{"id":27646188,"url":"https://github.com/fbarffmann/pandas-challenge","last_synced_at":"2025-10-12T02:04:00.336Z","repository":{"id":240815832,"uuid":"801704876","full_name":"fbarffmann/pandas-challenge","owner":"fbarffmann","description":"Analyzed school budget and performance data using Python and Pandas to uncover trends by school type, size, and spending per student.","archived":false,"fork":false,"pushed_at":"2025-04-01T11:52:11.000Z","size":483,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-24T01:17:36.826Z","etag":null,"topics":[],"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/fbarffmann.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,"zenodo":null}},"created_at":"2024-05-16T18:49:47.000Z","updated_at":"2025-04-01T11:53:53.000Z","dependencies_parsed_at":"2024-05-21T01:10:02.614Z","dependency_job_id":"8afdfc36-21bc-4d5b-b506-601d4dc537ca","html_url":"https://github.com/fbarffmann/pandas-challenge","commit_stats":null,"previous_names":["fbarffmann/pandas-challenge"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/fbarffmann/pandas-challenge","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fbarffmann%2Fpandas-challenge","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fbarffmann%2Fpandas-challenge/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fbarffmann%2Fpandas-challenge/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fbarffmann%2Fpandas-challenge/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fbarffmann","download_url":"https://codeload.github.com/fbarffmann/pandas-challenge/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fbarffmann%2Fpandas-challenge/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279009913,"owners_count":26084665,"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":"2025-10-12T02:00:06.719Z","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":[],"created_at":"2025-04-24T01:17:24.269Z","updated_at":"2025-10-12T02:04:00.305Z","avatar_url":"https://github.com/fbarffmann.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Pandas Challenge: PyCitySchools Analysis\n\n## Overview\n\nThis project analyzes standardized testing data for a hypothetical school district to help inform strategic decision-making around budgets and academic priorities. Using Python and the Pandas library, the analysis explores student and school-level performance metrics, including average scores, pass rates, and the impact of variables like school type, size, and budget per student.\n\n## Dataset\n\nThe data comes from two CSV files:\n\n- `schools_complete.csv`: Information about each school, including name, type (District or Charter), budget, and size.\n- `students_complete.csv`: Contains information for each student, including school attended, grade level, gender, and test scores in math and reading.\n\n## Objectives\n\n- Generate a **District Summary** of key metrics like average test scores and pass rates.\n- Create a **School Summary** that breaks down performance by individual schools.\n- Rank schools based on overall student performance.\n- Analyze **grade-level** performance trends in math and reading.\n- Explore the relationship between **spending per student** and test performance.\n- Investigate how **school size** and **school type** correlate with academic outcomes.\n\n## Key Findings\n\n- **Charter schools** consistently outperformed district schools in both math and reading, with higher average scores and pass rates.\n- Smaller schools (fewer than 1,000 students) performed better on average than larger schools.\n- Spending more per student did **not** correlate with higher performance, suggesting more efficient use of funds might be more important than total expenditure.\n- **9th graders** generally had the lowest average scores across subjects, while **10th and 11th graders** tended to perform better.\n- The top five schools were all charter schools, reinforcing the trend of better performance among that school type.\n\n## Technologies Used\n\n- **Python**\n- **Pandas**\n- **Jupyter Notebook**\n\n\n## How to Use\n\n1. Clone the repository:\n\n```\ngit clone https://github.com/fbarffmann/pandas-challenge.git\n```\n\n2. Navigate to the PyCitySchools directory:\n\n```\ncd pandas-challenge/PyCitySchools\n```\n\n3. Install pandas and jupyter libraries if need be:\n\n```\npip install pandas jupyter\n```\n\n4. Launch the Jupyter Notebook:\n\n```\njupyter notebook Analysis.ipynb\n```\n\n5. Run all cells to execute the full school budget and performance analysis.\n\n---\n\n👨‍💻 Developed by Finn Brennan Arffmann  \n📊 Learn more at [github.com/fbarffmann](https://github.com/fbarffmann)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffbarffmann%2Fpandas-challenge","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffbarffmann%2Fpandas-challenge","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffbarffmann%2Fpandas-challenge/lists"}