <th>Installs</th>\n",
              "      <th>Type</th>\n",
              "      <th>Price</th>\n",
              "      <th>Content Rating</th>\n",
              "      <th>Genres</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Photo Editor &amp; Candy Camera &amp; Grid &amp; ScrapBook</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.1</td>\n",
              "      <td>159</td>\n",
              "      <td>10000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Coloring book moana</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>3.9</td>\n",
              "      <td>967</td>\n",
              "      <td>500000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design;Pretend Play</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>U Launcher Lite – FREE Live Cool Themes, Hide ...</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.7</td>\n",
              "      <td>87510</td>\n",
              "      <td>5000000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Sketch - Draw &amp; Paint</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.5</td>\n",
              "      <td>215644</td>\n",
              "      <td>50000000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Teen</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Pixel Draw - Number Art Coloring Book</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.3</td>\n",
              "      <td>967</td>\n",
              "      <td>100000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design;Creativity</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Paper flowers instructions</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.4</td>\n",
              "      <td>167</td>\n",
              "      <td>50000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Smoke Effect Photo Maker - Smoke Editor</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>3.8</td>\n",
              "      <td>178</td>\n",
              "      <td>50000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Infinite Painter</td>\n",
              "      <td>ART_AND_DESIGN</td>\n",
              "      <td>4.1</td>\n",
              "      <td>36815</td>\n",
              "      <td>1000000</td>\n",
              "      <td>Free</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Art &amp; Design</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6e243fe0-9332-4b2d-8449-e325690ae9fc')\"\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-6e243fe0-9332-4b2d-8449-e325690ae9fc 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-6e243fe0-9332-4b2d-8449-e325690ae9fc');\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": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PBPGdNCLfECJ",
        "outputId": "e866d03d-6880-4f6b-c473-075cf99b3ed9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 10354 entries, 0 to 10840\n",
            "Data columns (total 9 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   App             10354 non-null  object \n",
            " 1   Category        10354 non-null  object \n",
            " 2   Rating          10354 non-null  float64\n",
            " 3   Reviews         10354 non-null  object \n",
            " 4   Installs        10354 non-null  int64  \n",
            " 5   Type            10354 non-null  object \n",
            " 6   Price           10354 non-null  float64\n",
            " 7   Content Rating  10354 non-null  object \n",
            " 8   Genres          10354 non-null  object \n",
            "dtypes: float64(2), int64(1), object(6)\n",
            "memory usage: 808.9+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Dropping duplicate values**"
      ],
      "metadata": {
        "id": "6vhRwNTNbKz7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.duplicated().sum()"
      ],
      "metadata": {
        "id": "lGhnn1HITPkS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "04ee3f93-1b60-4855-e843-8f89c8ed72a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "485"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "id": "01YUQ9jPTPhU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "13c0185b-75ea-4fca-8f71-81f1bf8005cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10839, 9)"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#After removing the duplicate values\n",
        "df.drop_duplicates(inplace = True)\n",
        "df.shape"
      ],
      "metadata": {
        "id": "0Cwb4eZdTPdH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "08c9a119-ac7b-4e44-eee7-be43adec3bfe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10354, 9)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Rest of the columns donot have any null values, jumping to the visualisation**"
      ],
      "metadata": {
        "id": "r1Rc--XGe9U5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Visualisation**"
      ],
      "metadata": {
        "id": "V0G1P8Fxfc1n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.countplot(data = df, x = 'Category')\n",
        "plt.xlabel('Category', fontsize = 14)\n",
        "plt.ylabel('Count', fontsize = 14)\n",
        "plt.title('Category Wise Counts', fontsize = 15)\n",
        "plt.xticks(rotation = 90)\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "XG55JxdITPZM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "outputId": "f9cadb7f-cdbc-4acf-9b1a-a02ed3fadbb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- Family, Game, Business, productivity and personalization this are the few app category has higher value count \n",
        "- That means this few apps has higher download rate and most liked apps"
      ],
      "metadata": {
        "id": "LFNJ_EkdfowD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Highest Rating App**"
      ],
      "metadata": {
        "id": "KypzmO9ri9r9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['App']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B2owsFr0gGER",
        "outputId": "bbf973a8-8700-40e4-ae33-03c7aeb01955"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           Photo Editor & Candy Camera & Grid & ScrapBook\n",
              "1                                      Coloring book moana\n",
              "2        U Launcher Lite – FREE Live Cool Themes, Hide ...\n",
              "3                                    Sketch - Draw & Paint\n",
              "4                    Pixel Draw - Number Art Coloring Book\n",
              "                               ...                        \n",
              "10836                                     Sya9a Maroc - FR\n",
              "10837                     Fr. Mike Schmitz Audio Teachings\n",
              "10838                               Parkinson Exercices FR\n",
              "10839                        The SCP Foundation DB fr nn5n\n",
              "10840        iHoroscope - 2018 Daily Horoscope & Astrology\n",
              "Name: App, Length: 10354, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "App = df['App'].value_counts()\n",
        "App"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ftRhwt8GgGAd",
        "outputId": "c5d7ec95-a385-4900-8ed1-9cdfbb67c3a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ROBLOX                                           9\n",
              "8 Ball Pool                                      7\n",
              "Zombie Catchers                                  6\n",
              "Helix Jump                                       6\n",
              "Bubble Shooter                                   6\n",
              "                                                ..\n",
              "PixelLab - Text on pictures                      1\n",
              "P Launcher for Android™ 9.0                      1\n",
              "Pacify (Android P theme) - Theme for Xperia™     1\n",
              "Volume Slider Like Android P Volume Control      1\n",
              "iHoroscope - 2018 Daily Horoscope & Astrology    1\n",
              "Name: App, Length: 9658, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#App smaller than 5\n",
        "App_lessthan5 = App[App < 5]\n",
        "App_lessthan5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XpI8QODrgF9i",
        "outputId": "2bb8d674-54ea-4ce6-c875-c1f91fa6be86"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Angry Birds Rio                                  4\n",
              "Yahoo Fantasy Sports - #1 Rated Fantasy App      4\n",
              "Clash Royale                                     4\n",
              "Pou                                              4\n",
              "PUBG MOBILE                                      4\n",
              "                                                ..\n",
              "PixelLab - Text on pictures                      1\n",
              "P Launcher for Android™ 9.0                      1\n",
              "Pacify (Android P theme) - Theme for Xperia™     1\n",
              "Volume Slider Like Android P Volume Control      1\n",
              "iHoroscope - 2018 Daily Horoscope & Astrology    1\n",
              "Name: App, Length: 9643, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def handelApp (values):\n",
        "  if values in App_lessthan5:\n",
        "    return 'others'\n",
        "  else:\n",
        "    return values\n",
        "df['App'] = df['App'].apply(handelApp)\n",
        "df['App'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lF1zfJeehE3o",
        "outputId": "fb497730-6627-4142-9029-fc2e51781839"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "others                            10270\n",
              "ROBLOX                                9\n",
              "8 Ball Pool                           7\n",
              "Bubble Shooter                        6\n",
              "Helix Jump                            6\n",
              "Zombie Catchers                       6\n",
              "Duolingo: Learn Languages Free        5\n",
              "Subway Surfers                        5\n",
              "Candy Crush Saga                      5\n",
              "slither.io                            5\n",
              "Temple Run 2                          5\n",
              "Granny                                5\n",
              "Angry Birds Classic                   5\n",
              "Zombie Tsunami                        5\n",
              "Farm Heroes Saga                      5\n",
              "Bowmasters                            5\n",
              "Name: App, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (15,8))\n",
        "sns.lineplot(x = df['App'], y = df['Rating']) \n",
        "plt.xlabel('App', fontsize = 14)\n",
        "plt.ylabel('Rating', fontsize = 14)\n",
        "plt.title('Highest Rating App', fontsize = 15)\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "sFZnY1AeTPSM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 670
        },
        "outputId": "6b024c90-5f33-4769-c81e-f6314010ba6d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Top 10 highest rating apps**\n"
      ],
      "metadata": {
        "id": "kdnqrIMVjTul"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(df['App'].unique())"
      ],
      "metadata": {
        "id": "5T6enPp-TPO1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d61cbcf3-99a0-4bcf-ce09-d001ca9b1158"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9660"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df['App'])"
      ],
      "metadata": {
        "id": "50cSmnmgTPLW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fc82f27b-e6d6-4724-8914-1c31da93c754"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10841"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby('App').sum().sort_values(by = 'Rating', ascending = False).head(11)"
      ],
      "metadata": {
        "id": "IFVJBuJHTPH1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "outputId": "4f2dc522-3995-41fb-cd3e-1a7295153f68"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                   Rating    Installs  Price\n",
              "App                                                                         \n",
              "ROBLOX                                               40.5   900000000    0.0\n",
              "CBS Sports App - Scores, News, Stats & Watch Live    34.4    40000000    0.0\n",
              "Duolingo: Learn Languages Free                       32.9   700000000    0.0\n",
              "8 Ball Pool                                          31.5   700000000    0.0\n",
              "Candy Crush Saga                                     30.8  3500000000    0.0\n",
              "ESPN                                                 29.4    70000000    0.0\n",
              "Zombie Catchers                                      28.2    60000000    0.0\n",
              "Bowmasters                                           28.2   300000000    0.0\n",
              "Sniper 3D Gun Shooter: Free Shooting Games - FPS     27.6   600000000    0.0\n",
              "Subway Surfers                                       27.0  6000000000    0.0\n",
              "Bubble Shooter                                       26.9    50000000    0.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ede9076f-d41a-4cc7-ad34-381222ad2581\">\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>Rating</th>\n",
              "      <th>Installs</th>\n",
              "      <th>Price</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>App</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ROBLOX</th>\n",
              "      <td>40.5</td>\n",
              "      <td>900000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CBS Sports App - Scores, News, Stats &amp; Watch Live</th>\n",
              "      <td>34.4</td>\n",
              "      <td>40000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Duolingo: Learn Languages Free</th>\n",
              "      <td>32.9</td>\n",
              "      <td>700000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8 Ball Pool</th>\n",
              "      <td>31.5</td>\n",
              "      <td>700000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Candy Crush Saga</th>\n",
              "      <td>30.8</td>\n",
              "      <td>3500000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ESPN</th>\n",
              "      <td>29.4</td>\n",
              "      <td>70000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zombie Catchers</th>\n",
              "      <td>28.2</td>\n",
              "      <td>60000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bowmasters</th>\n",
              "      <td>28.2</td>\n",
              "      <td>300000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sniper 3D Gun Shooter: Free Shooting Games - FPS</th>\n",
              "      <td>27.6</td>\n",
              "      <td>600000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Subway Surfers</th>\n",
              "      <td>27.0</td>\n",
              "      <td>6000000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bubble Shooter</th>\n",
              "      <td>26.9</td>\n",
              "      <td>50000000</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ede9076f-d41a-4cc7-ad34-381222ad2581')\"\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",
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              "    <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",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\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",
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              "\n",
              "      <script>\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ede9076f-d41a-4cc7-ad34-381222ad2581');\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": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Top 10 Lowest Rating Apps**"
      ],
      "metadata": {
        "id": "hCar1lXNkIdc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby('App').sum().sort_values(by = 'Rating', ascending = True).head(20)"
      ],
      "metadata": {
        "id": "D45fyspFTPEE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 708
        },
        "outputId": "d29f99cb-ef3f-4efa-ee05-703560a8bf5f"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                Rating  Installs  Price\n",
              "App                                                                    \n",
              "\"i DT\" Fútbol. Todos Somos Técnicos.               0.0       500   0.00\n",
              "Málaga CF Wallpapers 4 Fans                        0.0        10   0.00\n",
              "México City D.F News                               0.0       100   0.00\n",
              "N+ News Bulgaria                                   0.0        50   0.00\n",
              "Weather Data CH                                    0.0       500   2.99\n",
              "Carpooling FH Hagenberg                            0.0       100   0.00\n",
              "Cargo de Praça PM DF                               0.0        10   2.99\n",
              "NATIVE ENTERTAINMENT MAGAZINE - ISSUE # 1          0.0        10   0.00\n",
              "Cardio-FR                                          0.0     10000   0.00\n",
              "Cardio Z                                           0.0       100   5.99\n",
              "NCLEX-RN Q&A FLASH CARDS - FA Davis                0.0      1000   0.00\n",
              "Shaggy's DM Assistant                              0.0         5   0.00\n",
              "Car Driving Theory Test BC                         0.0        10   1.49\n",
              "Caprock Santa Fe Credit Union                      0.0       100   0.00\n",
              "Capitalnews.com.cy                                 0.0        10   0.00\n",
              "Capital Bk Mobile Business Dep                     0.0       100   0.00\n",
              "Servidor Privado CR y CoC - Royale Servers PRO     0.0       100   1.99\n",
              "Weill Cornell Medicine                             0.0        50   0.00\n",
              "CZ-52 pistol explained                             0.0        10   5.99\n",
              "CZ-70 (CZ-50) pistol explained                     0.0        10   5.99"
            ],
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              "\n",
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              "      <th>\"i DT\" Fútbol. Todos Somos Técnicos.</th>\n",
              "      <td>0.0</td>\n",
              "      <td>500</td>\n",
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              "      <th>Málaga CF Wallpapers 4 Fans</th>\n",
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              "      <th>N+ News Bulgaria</th>\n",
              "      <td>0.0</td>\n",
              "      <td>50</td>\n",
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              "      <th>Weather Data CH</th>\n",
              "      <td>0.0</td>\n",
              "      <td>500</td>\n",
              "      <td>2.99</td>\n",
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              "      <th>Carpooling FH Hagenberg</th>\n",
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              "      <td>100</td>\n",
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              "      <td>10</td>\n",
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              "      <th>NATIVE ENTERTAINMENT MAGAZINE - ISSUE # 1</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10</td>\n",
              "      <td>0.00</td>\n",
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              "    <tr>\n",
              "      <th>Cardio-FR</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10000</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cardio Z</th>\n",
              "      <td>0.0</td>\n",
              "      <td>100</td>\n",
              "      <td>5.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NCLEX-RN Q&amp;A FLASH CARDS - FA Davis</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1000</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shaggy's DM Assistant</th>\n",
              "      <td>0.0</td>\n",
              "      <td>5</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Car Driving Theory Test BC</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10</td>\n",
              "      <td>1.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Caprock Santa Fe Credit Union</th>\n",
              "      <td>0.0</td>\n",
              "      <td>100</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Capitalnews.com.cy</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Capital Bk Mobile Business Dep</th>\n",
              "      <td>0.0</td>\n",
              "      <td>100</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Servidor Privado CR y CoC - Royale Servers PRO</th>\n",
              "      <td>0.0</td>\n",
              "      <td>100</td>\n",
              "      <td>1.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Weill Cornell Medicine</th>\n",
              "      <td>0.0</td>\n",
              "      <td>50</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CZ-52 pistol explained</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10</td>\n",
              "      <td>5.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CZ-70 (CZ-50) pistol explained</th>\n",
              "      <td>0.0</td>\n",
              "      <td>10</td>\n",
              "      <td>5.99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6f5fcd55-303b-4e7a-ab1d-ec9b6a08dbd4')\"\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",
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              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      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-6f5fcd55-303b-4e7a-ab1d-ec9b6a08dbd4 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-6f5fcd55-303b-4e7a-ab1d-ec9b6a08dbd4');\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": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Paid&Free Apps Counts**"
      ],
      "metadata": {
        "id": "yngkP9XOlIOi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.countplot(data = df, x = 'Type')\n",
        "plt.xlabel(\"Type\", fontsize = 12)\n",
        "plt.ylabel(\"Count\", fontsize = 12)\n",
        "plt.title(\"Paid&Free Apps Counts\", fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "xnRywJp6TO-5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "d5f1b505-3d6c-4deb-e833-ad85375776b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
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          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (12,5))\n",
        "sns.boxplot(x = 'Type', y = 'Rating', data = df)\n",
        "plt.xlabel(\"Type\", fontsize = 12)\n",
        "plt.ylabel(\"Rating\", fontsize = 12)\n",
        "plt.title(\"Paid&Free Apps Rating\", fontsize = 15)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "32cybC1CTO7K",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "c75867d1-4d1c-424d-f41b-2d608507113f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "According to the graph free app rating is somewhere around '4.2' and paid appa rating '4.4'. There is not much difference but still the paid is more rating than free app"
      ],
      "metadata": {
        "id": "A2hWPyD_mGvZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Age group wise rating**"
      ],
      "metadata": {
        "id": "BD8XfEnXnNJQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Content_Rating = df.groupby('Content Rating').sum()['Rating'].reset_index()\n",
        "Content_Rating"
      ],
      "metadata": {
        "id": "1YSkXHClTO38",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "outputId": "cd9eeaa5-7589-4b3c-d2fe-16d88ae7e387"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Content Rating        Rating\n",
              "0  Adults only 18+     12.900000\n",
              "1         Everyone  35051.426412\n",
              "2     Everyone 10+   1598.593413\n",
              "3       Mature 17+   1846.060179\n",
              "4             Teen   4852.073951\n",
              "5          Unrated      8.293338"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-599395cf-9927-47be-800e-bdc522cad5f7\">\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>Content Rating</th>\n",
              "      <th>Rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adults only 18+</td>\n",
              "      <td>12.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Everyone</td>\n",
              "      <td>35051.426412</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Everyone 10+</td>\n",
              "      <td>1598.593413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Mature 17+</td>\n",
              "      <td>1846.060179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Teen</td>\n",
              "      <td>4852.073951</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Unrated</td>\n",
              "      <td>8.293338</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-599395cf-9927-47be-800e-bdc522cad5f7')\"\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-599395cf-9927-47be-800e-bdc522cad5f7 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-599395cf-9927-47be-800e-bdc522cad5f7');\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": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.barplot(x = Content_Rating['Content Rating'], y = Content_Rating['Rating'] )\n",
        "plt.xlabel('Content Rating')\n",
        "plt.ylabel('Count')\n",
        "plt.title('Age Group wise rating')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "S_QYXnuCTO0U",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 365
        },
        "outputId": "af8aba32-c562-45c0-e629-a7ac342280bf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Top 10 highest installed apps**"
      ],
      "metadata": {
        "id": "7CIvriDjnudL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "install = df.groupby('App')['Installs'].sum().sort_values(ascending = False).head(10).reset_index()\n",
        "plt.bar('App', 'Installs', data = install, color = 'blue')\n",
        "plt.xlabel('Apps')\n",
        "plt.ylabel('Installs')\n",
        "plt.xticks(rotation = 90)\n",
        "plt.title('Top 20 highest installed apps')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "A3Y5CDobTOwz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 492
        },
        "outputId": "f768d152-7730-4042-ee75-ca56843cc698"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Top 10 Paids App**"
      ],
      "metadata": {
        "id": "iTDWUVIaboLz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "paid_apps = df[df['Type'] == 'Paid'].sort_values(by='Price', ascending=False).head(10)"
      ],
      "metadata": {
        "id": "YSh2xy6sTOrC"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "paid_apps"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "4HiFzyOXdDf6",
        "outputId": "6cf6e489-7da3-4e89-f4b2-6f491d65fcdf"
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      "execution_count": 32,
      "outputs": [
        {
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            "text/plain": [
              "                                    App   Category  Rating Reviews  Size  \\\n",
              "4367           I'm Rich - Trump Edition  LIFESTYLE     3.6     275  7.3M   \n",
              "5359                 I am rich(premium)    FINANCE     3.5     472  965k   \n",
              "5373                 I AM RICH PRO PLUS    FINANCE     4.0      36   41M   \n",
              "9934  I'm Rich/Eu sou Rico/أنا غني/我很有錢  LIFESTYLE     NaN       0   40M   \n",
              "5354                     I am Rich Plus     FAMILY     4.0     856  8.7M   \n",
              "5351                          I am rich  LIFESTYLE     3.8    3547  1.8M   \n",
              "5358                         I am Rich!    FINANCE     3.8      93   22M   \n",
              "5362                      I Am Rich Pro     FAMILY     4.4     201  2.7M   \n",
              "4362                         💎 I'm rich  LIFESTYLE     3.8     718   26M   \n",
              "5364     I am rich (Most expensive app)    FINANCE     4.1     129  2.7M   \n",
              "\n",
              "      Installs  Type   Price Content Rating         Genres       Last Updated  \\\n",
              "4367     10000  Paid  400.00       Everyone      Lifestyle        May 3, 2018   \n",
              "5359      5000  Paid  399.99       Everyone        Finance        May 1, 2017   \n",
              "5373      1000  Paid  399.99       Everyone        Finance      June 25, 2018   \n",
              "9934         0  Paid  399.99       Everyone      Lifestyle   December 1, 2017   \n",
              "5354     10000  Paid  399.99       Everyone  Entertainment       May 19, 2018   \n",
              "5351    100000  Paid  399.99       Everyone      Lifestyle   January 12, 2018   \n",
              "5358      1000  Paid  399.99       Everyone        Finance  December 11, 2017   \n",
              "5362      5000  Paid  399.99       Everyone  Entertainment       May 30, 2017   \n",
              "4362     10000  Paid  399.99       Everyone      Lifestyle     March 11, 2018   \n",
              "5364      1000  Paid  399.99           Teen        Finance   December 6, 2017   \n",
              "\n",
              "     Current Ver   Android Ver  \n",
              "4367       1.0.1    4.1 and up  \n",
              "5359         3.4    4.4 and up  \n",
              "5373       1.0.2    4.1 and up  \n",
              "9934       MONEY    4.1 and up  \n",
              "5354         3.0    4.4 and up  \n",
              "5351         2.0  4.0.3 and up  \n",
              "5358         1.0    4.1 and up  \n",
              "5362        1.54    1.6 and up  \n",
              "4362       1.0.0    4.4 and up  \n",
              "5364           2  4.0.3 and up  "
            ],
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              "      <th></th>\n",
              "      <th>App</th>\n",
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              "      <th>4367</th>\n",
              "      <td>I'm Rich - Trump Edition</td>\n",
              "      <td>LIFESTYLE</td>\n",
              "      <td>3.6</td>\n",
              "      <td>275</td>\n",
              "      <td>7.3M</td>\n",
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              "      <td>472</td>\n",
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              "      <td>Paid</td>\n",
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              "      <td>I AM RICH PRO PLUS</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>36</td>\n",
              "      <td>41M</td>\n",
              "      <td>1000</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Finance</td>\n",
              "      <td>June 25, 2018</td>\n",
              "      <td>1.0.2</td>\n",
              "      <td>4.1 and up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9934</th>\n",
              "      <td>I'm Rich/Eu sou Rico/أنا غني/我很有錢</td>\n",
              "      <td>LIFESTYLE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>40M</td>\n",
              "      <td>0</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Lifestyle</td>\n",
              "      <td>December 1, 2017</td>\n",
              "      <td>MONEY</td>\n",
              "      <td>4.1 and up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5354</th>\n",
              "      <td>I am Rich Plus</td>\n",
              "      <td>FAMILY</td>\n",
              "      <td>4.0</td>\n",
              "      <td>856</td>\n",
              "      <td>8.7M</td>\n",
              "      <td>10000</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Entertainment</td>\n",
              "      <td>May 19, 2018</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.4 and up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5351</th>\n",
              "      <td>I am rich</td>\n",
              "      <td>LIFESTYLE</td>\n",
              "      <td>3.8</td>\n",
              "      <td>3547</td>\n",
              "      <td>1.8M</td>\n",
              "      <td>100000</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Lifestyle</td>\n",
              "      <td>January 12, 2018</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0.3 and up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5358</th>\n",
              "      <td>I am Rich!</td>\n",
              "      <td>FINANCE</td>\n",
              "      <td>3.8</td>\n",
              "      <td>93</td>\n",
              "      <td>22M</td>\n",
              "      <td>1000</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Finance</td>\n",
              "      <td>December 11, 2017</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.1 and up</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5362</th>\n",
              "      <td>I Am Rich Pro</td>\n",
              "      <td>FAMILY</td>\n",
              "      <td>4.4</td>\n",
              "      <td>201</td>\n",
              "      <td>2.7M</td>\n",
              "      <td>5000</td>\n",
              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
              "      <td>Everyone</td>\n",
              "      <td>Entertainment</td>\n",
              "      <td>May 30, 2017</td>\n",
              "      <td>1.54</td>\n",
              "      <td>1.6 and up</td>\n",
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              "    <tr>\n",
              "      <th>4362</th>\n",
              "      <td>💎 I'm rich</td>\n",
              "      <td>LIFESTYLE</td>\n",
              "      <td>3.8</td>\n",
              "      <td>718</td>\n",
              "      <td>26M</td>\n",
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              "      <th>5364</th>\n",
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              "      <td>4.1</td>\n",
              "      <td>129</td>\n",
              "      <td>2.7M</td>\n",
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              "      <td>Paid</td>\n",
              "      <td>399.99</td>\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "plt.pie(paid_apps.Installs, labels = paid_apps.App, autopct='%1.1f%%')\n",
        "plt.title('Top 10 Paids Apps')\n",
        "plt.legend(paid_apps.App, title='Apps', fontsize = 'medium')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "kg3Vd5jrTOm2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 938
        },
        "outputId": "aaec140f-74ac-4ece-c18c-d8d6ea4771c6"
      },
      "execution_count": 44,
      "outputs": [
        {
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          "name": "stderr",
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Top five Paid apps are:-**\n",
        "\n",
        "1. I am Rich\n",
        "2. I am Rich - Trump Editiom\n",
        "3. I am Rich Plus\n",
        "4. I am rich premium\n",
        "5. I am rich pro"
      ],
      "metadata": {
        "id": "BK4yUw3kheB_"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "AtZ0vHS2TOgW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "iwjjadhVTOdb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "IqIzAdLVTOaA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Sv73cMClTOUS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "dYjnevIHTOQ6"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}