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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["data-mining","fp-growth","fpgrowth","machine-learning","python"],"created_at":"2026-01-14T09:38:41.947Z","updated_at":"2026-01-14T09:38:42.785Z","avatar_url":"https://github.com/chonyy.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=center\u003e\n    \u003cimg src=\"fpgrowth.PNG\" width=\"468\" height=\"303\"\u003e\n\u003c/p\u003e\n\n\u003cp align=center\u003e\n    \u003ca target=\"_blank\" href=\"#\" title=\"pip\"\u003e\u003cimg src=\"https://img.shields.io/pypi/v/fpgrowth_py?color=brightgreen\"\u003e\u003c/a\u003e\n    \u003ca target=\"_blank\" href=\"#\" title=\"language count\"\u003e\u003cimg src=\"https://img.shields.io/github/languages/count/chonyy/fpgrowth_py\"\u003e\u003c/a\u003e\n    \u003ca target=\"_blank\" href=\"#\" title=\"top language\"\u003e\u003cimg src=\"https://img.shields.io/github/languages/top/chonyy/fpgrowth_py?color=orange\"\u003e\u003c/a\u003e\n    \u003ca target=\"_blank\" href=\"https://opensource.org/licenses/MIT\" title=\"License: MIT\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-MIT-blue.svg\"\u003e\u003c/a\u003e\n    \u003ca target=\"_blank\" href=\"#\" title=\"repo size\"\u003e\u003cimg src=\"https://img.shields.io/github/repo-size/chonyy/fpgrowth_py\"\u003e\u003c/a\u003e\n    \u003ca target=\"_blank\" href=\"http://makeapullrequest.com\" title=\"PRs Welcome\"\u003e\u003cimg src=\"https://img.shields.io/badge/PRs-welcome-brightgreen.svg\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n## How to use\n\n### Install the Pypi package using pip\n\n```\npip install fpgrowth_py\n```\n\nThen use it like \n\n```python\nfrom fpgrowth_py import fpgrowth\nitemSetList = [['eggs', 'bacon', 'soup'],\n                ['eggs', 'bacon', 'apple'],\n                ['soup', 'bacon', 'banana']]\nfreqItemSet, rules = fpgrowth(itemSetList, minSupRatio=0.5, minConf=0.5)\nprint(freqItemSet)\nprint(rules)  \n# [[{'beer'}, {'rice'}, 0.6666666666666666], [{'rice'}, {'beer'}, 1.0]]\n# rules[0] --\u003e rules[1], confidence = rules[2]\n```\n\n### Clone the repo\n\nGet a copy of this repo using git clone\n```\ngit clone https://github.com/chonyy/fpgrowth_py.git\n```\n\nRun the program with dataset provided and **default** values for *minSupport* = 0.5 and *minConfidence* = 0.5\n\n```\npython fpgrowth.py -f dataset.csv\n```\n\nRun program with dataset and min support and min confidence  \n\n```\npython fpgrowth.py -f tesco2.csv -s 0.5 -c 0.5\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchonyy%2Ffpgrowth_py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchonyy%2Ffpgrowth_py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchonyy%2Ffpgrowth_py/lists"}