{"id":18330120,"url":"https://github.com/dmarks84/coursework_project_data-analysis-apache-spark","last_synced_at":"2026-04-11T00:07:24.068Z","repository":{"id":217712631,"uuid":"744619730","full_name":"dmarks84/Coursework_Project_Data-Analysis-Apache-Spark","owner":"dmarks84","description":"Project for IBM Data Engineering \u0026 Python course on ETL \u0026 Big Data -- Read in data, wrote to SQL database and performed queries, performed statistical analysis and issued reports","archived":false,"fork":false,"pushed_at":"2024-01-17T23:06:23.000Z","size":7,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-15T10:32:08.234Z","etag":null,"topics":["apache-sprk","automation","dag","data-modeling","eda","elt","etl","numpy","pandas","pipelines","python","sql","statistics","visualization"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dmarks84.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2024-01-17T17:08:24.000Z","updated_at":"2024-03-05T21:14:11.000Z","dependencies_parsed_at":"2024-01-18T01:18:09.357Z","dependency_job_id":"0b20b2d3-c50f-4a8f-a593-a19e2b59f8a8","html_url":"https://github.com/dmarks84/Coursework_Project_Data-Analysis-Apache-Spark","commit_stats":null,"previous_names":["dmarks84/project_data-analysis-apache-spark","dmarks84/coursework_project_data-analysis-apache-spark"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmarks84%2FCoursework_Project_Data-Analysis-Apache-Spark","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmarks84%2FCoursework_Project_Data-Analysis-Apache-Spark/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmarks84%2FCoursework_Project_Data-Analysis-Apache-Spark/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmarks84%2FCoursework_Project_Data-Analysis-Apache-Spark/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dmarks84","download_url":"https://codeload.github.com/dmarks84/Coursework_Project_Data-Analysis-Apache-Spark/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248078966,"owners_count":21044207,"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","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-sprk","automation","dag","data-modeling","eda","elt","etl","numpy","pandas","pipelines","python","sql","statistics","visualization"],"created_at":"2024-11-05T19:20:34.013Z","updated_at":"2025-12-30T23:05:08.930Z","avatar_url":"https://github.com/dmarks84.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Project(Project_Data-Analysis-Apache-Spark)\n### Part of the Coursera series: IBM Data Engineering \u0026 Python\n    \n## Summary\nMy Jupyter notebook did not save correctly, unfortunately.  My work has been deleted, but the outline of the project belies the steps I understook.  Primarily, we completed these tasks:\nTask 1: Generate DataFrame from CSV data.\nTask 2: Define a schema for the data.\nTask 3: Display schema of DataFrame.\nTask 4: Create a temporary view.\nTask 5: Execute an SQL query.\nTask 6: Calculate Average Salary by Department.\nTask 7: Filter and Display IT Department Employees.\nTask 8: Add 10% Bonus to Salaries.\nTask 9: Find Maximum Salary by Age.\nTask 10: Self-Join on Employee Data.\nTask 11: Calculate Average Employee Age.\nTask 12: Calculate Total Salary by Department.\nTask 13: Sort Data by Age and Salary.\nTask 14: Count Employees in Each Department.\nTask 15: Filter Employees with the letter o in the Name. \n\n## Skills (Developed \u0026 Applied)\nProgramming, Python, RDBMS \u0026 SQL, Databases, Statistics, Numpy, Pandas, Dataframes, ETL \u0026| ELT \u0026 Data Pipelines, DAGs, Apache Spark, Automation, Data Modeling, EDA, Data Visualization, Data Summarization\n    ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmarks84%2Fcoursework_project_data-analysis-apache-spark","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdmarks84%2Fcoursework_project_data-analysis-apache-spark","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmarks84%2Fcoursework_project_data-analysis-apache-spark/lists"}