The team at Google Play Store wants to develop a feature that would enable them to boost visibility for the most promising apps. Now, this analysis would require a preliminary understanding of the features that define a well-performing app. This analysis can answer questions like:
- Does a higher size or price necessarily mean that an app would perform better than the other apps?
- Or does a higher number of installs give a clear picture of which app would have a better rating than others?
Analysis was done in Jupyter Notebook using these Python libraries - Pandas, Numpy, Matplotib, Seaborn and Plotly
This analysis used various analytical steps and visualization:
- Data Handling and Cleaning
- Sanity Checks
- Outlier Analysis with Boxplots
- Histograms
- Distribution Plots
- Pie Chart
- Bar Chart
- Pair Plots
- Heatmaps
- Line Chart
- Stacked Bar Charts
- Plotly