This data analysis project aims to provide analysis of Google PlayStore Apps data. This data has a potential to drive app-making businesses to success. Actionable insights can be drawn for business analysts and developers to work on and capture the Android market. In the dataset, each app has values for catergory, rating, size, etc.
Kaggle Dataset - Google Playstore Apps
- Kaggle Notebook : Data cleaning and analysis
- Tableau Public : Data visualizations
In the data preparations phase, I performed the following tasks;
- Dataset loading and inspection
- Handling missing values
- Handling duplicates
EDA involved exploring the dataset to answer key questions, such as;
- How many Google PlayStore Apps were collected?
- How many apps' categories were identified?
- Total number of installs in each category?
Checkout the dashboard on my Tableau Public Page
The analysis results are summarized as follows;
- The dataset collected just about 10k of Googles PlayStore Apps data
- The data had over 30 different apps' categories (i.e. family related apps, gaming, etc)
- Gaming-related apps have the most active reveiws and engagements
Based on the above analysis, I recommend the following;
- Gaming, communication, social media, family-related apps are leading in user engagements in Playstore. This could suggest apps' popularity.
- Comparing to the current (2026) number of apps available in playstore which is 3M+, much more data need to be analyzed to assess the validity of point 1 above.
- Dataset was small, a larger dataset is required for further analysis.
Dataset: L. Gupta, "Google Play Store Apps," Feb 2019. [Online]. Available: https://www.kaggle.com/lava18/google-play-store-apps