{"id":23907725,"url":"https://github.com/danymukesha/pca-pwa","last_synced_at":"2025-10-27T22:02:21.807Z","repository":{"id":215933041,"uuid":"740026322","full_name":"danymukesha/pca-pwa","owner":"danymukesha","description":"simplified manner for insights and decision-making by visualizing complex relationships with PCA web application","archived":false,"fork":false,"pushed_at":"2024-01-21T08:48:48.000Z","size":206,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-05T04:06:06.134Z","etag":null,"topics":["pca","statistics","unsupervised-learning"],"latest_commit_sha":null,"homepage":"https://pypi.org/project/pca-pwa/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/danymukesha.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":"2024-01-07T09:47:06.000Z","updated_at":"2024-12-03T20:42:34.000Z","dependencies_parsed_at":"2024-01-13T18:59:31.564Z","dependency_job_id":null,"html_url":"https://github.com/danymukesha/pca-pwa","commit_stats":null,"previous_names":["danymukesha/pca-pwa"],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danymukesha%2Fpca-pwa","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danymukesha%2Fpca-pwa/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danymukesha%2Fpca-pwa/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danymukesha%2Fpca-pwa/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/danymukesha","download_url":"https://codeload.github.com/danymukesha/pca-pwa/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240331318,"owners_count":19784643,"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":["pca","statistics","unsupervised-learning"],"created_at":"2025-01-05T03:14:09.673Z","updated_at":"2025-10-27T22:02:21.722Z","avatar_url":"https://github.com/danymukesha.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pca-pwa\r\n\r\n[![Python Tests](https://github.com/danymukesha/pca-pwa/actions/workflows/main.yml/badge.svg)](https://github.com/danymukesha/pca-pwa/actions/workflows/main.yml)\r\n\r\n`pca-pwa`, a simplified manner for insights and decision-making by visualizing complex relationships with PCA web application.\r\n\r\n### The Purpose of the Package\r\n- The purpose of the package is to offer a simple way of visualizing relatationships between items of any given dataset. \r\nThe user could easily obtain a pca plot without needing to configure or compile the application.\r\n\r\n### Installation\r\nTo install `pca_pwa`, you can use pip. Open your terminal and run:\r\n\r\n```sh\r\npip install pca_pwa\r\n```\r\nOpen `IPython` or `Jupyter Notebook`\r\n```python\r\n\u003e\u003e\u003e from pca_pwa import app\r\n\u003e\u003e\u003e app.app.run(debug=True, use_reloader=True, host='0.0.0.0', port=8082)\r\n\u003e\u003e\u003e # * Serving Flask app 'app'\r\n\u003e\u003e\u003e # * Debug mode: on\r\n\u003e\u003e\u003e # * Running on http://127.0.0.1:8082\r\n```\r\n\r\nOpen the url: http://127.0.0.1:8082\r\n\r\n![image](https://github.com/danymukesha/pca-pwa/assets/45208254/03c32efa-3873-4173-9682-877c51aefdd6)\r\n\r\nUpload `xslx/slx` file (Excel) \r\n\r\n- e.g.:\r\n  - Click [here](https://github.com/danymukesha/pca-pwa/raw/main/tests/samples_file.xlsx) to download the excel file\r\n    * Items/Observations should be in rows\r\n    * Variables/Features should in columns\r\n      \r\n        - **Standard Data (table) Format**\r\n        \r\n        The example of standard data format to be used while uploading to pca-pwa web app is a dataframe from sample names\r\n        in the first column, and the rest (e.g.: metabolites, genes, RNA, etc.) for each sample in the following columns (see Table 1).\r\n        \r\n        **Table 1:** ***Standard data table format.***\r\n        \r\n        | Sample | Met 1   | Met 2   | Met 3   | ...     | Met N   |\r\n        |--------|---------|---------|---------|---------|---------|\r\n        | S1     | 99,380  | 10.177  | 51.484  | ...     | 71.882  |\r\n        | S2     | 101.195 | 10.786  | 50.446  | ...     | 73.318  |\r\n        | S3     | 102.165 | 9,375   | 49.668  | ...     | 72,056  |\r\n        | S4     | 99.481  | 8.291   | 48.111  | ...     | 73.282  |\r\n        | S5     | 101.282 | 10.867  | 50.209  | ...     | 73,572  |\r\n        | S6     | 99.43   | 9.95    | 47.602  | ...     | 71,983  |\r\n\r\n\r\nChoose a method of imputation for missing values.\r\n\r\nThen run the pca by clicking ``Perform PCA`` button.\r\n\r\n![image](https://github.com/danymukesha/pca-pwa/assets/45208254/a25bf538-599e-4353-80e4-a26963e4d721)\r\n\r\n---------\r\n\r\nOtherwise you can use `git clone`:\r\n\r\nHere is the [Usage](https://github.com/danymukesha/pca-pwa/blob/main/Usage.md):\r\n\r\nClone the github repository\r\n\r\n```git\r\ngit clone https://github.com/danymukesha/pca-pwa.git\r\n```\r\n\r\nRun the app\r\n\r\n```sh\r\ncd pca-pwa\r\npython3.1 pca-pwa/app.y\r\n\r\n# * Serving Flask app 'app'\r\n# * Debug mode: on\r\n# * Running on http://127.0.0.1:8082\r\n```\r\n\r\nOpen the url: http://127.0.0.1:8082\r\n\r\n### License\r\nThis project is licensed under the MIT License.\r\n\r\n### Credits\r\nAuthor: MIT © [Dany Mukesha](https://danymukesha.github.io/)\r\n\r\nEmail: danymukesha@gmail.com\r\n\r\nThank you for using `pca_pwa`!\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanymukesha%2Fpca-pwa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdanymukesha%2Fpca-pwa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanymukesha%2Fpca-pwa/lists"}