https://github.com/gajendrasharma-github/app_store

Capstone Project with 2.4 Million Records
https://github.com/gajendrasharma-github/app_store

classification data-analysis-python regression

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Capstone Project with 2.4 Million Records

• Host: GitHub
• URL: https://github.com/gajendrasharma-github/app_store
• Owner: gajendrasharma-github
• Created: 2024-06-03T09:10:53.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-08-25T11:29:17.000Z (3 months ago)
• Last Synced: 2024-08-25T12:37:39.255Z (3 months ago)
• Topics: classification, data-analysis-python, regression
• Language: Jupyter Notebook
• Homepage:
• Size: 1.14 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

![Logo](https://play.google.com/intl/en_us/badges/images/generic/en_badge_web_generic.png)

# Predictive Analytics and Performance Insights for Google Playstore

## Problem Statement

The mobile application market, specifically Google Play Store, has seen exponential growth over the past decade. With millions of apps available, it becomes crucial for developers and 

businesses to understand what drives app success and how to predict future performance. 

This project focuses on analyzing app performance metrics and using machine learning to 

predict key success indicators such as earning the **Editor's Choice badge**, classifying apps 

based on installation counts, and predicting **average installs**.

Understanding these factors can help developers optimize their apps for better visibility and 

success in the competitive app marketplace. This analysis provides valuable insights into app 

characteristics that contribute to high performance and user engagement.

## Goals for the Project

- Deploying comprehensive analysis of apps on a **Streamlit web application**

- Predicting whether an app will be awarded the Editor's Choice badge.

- Classifying apps based on their installation numbers

- Predicting the average number of installs a new app might expect

## About Data

 - The dataset was sourced from Kaggle and includes comprehensive details of 2.3 million apps on Google Play Store

 - Attributes: 24 , Values: 2312944

 **Link to the Dataset**: https://www.kaggle.com/datasetsgauthamp10/google-playstore-apps

## Streamlit Web Application

![App Screenshot](https://github.com/gajendrasharma-github/TMDB_Movie_Recommender_System/blob/master/Streamlit_app_image.jpeg?raw=true)

**Link to the Streamlit Application** : 

https://playstore-analytics.streamlit.app/

## Tech Stack

**Skills :** Data Analysis, Data Preprocessing, Exploratory Data Analysis, Machine Learning

**Tools :** Python, Streamlit, Git and Github

**Libraries :** Numpy, Pandas, Seaborn, Matplotlib, Scikit Learn