{"id":13907047,"url":"https://github.com/amueller/dabl","last_synced_at":"2025-07-18T04:33:36.372Z","repository":{"id":41565915,"uuid":"237277559","full_name":"amueller/dabl","owner":"amueller","description":"Data Analysis Baseline Library","archived":false,"fork":true,"pushed_at":"2024-01-09T19:00:03.000Z","size":120629,"stargazers_count":130,"open_issues_count":1,"forks_count":9,"subscribers_count":5,"default_branch":"main","last_synced_at":"2024-08-07T23:49:51.600Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://dabl.github.io/","language":"Jupyter Notebook","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"dabl/dabl","license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/amueller.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}},"created_at":"2020-01-30T18:26:49.000Z","updated_at":"2024-07-17T02:59:01.000Z","dependencies_parsed_at":"2023-01-31T07:45:26.969Z","dependency_job_id":null,"html_url":"https://github.com/amueller/dabl","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amueller%2Fdabl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amueller%2Fdabl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amueller%2Fdabl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amueller%2Fdabl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/amueller","download_url":"https://codeload.github.com/amueller/dabl/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":226353547,"owners_count":17611721,"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":[],"created_at":"2024-08-06T23:01:46.841Z","updated_at":"2024-11-25T15:31:04.462Z","avatar_url":"https://github.com/amueller.png","language":"Jupyter Notebook","funding_links":[],"categories":["Sklearn实用程序","其他_机器学习与深度学习"],"sub_categories":[],"readme":"# dabl\n\n[![CI](https://github.com/dabl/dabl/actions/workflows/ci.yml/badge.svg)](https://github.com/dabl/dabl/actions/workflows/ci.yml)\n\nThe data analysis baseline library.\n\n- \"Mr Sanchez, are you a data scientist?\"\n- \"I dabl, Mr president.\"\n\nFind more information on the [website](https://dabl.github.io/).\n\n## Try it out\n\n```\npip install dabl\n```\n\nor [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/dabl/dabl/main)\n\n## Current scope and upcoming features\nThis library is very much still under development. Current code focuses mostly on exploratory visualization and preprocessing.\nThere are also drop-in replacements for GridSearchCV and RandomizedSearchCV using successive halfing.\nThere are preliminary portfolios in the style of\n[POSH\nauto-sklearn](https://ml.informatik.uni-freiburg.de/papers/18-AUTOML-AutoChallenge.pdf)\nto find strong models quickly.  In essence that boils down to a quick search\nover different gradient boosting models and other tree ensembles and\npotentially kernel methods.\n\nCheck out the [the website](https://dabl.github.io/dev/) and [example gallery](https://dabl.github.io/0.1.9/auto_examples/index.html) to get an idea of the visualizations that are available.\n\nStay Tuned!\n\n## Related packages\n\n## Lux\n[Lux](https://github.com/lux-org/lux) is an awesome project for easy interactive visualization of pandas dataframes within notebooks.\n\n### Pandas Profiling\n[Pandas Profiling](https://github.com/pandas-profiling/pandas-profiling) can\nprovide a thorough summary of the data in only a single line of code. Using the\n```ProfileReport()``` method, you are able to access a HTML report of your data\nthat can help you find correlations and identify missing data.\n\n`dabl` focuses less on statistical measures of individual columns, and more on\nproviding a quick overview via visualizations, as well as convienient\npreprocessing and model search for machine learning.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famueller%2Fdabl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Famueller%2Fdabl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famueller%2Fdabl/lists"}