{"id":24033432,"url":"https://github.com/abhipatel35/gym-performance-analysis","last_synced_at":"2026-04-16T17:36:15.395Z","repository":{"id":270046679,"uuid":"909178129","full_name":"abhipatel35/Gym-Performance-Analysis","owner":"abhipatel35","description":"Analyzing gym performance and user engagement in Arizona using Spark SQL, PySpark, and visualization techniques on the Yelp dataset.","archived":false,"fork":false,"pushed_at":"2024-12-28T00:38:03.000Z","size":632,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-04T09:26:53.784Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/abhipatel35.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-28T00:02:48.000Z","updated_at":"2025-01-09T23:34:16.000Z","dependencies_parsed_at":"2024-12-28T01:20:34.286Z","dependency_job_id":"d1fefd6f-a238-4288-9d17-ea02b1400134","html_url":"https://github.com/abhipatel35/Gym-Performance-Analysis","commit_stats":null,"previous_names":["abhipatel35/gym-performance-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/abhipatel35/Gym-Performance-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhipatel35%2FGym-Performance-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhipatel35%2FGym-Performance-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhipatel35%2FGym-Performance-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhipatel35%2FGym-Performance-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abhipatel35","download_url":"https://codeload.github.com/abhipatel35/Gym-Performance-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhipatel35%2FGym-Performance-Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279139981,"owners_count":26112498,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-16T02:00:06.019Z","response_time":53,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["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"],"created_at":"2025-01-08T18:19:31.838Z","updated_at":"2025-10-16T02:08:49.887Z","avatar_url":"https://github.com/abhipatel35.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Gym Performance Analysis (Yelp Analysis)\n\n## Description\nThis repository contains SQL scripts for analyzing Yelp data at both user and business levels. \n\n## Dataset\nThe dataset used for this analysis can be downloaded from the following link:\n[Download Yelp Dataset](https://www.yelp.com/dataset)\n![image](https://github.com/user-attachments/assets/98de57cb-4e3a-4d5e-b64d-155a58727ce2)\n\n\n## Files\n- `gym_user_level_analysis.ipynb`: SQL queries for user-level analysis.\n- `gym_business_level_analysis.ipynb`: SQL queries for business-level analysis. \n- `gym_user_level_analysis_report.pdf`: Report for SQL queries for user-level analysis.\n- `gym_business_level_analysis_report.pdf`: Report for SQL queries for business-level analysis.\n\n## Usage\n1. Download the dataset from the provided link.\n3. Extract the dataset files.\n4. Run SQL scripts using Apache Spark.\n5. Visualize outputs as described.\n\n## Results\nKey insights from analyses include:\n- Top cities for gyms.\n- User activity trends.\n- Rating patterns.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhipatel35%2Fgym-performance-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhipatel35%2Fgym-performance-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhipatel35%2Fgym-performance-analysis/lists"}