{"id":18553536,"url":"https://github.com/quantumudit/basketball-players-analysis","last_synced_at":"2026-05-17T01:36:32.117Z","repository":{"id":128744299,"uuid":"432631638","full_name":"quantumudit/Basketball-Players-Analysis","owner":"quantumudit","description":"The project focuses on analyzing salaries and various other in-game metrics of top NBA basketball players from 2005-14 by performing exploratory data analysis with Python and Jupyter Notebook and by visualizing the data in an insightful dashboard made with Power BI","archived":false,"fork":false,"pushed_at":"2021-11-28T05:59:10.000Z","size":1239,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-12-26T08:42:27.298Z","etag":null,"topics":["data-analysis","jupyter-notebook","power-bi","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/quantumudit.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,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-11-28T05:58:07.000Z","updated_at":"2024-01-01T17:47:54.000Z","dependencies_parsed_at":"2023-03-26T01:32:41.584Z","dependency_job_id":null,"html_url":"https://github.com/quantumudit/Basketball-Players-Analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantumudit%2FBasketball-Players-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantumudit%2FBasketball-Players-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantumudit%2FBasketball-Players-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantumudit%2FBasketball-Players-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/quantumudit","download_url":"https://codeload.github.com/quantumudit/Basketball-Players-Analysis/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239278525,"owners_count":19612329,"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":["data-analysis","jupyter-notebook","power-bi","python"],"created_at":"2024-11-06T21:17:28.871Z","updated_at":"2026-05-17T01:36:27.092Z","avatar_url":"https://github.com/quantumudit.png","language":"Jupyter Notebook","funding_links":["https://www.patreon.com/quantumudit"],"categories":[],"sub_categories":[],"readme":"![Project Logo][project_logo]\n\n---\n\n\u003ch4 align=\"center\"\u003eAnalyzing salary and in-game metrics of top-10 highest paid NBA basketball players from 2005-2014 with \u003ca href=\"https://en.wikipedia.org/wiki/Python_(programming_language)\" target=\"_blank\"\u003ePython\u003c/a\u003e and \u003ca href=\"https://en.wikipedia.org/wiki/Microsoft_Power_BI\" target=\"_blank\"\u003ePower BI\u003c/a\u003e\u003c/h4\u003e\n\n\u003cp align='center'\u003e\n\u003cimg src='05_RESOURCES/built-with-love.svg'\u003e\n\u003cimg src='05_RESOURCES/powered-by-coffee.svg'\u003e\n\u003cimg src='05_RESOURCES/cc-nc-sa.svg'\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"#overview\"\u003eOverview\u003c/a\u003e •\n  \u003ca href=\"#prerequisites\"\u003ePrerequisites\u003c/a\u003e •\n  \u003ca href=\"#architecture\"\u003eArchitecture\u003c/a\u003e •\n  \u003ca href=\"#demo\"\u003eDemo\u003c/a\u003e •\n  \u003ca href=\"#support\"\u003eSupport\u003c/a\u003e •\n  \u003ca href=\"#license\"\u003eLicense\u003c/a\u003e\n\u003c/p\u003e\n\n## Overview\n\nThis project focuses on analyzing salaries and various other in-game metrics of top NBA basketball players by performing exploratory data analysis to generate insights and visualizing the data with the help of Power BI.\n\nThe repository directory structure is as follows:\n\nBasketball-Players-Analysis\u003cbr\u003e\n├─ 01_ETL\u003cbr\u003e\n├─ 02_DATA\u003cbr\u003e\n├─ 03_ANALYSIS\u003cbr\u003e\n├─ 04_DASHBOARD\u003cbr\u003e\n├─ 05_RESOURCES\u003cbr\u003e\n\nThe type of content present in the directories is as follows:\n\n**01_ETL**\n\nThis directory contains the Python raw data file and Python ETL script that takes numpy matrix in the raw data file as input, transforms it and exports an analysis-ready dataset into the _02_DATA_ directory.\n\n**02_DATA**\n\nThis directory contains the data that can be directly used for exploratory data analysis and data visualization purposes.\n\n**03_ANALYSIS**\n\nThis directory contains the python notebooks that analyzes the clean dataset to generate insights\n\n**04_DASHBOARD**\n\nThis directory contains the python notebook with an embedded Power BI report that visualizes the data. The Power BI dashboard contains slicers, cross-filtering and other advance capabilities that end user can play with to visualize a specific facet of the data or, to get additional insights.\n\n**05_RESOURCES**\n\nThis directory contains images, icons, layouts, etc. that are used in this project\n\n## Prerequisites\n\nThe major skills that are required as prerequisite to fully understand this project are as follows:\n\n- Basics of Python\n- Python libraries: Numpy, Pandas, Matplotlib\n- Basics of Python Notebooks\n- Basics of Power BI\n\nIn order to complete the project, I've used the following applications and libraries\n\n- Python\n- Python libraries mentioned in requirements.txt file\n- Jupyter Notebook\n- Visual Studio Code\n- Microsoft Power BI\n\n\u003e The choice of applications \u0026 their installation might vary based on individual preferences \u0026 system settings.\n\n## Architecture\n\nThe project architecture is quite straight forward and can be explained through the below image:\n\n![Process Architecture][process_workflow]\n\nAs per the above workflow; we are first importing data present as numpy matrix from the Python file which is then processed and cleaned with another ETL specific Python script.\n\nFinally; we leverage the clean \u0026 analysis-ready dataset for some exploratory data analysis (EDA) using Jupyter Notebook and creating an insightful report using Power BI\n\n## Demo\n\nTo be updated.\n\n## Support\n\nIf you have any doubts, queries or, suggestions then, please connect with me in any of the following platforms:\n\n[![Linkedin Badge][linkedinbadge]][linkedin] [![Twitter Badge][twitterbadge]][twitter]\n\nIf you like my work then, you may support me at Patreon:\n\n\u003ca href=\"https://www.patreon.com/quantumudit\" target=\"_blank\"\u003e\n\u003cimg src=\"05_RESOURCES/become_a_patreon.png\" alt=\"git\" width=\"170\" height=\"50\"/\u003e\n\u003c/a\u003e\n\n## License\n\n\u003ca href = 'https://creativecommons.org/licenses/by-nc-sa/4.0/' target=\"_blank\"\u003e\n    \u003cimg src='05_RESOURCES/by-nc-sa.png' width=88 height=31\u003e\n\u003c/a\u003e\n\nThis license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.\n\n\u003c!-- Image Links --\u003e\n\n[project_logo]: 05_RESOURCES/project_cover_image.png\n[process_workflow]: 05_RESOURCES/process_architecture.png\n[scraping_graphic]: 05_RESOURCES/scraping_graphic.gif\n\n\u003c!-- External Links --\u003e\n\n[website_link]: https://www.mohfw.gov.in/\n\n\u003c!-- Profile Links --\u003e\n\n[linkedin]: https://www.linkedin.com/in/uditkumarchatterjee/\n[twitter]: https://twitter.com/quantumudit\n\n\u003c!-- Shields Profile Links --\u003e\n\n[linkedinbadge]: https://img.shields.io/badge/-uditkumarchatterjee-0e76a8?style=flat\u0026labelColor=0e76a8\u0026logo=linkedin\u0026logoColor=white\n[twitterbadge]: https://img.shields.io/badge/-@quantumudit-1ca0f1?style=flat\u0026labelColor=1ca0f1\u0026logo=twitter\u0026logoColor=white\u0026link=https://twitter.com/quantumudit\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fquantumudit%2Fbasketball-players-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fquantumudit%2Fbasketball-players-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fquantumudit%2Fbasketball-players-analysis/lists"}