{"id":21195260,"url":"https://github.com/szapp/candyanalysis","last_synced_at":"2026-04-28T19:33:37.749Z","repository":{"id":249607435,"uuid":"831008952","full_name":"szapp/CandyAnalysis","owner":"szapp","description":"Case study: Analyze the candy power ranking to identify and recommend popular candy characteristics","archived":false,"fork":false,"pushed_at":"2024-07-22T06:08:56.000Z","size":992,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-14T21:39:46.044Z","etag":null,"topics":["data-analysis","data-visualization","feature-selection","interaction-terms"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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characteristics.\n\nThe dataset by FiveThirtyEight is distributed un the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/).\n\n## Project\n\nThe production of a new candy is planned.\nAmong the project team there is no consensus about the characteristics of the candy.\n\nBased on a dataset from market analysis, the task is to give a clear recommendation for what characteristics the new product should express.\n\n## Deliverable\n\nThe results are compiled in a [presentation](Presentation.pdf) with a clear recommendation.\nThe presentation is in German, but the numbers speak for themselves.\n\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/3a7f5069-f299-4b35-95c1-1d13146ae950\" width=400\u003e \u003cimg src=\"https://github.com/user-attachments/assets/ea37f378-6052-496f-b6de-6070cbe091e1\" width=400\u003e\n\u003cbr\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/224de4a4-b659-4a43-8244-dc814a8173b0\" width=400\u003e \u003cimg src=\"https://github.com/user-attachments/assets/e6e38600-ea02-4107-b738-cd5a5b72e42e\" width=400\u003e\n\u003c/div\u003e\n\n## Libraries used\n\n- Scipy\n- Scikit-learn\n- Seaborn\n\n\u003csup\u003e*See [requirements.txt](requirements.txt).*\u003c/sup\u003e\n\n## Challenges\n\n- Small dataset (86 rows/samples)\n- Data is aggregated over brands (e.g. win percentage)\n- Study design might not be fair (not blind)\n\n## Approach\n\nTreating the problem not as a regression but as a classification and using statistical analysis allows to identify features that are statistically dependent with popular brands.\nWith interaction terms, the combination of successful characteristics can be recommended.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fszapp%2Fcandyanalysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fszapp%2Fcandyanalysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fszapp%2Fcandyanalysis/lists"}