{"id":13400317,"url":"https://github.com/fmv1992/data_utilities","last_synced_at":"2025-03-14T06:31:38.275Z","repository":{"id":57417955,"uuid":"85405083","full_name":"fmv1992/data_utilities","owner":"fmv1992","description":"Data utilities library focused on machine learning and data analysis.","archived":true,"fork":false,"pushed_at":"2019-10-12T21:19:39.000Z","size":235,"stargazers_count":5,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-09-21T12:09:32.541Z","etag":null,"topics":["data-science","utility-library"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/fmv1992.png","metadata":{"files":{"readme":"readme.md","changelog":"changelog.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-03-18T13:55:58.000Z","updated_at":"2023-01-28T00:00:06.000Z","dependencies_parsed_at":"2022-09-03T09:41:37.285Z","dependency_job_id":null,"html_url":"https://github.com/fmv1992/data_utilities","commit_stats":null,"previous_names":[],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fmv1992%2Fdata_utilities","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fmv1992%2Fdata_utilities/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fmv1992%2Fdata_utilities/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fmv1992%2Fdata_utilities/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/fmv1992","download_url":"https://codeload.github.com/fmv1992/data_utilities/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":221440179,"owners_count":16821599,"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-science","utility-library"],"created_at":"2024-07-30T19:00:50.579Z","updated_at":"2024-10-25T16:30:20.246Z","avatar_url":"https://github.com/fmv1992.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"[![Build Status](https://travis-ci.org/fmv1992/data_utilities.svg?branch=master)](https://travis-ci.org/fmv1992/data_utilities)\n\n# Data Utilities\n\nThis module provides some helper functions and conveniences for working with\ndata analysis in python.\n\nIt depends on:\n\n* Numpy\n* Scipy\n* Pandas\n* Matplotlib\n* Seaborn\n* Scikit-learn\n\n# Organization and files\n\n    .\n    ├── data_utilities\n    │   ├── __init__.py\n    │   ├── matplotlib_utilities.py\n    │   ├── pandas_utilities.py\n    │   ├── python_utilities.py\n    │   ├── sklearn_utilities\n    │   │   ├── grid_search.py\n    │   │   └── __init__.py\n    │   └── tests\n    │       ├── __init__.py\n    │       ├── test_matplotlib_utilities.py\n    │       ├── test_pandas_utilities.py\n    │       ├── test_python_utilities.py\n    │       ├── test_sklearn_utilities.py\n    │       └── test_support.py\n    ├── LICENSE\n    ├── MANIFEST.in\n    ├── readme.md\n    └── setup.py\n\nEach of python's significant data modules has its own set of helper functions.\n\nThis module does not intend to create its own API or standards. Instead each of\nthe utilities module should follow the guidelines and APIs provided by the\nparent module.\n\nNote: This is a primitive project. Expect backwards incompatible changes as I\nfigure out the best way to to develop the utilities.\n\n# What's new\n\n* **Added `sklearn_utilities`**.\n* Improved tests customization in `du.test`.\n* Greatly improved documentation to `matplotlib_utilities`.\n* Greatly expanded `pandas_utilities` functions.\n* Improved tests as a whole.\n\n# Development guidelines\n\n* Coding style: [PEP 8](https://www.python.org/dev/peps/pep-0008/) compliant.\n* Docstrings: [google docstrings](http://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html).\n* Before commiting new versions do a test for different versions of python3:\n    * python3.4\n    * python3.5\n    * python3.6\n    * (newer versions)\n    * Rationale: even though stability is expected between python versions some\n      changes occur. See for instance that on commit v1.2.8 (60573d7) there was\n      as unexpected import error on python34 but not on python36.\n\n\n* Support first the test interface of numpy:\n\n        `python3 -c \"import data_utilities as du; du.test()\"`\n  and then the unittest interface:\n\n        `python3 -m unittest discover -vvv data_utilities/tests`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffmv1992%2Fdata_utilities","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffmv1992%2Fdata_utilities","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffmv1992%2Fdata_utilities/lists"}