https://github.com/abhipatel35/gym-performance-analysis

Analyzing gym performance and user engagement in Arizona using Spark SQL, PySpark, and visualization techniques on the Yelp dataset.
https://github.com/abhipatel35/gym-performance-analysis

apache-spark asu business-insights data-analysis data-processing-at-scale data-visualization dps gym-analysis rating-patterns sql trend-analysis user-insights yelp-dataset

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Analyzing gym performance and user engagement in Arizona using Spark SQL, PySpark, and visualization techniques on the Yelp dataset.

• Host: GitHub
• URL: https://github.com/abhipatel35/gym-performance-analysis
• Owner: abhipatel35
• Created: 2024-12-28T00:02:48.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-28T00:38:03.000Z (over 1 year ago)
• Last Synced: 2025-06-04T09:26:53.784Z (about 1 year ago)
• Topics: apache-spark, asu, business-insights, data-analysis, data-processing-at-scale, data-visualization, dps, gym-analysis, rating-patterns, sql, trend-analysis, user-insights, yelp-dataset
• Language: Jupyter Notebook
• Homepage:
• Size: 617 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Gym Performance Analysis (Yelp Analysis)

## Description

This repository contains SQL scripts for analyzing Yelp data at both user and business levels. 

## Dataset

The dataset used for this analysis can be downloaded from the following link:

[Download Yelp Dataset](https://www.yelp.com/dataset)

![image](https://github.com/user-attachments/assets/98de57cb-4e3a-4d5e-b64d-155a58727ce2)

## Files

- `gym_user_level_analysis.ipynb`: SQL queries for user-level analysis.

- `gym_business_level_analysis.ipynb`: SQL queries for business-level analysis. 

- `gym_user_level_analysis_report.pdf`: Report for SQL queries for user-level analysis.

- `gym_business_level_analysis_report.pdf`: Report for SQL queries for business-level analysis.

## Usage

1. Download the dataset from the provided link.

3. Extract the dataset files.

4. Run SQL scripts using Apache Spark.

5. Visualize outputs as described.

## Results

Key insights from analyses include:

- Top cities for gyms.

- User activity trends.

- Rating patterns.