User_reviews_csv.ipynb

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        "<a href=\"https://colab.research.google.com/github/rutujahingankar/Play-store-app-review-analysis/blob/main/User_reviews_csv.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "## <b> The Play Store apps data has enormous potential to drive app-making businesses to success. Actionable insights can be drawn for developers to work on and capture the Android market. </b>\n",
        "\n",
        "## <b> Each app (row) has values for catergory, rating, size, and more. Another dataset contains customer reviews of the android apps.</b>\n",
        "\n",
        "## <b> Explore and analyze the data to discover key factors responsible for app engagement and success. </b>"
      ]
    },
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      "source": [
        "#import library\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "import numpy as np # linear algebra\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns  # visualization tool\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive') # Mounted Google Drive"
      ],
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          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df =pd.read_csv('/content/drive/MyDrive/Play Store Data.csv')   # Read the Google play store Data\n",
        "df.head()"
      ],
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        "id": "VD7NHF-8Snb6",
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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",
              "\n",
              "    Android Ver  \n",
              "0  4.0.3 and up  \n",
              "1  4.0.3 and up  \n",
              "2  4.0.3 and up  \n",
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              "      <td>U Launcher Lite – FREE Live Cool Themes, Hide ...</td>\n",
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              "      <td>Pixel Draw - Number Art Coloring Book</td>\n",
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              "      <td>967</td>\n",
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              "      <td>Art &amp; Design;Creativity</td>\n",
              "      <td>June 20, 2018</td>\n",
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        "df_review = pd.read_csv('/content/drive/MyDrive/User Reviews.csv') # Read the User Reviews\n",
        "df_review.head()"
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              "                     App                                  Translated_Review  \\\n",
              "0  10 Best Foods for You  I like eat delicious food. That's I'm cooking ...   \n",
              "1  10 Best Foods for You    This help eating healthy exercise regular basis   \n",
              "2  10 Best Foods for You                                                NaN   \n",
              "3  10 Best Foods for You         Works great especially going grocery store   \n",
              "4  10 Best Foods for You                                       Best idea us   \n",
              "\n",
              "  Sentiment  Sentiment_Polarity  Sentiment_Subjectivity  \n",
              "0  Positive                1.00                0.533333  \n",
              "1  Positive                0.25                0.288462  \n",
              "2       NaN                 NaN                     NaN  \n",
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              "4  Positive                1.00                0.300000  "
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Analysis Of User Review Data**\n",
        "\n"
      ],
      "metadata": {
        "id": "pYd_t01vTfN_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Drop missing data\n",
        "df_review.dropna(inplace= True)"
      ],
      "metadata": {
        "id": "HKvb5TwPTUAB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Drop the column \n",
        "df_review.drop(\"Translated_Review\",axis= 1, inplace= True)"
      ],
      "metadata": {
        "id": "hb7m_dpuTy0c"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Rename the remaining column \n",
        "df_review.columns = [\"App\", \"Sentiment\", \"polarity\", \"subjectivity\"]\n",
        "df_review"
      ],
      "metadata": {
        "id": "QZQuYI-JT3th",
        "outputId": "91441a78-8b65-4c19-a330-5cab9abae3ee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                  App Sentiment  polarity  subjectivity\n",
              "0               10 Best Foods for You  Positive  1.000000      0.533333\n",
              "1               10 Best Foods for You  Positive  0.250000      0.288462\n",
              "3               10 Best Foods for You  Positive  0.400000      0.875000\n",
              "4               10 Best Foods for You  Positive  1.000000      0.300000\n",
              "5               10 Best Foods for You  Positive  1.000000      0.300000\n",
              "...                               ...       ...       ...           ...\n",
              "64222  Housing-Real Estate & Property  Positive  0.173333      0.486667\n",
              "64223  Housing-Real Estate & Property  Positive  0.225000      0.447222\n",
              "64226  Housing-Real Estate & Property  Negative -0.287500      0.250000\n",
              "64227  Housing-Real Estate & Property  Positive  0.800000      1.000000\n",
              "64230  Housing-Real Estate & Property  Negative -0.316667      0.400000\n",
              "\n",
              "[37427 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4b630c21-eef0-4741-9da4-c1e185d74eed\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "    <tr style=\"text-align: right;\">\n",
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              "      <th>App</th>\n",
              "      <th>Sentiment</th>\n",
              "      <th>polarity</th>\n",
              "      <th>subjectivity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>10 Best Foods for You</td>\n",
              "      <td>Positive</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.533333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10 Best Foods for You</td>\n",
              "      <td>Positive</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>0.288462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10 Best Foods for You</td>\n",
              "      <td>Positive</td>\n",
              "      <td>0.400000</td>\n",
              "      <td>0.875000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10 Best Foods for You</td>\n",
              "      <td>Positive</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>10 Best Foods for You</td>\n",
              "      <td>Positive</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.300000</td>\n",
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              "    <tr>\n",
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              "      <td>Housing-Real Estate &amp; Property</td>\n",
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              "      <td>0.173333</td>\n",
              "      <td>0.486667</td>\n",
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              "    <tr>\n",
              "      <th>64223</th>\n",
              "      <td>Housing-Real Estate &amp; Property</td>\n",
              "      <td>Positive</td>\n",
              "      <td>0.225000</td>\n",
              "      <td>0.447222</td>\n",
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              "    <tr>\n",
              "      <th>64226</th>\n",
              "      <td>Housing-Real Estate &amp; Property</td>\n",
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              "    <tr>\n",
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              "      <td>1.000000</td>\n",
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              "      <td>Housing-Real Estate &amp; Property</td>\n",
              "      <td>Negative</td>\n",
              "      <td>-0.316667</td>\n",
              "      <td>0.400000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>37427 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4b630c21-eef0-4741-9da4-c1e185d74eed')\"\n",
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              "\n",
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              "\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4b630c21-eef0-4741-9da4-c1e185d74eed');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#shape before removing duplicates\n",
        "df_review.shape"
      ],
      "metadata": {
        "id": "14U5gFx4T8wy",
        "outputId": "7fb88797-98b1-4370-bb68-1e5c48fcae6b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(37427, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df_review[df_review.duplicated()])"
      ],
      "metadata": {
        "id": "XvGg3IXfUCFV",
        "outputId": "cbe61ea6-ed5d-48e6-edc0-c7d34498f7b3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12343"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#list of all duplicates values\n",
        "duplicate_review = df_review[df_review.duplicated(keep = 'last')]\n",
        "print(duplicate_review)"
      ],
      "metadata": {
        "id": "-TakclG8UJfA",
        "outputId": "5421cec9-854e-464f-8733-5d1509d9577f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                                  App Sentiment  polarity  subjectivity\n",
            "0               10 Best Foods for You  Positive      1.00      0.533333\n",
            "1               10 Best Foods for You  Positive      0.25      0.288462\n",
            "3               10 Best Foods for You  Positive      0.40      0.875000\n",
            "4               10 Best Foods for You  Positive      1.00      0.300000\n",
            "5               10 Best Foods for You  Positive      1.00      0.300000\n",
            "...                               ...       ...       ...           ...\n",
            "64179  Hotwire Hotel & Car Rental App   Neutral      0.00      0.000000\n",
            "64188  Hotwire Hotel & Car Rental App   Neutral      0.00      0.000000\n",
            "64199  Housing-Real Estate & Property  Negative     -0.50      0.200000\n",
            "64200  Housing-Real Estate & Property   Neutral      0.00      0.000000\n",
            "64205  Housing-Real Estate & Property   Neutral      0.00      0.000000\n",
            "\n",
            "[12343 rows x 4 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Remove duplicates and save as new DataFrame\n",
        "df_new_reviews = df_review.drop_duplicates()\n",
        "df_new_reviews.shape"
      ],
      "metadata": {
        "id": "G5MVkj-kUK0G",
        "outputId": "463995e6-af25-4fe7-e287-c5c647e65248",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(25084, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new_reviews.isnull().sum()"
      ],
      "metadata": {
        "id": "IqlmbAEyUSL6",
        "outputId": "c27d04a1-da3a-4d39-d63b-ee86a271e942",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "App             0\n",
              "Sentiment       0\n",
              "polarity        0\n",
              "subjectivity    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new_reviews.describe()"
      ],
      "metadata": {
        "id": "YAUSghxYUZh3",
        "outputId": "f990fc9b-e06d-471a-a882-33a7bb462dbd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           polarity  subjectivity\n",
              "count  25084.000000  25084.000000\n",
              "mean       0.189794      0.538103\n",
              "std        0.355776      0.220541\n",
              "min       -1.000000      0.000000\n",
              "25%        0.000000      0.403700\n",
              "50%        0.189167      0.540000\n",
              "75%        0.416667      0.666667\n",
              "max        1.000000      1.000000"
            ],
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              "      <td>0.538103</td>\n",
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              "      <th>std</th>\n",
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              "\n",
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              "            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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "DswokJmcUa-B"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}