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The Android App Market on Google Play

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Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.

  • The data for this project was scraped from the Google Play website. While there are many popular datasets for Apple App Store. The data files are:
    • apps.csv: contains all the details of the apps on Google Play.
    • user_reviews.csv: contains 100 reviews for each app, most helpful first.

📂 Dataset

📄: apps.csv

Unnamed: 0 App Category Rating Reviews Size Installs Type Price Content Rating Genres Last Updated Current Ver Android Ver
0 0 Photo Editor & Candy Camera & Grid & ScrapBook ART_AND_DESIGN 4.1 159 19 10000 Free 0 Everyone Art & Design January 7, 2018 1.0.0 4.0.3 and up
1 1 Coloring book moana ART_AND_DESIGN 3.9 967 14 500000 Free 0 Everyone Art & Design;Pretend Play January 15, 2018 2.0.0 4.0.3 and up
2 2 U Launcher Lite – FREE Live Cool Themes, Hide Apps ART_AND_DESIGN 4.7 87510 8.7 5e+06 Free 0 Everyone Art & Design August 1, 2018 1.2.4 4.0.3 and up
3 3 Sketch - Draw & Paint ART_AND_DESIGN 4.5 215644 25 5e+07 Free 0 Teen Art & Design June 8, 2018 Varies with device 4.2 and up
4 4 Pixel Draw - Number Art Coloring Book ART_AND_DESIGN 4.3 967 2.8 100000 Free 0 Everyone Art & Design;Creativity June 20, 2018 1.1 4.4 and up

📄: user_reviews.csv

App Review Sentiment Sentiment_Polarity Sentiment_Subjectivity
0 10 Best Foods for You I like eat delicious food. That's I'm cooking food myself, case "10 Best Foods" helps lot, also "Best Before (Shelf Life)" Positive 1 0.533333
1 10 Best Foods for You This help eating healthy exercise regular basis Positive 0.25 0.288462
2 10 Best Foods for You nan nan nan nan
3 10 Best Foods for You Works great especially going grocery store Positive 0.4 0.875
4 10 Best Foods for You Best idea us Positive 1 0.3

Project instructions:

  • Import the data, drop duplicate rows, and inspect the data

  • Clean the dataset

  • Correcting data types

  • Dealing with missing numerical values.

  • Exploring app categories: create data for a bar chart that shows the distribution of apps across different categories.

  • Distribution of app ratings: create a plot annotation for average app rating.

  • Examine the relationship between size, price, and rating of apps using jointplot().

  • Use a strip plot to visualize the distribution of paid apps across different categories.

  • Filter out "junk" apps.

  • Popularity of paid apps vs free apps: prep the data for a box plot that compares the number of installs of paid apps vs. number of installs of free apps: this figure shows that the number of downloads of free applications is higher than paid applications

  • Sentiment analysis of user reviews: load the user review data and plot it to visualize sentiment of paid vs. free apps.

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