Feature request: Add a new project (Real-Time Google Play Store Data Analytics Dashboard - Python) under new Data Analysis folder in the ML Nexus Repo

[sanyadureja]

Is your feature request related to a problem? Please describe. In today’s fast-paced app market, stakeholders often lack immediate and interactive insights into app performance data, especially for metrics like ratings, reviews, and downloads on the Google Play Store. Existing tools may lack customization and flexibility, making it challenging for users to analyze app data in real time and to quickly gauge app trends and user sentiment.

Describe the solution you'd like I propose adding a real-time analytics dashboard project under new Data Analysis folder using Python and Plotly that would visualize key metrics for Google Play Store apps, including ratings, review sentiment, and download counts. The dashboard will allow users to interact with the data, filter by parameters like date range or app category, and quickly gain insights into performance and trends. This could empower developers, marketers, and analysts to make timely, data-driven decisions based on real-time app performance.

Describe alternatives you've considered

• Static Reports: Generating weekly or monthly static reports that show app performance trends. However, this lacks the real-time interaction and customization features of a live dashboard.
• Third-Party Tools: Using existing app analytics platforms, but these may not provide the same level of customization or access to raw data for users who want a more hands-on approach.
• Excel-Based Visualization: Using Excel for data import and visualization. While effective for simpler analyses, it does not scale well for large datasets or offer the interactivity of a dashboard.

Approach to be followed (optional)

• Data Collection: Use APIs or web scraping (if permitted by Google’s terms) to gather real-time data on Google Play Store apps, focusing on metrics like ratings, reviews, and downloads.
• Data Processing: Clean and process the data using Python, storing it in a format compatible with Plotly (e.g., Pandas DataFrames).
• Dashboard Creation: Develop the dashboard with Plotly to provide interactive, customizable visualizations (e.g., line charts, bar graphs, heatmaps) and filtering options.
• Real-Time Updates: Implement a mechanism for periodic data refresh to maintain up-to-date analytics.

Additional context This feature could be especially valuable for app developers or digital marketers focused on improving app visibility, user satisfaction, and download rates. Below are examples of potential visualizations:

• Trend Line for ratings over time
• Sentiment Analysis of user reviews
• Download Comparison across app categories

Example dashboard for your reference

[github-actions[bot]]

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[sanyadureja]

@Neilblaze @SaiNivedh26 @UppuluriKalyani thanks for assigning this issue to me.

[sanyadureja]

@UppuluriKalyani, @Neilblaze, and @SaiNivedh26 please review my PR https://github.com/UppuluriKalyani/ML-Nexus/pull/813. I've solved the issue https://github.com/UppuluriKalyani/ML-Nexus/issues/811. Looking forward to getting the PR merged and assignment of level and labels.

Awaiting your response. Thank you!

[github-actions[bot]]

Hello @sanyadureja! Your issue #811 has been closed. Thank you for your contribution!