{"id":18326856,"url":"https://github.com/franzdiebold/data-science-cheat-sheets","last_synced_at":"2025-06-20T06:06:10.964Z","repository":{"id":37404785,"uuid":"485827794","full_name":"FranzDiebold/data-science-cheat-sheets","owner":"FranzDiebold","description":"A collection of Data Science cheat sheets.","archived":false,"fork":false,"pushed_at":"2022-11-02T15:08:48.000Z","size":8255,"stargazers_count":44,"open_issues_count":0,"forks_count":10,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-09T16:53:14.387Z","etag":null,"topics":["cheat-sheet","cheat-sheets","data-science","pandas"],"latest_commit_sha":null,"homepage":"","language":null,"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/FranzDiebold.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null},"funding":{"github":"FranzDiebold"}},"created_at":"2022-04-26T14:45:00.000Z","updated_at":"2025-04-08T23:45:59.000Z","dependencies_parsed_at":"2023-01-21T05:18:21.812Z","dependency_job_id":null,"html_url":"https://github.com/FranzDiebold/data-science-cheat-sheets","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/FranzDiebold/data-science-cheat-sheets","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FranzDiebold%2Fdata-science-cheat-sheets","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FranzDiebold%2Fdata-science-cheat-sheets/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FranzDiebold%2Fdata-science-cheat-sheets/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FranzDiebold%2Fdata-science-cheat-sheets/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/FranzDiebold","download_url":"https://codeload.github.com/FranzDiebold/data-science-cheat-sheets/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/FranzDiebold%2Fdata-science-cheat-sheets/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260891143,"owners_count":23077909,"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":["cheat-sheet","cheat-sheets","data-science","pandas"],"created_at":"2024-11-05T19:08:27.335Z","updated_at":"2025-06-20T06:06:05.937Z","avatar_url":"https://github.com/FranzDiebold.png","language":null,"funding_links":["https://github.com/sponsors/FranzDiebold"],"categories":[],"sub_categories":[],"readme":"# Data Science cheat sheets\n\nA collection of Data Science cheat sheets.\n\n## Table of contents\n\n- [Data Extraction](#data-extraction)\n  - [SQL](#sql)\n  - [Python Regular expressions](#python-regular-expressions)\n- [Data Processing](#data-processing)\n  - [Polars](#polars)\n  - [Pandas](#pandas)\n  - [PySpark](#pyspark)\n- [Computer Vision](#computer-vision)\n  - [OpenCV](#opencv)\n- [Visualization](#visualization)\n  - [Plotly Express](#plotly-express)\n  - [Choosing a good chart](#choosing-a-good-chart)\n  - [Chart guide](#chart-guide)\n- [Modeling](#modeling)\n  - [Keras](#keras)\n- [Infrastructure](#infrastructure)\n  - [Docker](#docker)\n\n## Data Extraction\n\n### SQL\n\n[![SQL cheat sheet](images/sql-cheat-sheet.png)](cheat-sheets/sql-cheat-sheet.pdf)\n\nSource: [https://learnsql.com/tags/cheat-sheet/](https://learnsql.com/tags/cheat-sheet/)\n\n### [Python Regular expressions](https://docs.python.org/3/library/re.html)\n\n[![Python regular expressions cheat sheet](images/Python-regular-expressions-cheat-sheet.png)](cheat-sheets/Python-regular-expressions-cheat-sheet.pdf)\n\nSource: [https://www.dataquest.io/blog/regex-cheatsheet/](https://www.dataquest.io/blog/regex-cheatsheet/)\n\n## Data Processing\n\n### [Polars](https://www.pola.rs/)\n\n[![Polars cheat sheet](https://franzdiebold.github.io/polars-cheat-sheet/Polars_cheat_sheet.png)](https://franzdiebold.github.io/polars-cheat-sheet/Polars_cheat_sheet.pdf)\n\nSource: [FranzDiebold/polars-cheat-sheet](https://github.com/FranzDiebold/polars-cheat-sheet)\n\n### [Pandas](https://pandas.pydata.org/)\n\n[![Pandas cheat sheet](images/Pandas-cheat-sheet.png)](cheat-sheets/Pandas-cheat-sheet.pdf)\n\nSource: [https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf](https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf)\n\n### [PySpark](https://spark.apache.org/docs/latest/api/python/)\n\n[![PySpark cheat sheet](images/PySpark-cheat-sheet.png)](cheat-sheets/PySpark-cheat-sheet.pdf)\n\nSource: [https://www.datacamp.com/cheat-sheet/pyspark-cheat-sheet-spark-dataframes-in-python](https://www.datacamp.com/cheat-sheet/pyspark-cheat-sheet-spark-dataframes-in-python)\n\n## Computer Vision\n\n### [OpenCV](https://opencv.org/)\n\n[![OpenCV cheat sheet](images/OpenCV-cheat-sheet.png)](cheat-sheets/OpenCV-cheat-sheet.pdf)\n\nSource: [https://github.com/a-anjos/python-opencv](https://github.com/a-anjos/python-opencv)\n\n## Visualization\n\n### [Plotly Express](https://plotly.com/python/plotly-express/)\n\n[![Plotly Express cheat sheet](https://franzdiebold.github.io/plotly-express-cheat-sheet/Plotly_Express_cheat_sheet.png)](https://franzdiebold.github.io/plotly-express-cheat-sheet/Plotly_Express_cheat_sheet.pdf)\n\nSource: [FranzDiebold/plotly-express-cheat-sheet](https://github.com/FranzDiebold/plotly-express-cheat-sheet)\n\n### Choosing a good chart\n\n[![Choosing a good chart](images/choosing-a-good-chart.png)](cheat-sheets/choosing-a-good-chart.pdf)\n\nSource: [https://www.tapclicks.com/resources/blog/data-visualization-types/](https://www.tapclicks.com/resources/blog/data-visualization-types/)\n\n### Chart guide\n\n[![Chart Guide](images/ChartGuide.png)](cheat-sheets/ChartGuide.pdf)\n\nSource: [https://chart.guide/poster/](https://chart.guide/poster/)\n\n## Modeling\n\n### [Keras](https://keras.io/)\n\n[![Keras cheat sheet](images/Keras-cheat-sheet.png)](cheat-sheets/Keras-cheat-sheet.pdf)\n\nSource: [https://www.datacamp.com/cheat-sheet/keras-cheat-sheet-neural-networks-in-python](https://www.datacamp.com/cheat-sheet/keras-cheat-sheet-neural-networks-in-python)\n\n## Infrastructure\n\n### [Docker](https://www.docker.com/)\n\n[![Docker cheat sheet](images/Docker-cheat-sheet.png)](cheat-sheets/Docker-cheat-sheet.pdf)\n\nSources:\n\n- [https://www.lostindetails.com/cheatsheet/docker/docker_blue_light1.pdf](https://www.lostindetails.com/cheatsheet/docker/docker_blue_light1.pdf)\n- [https://dockerlux.github.io/pdf/cheat-sheet-v2.pdf](https://dockerlux.github.io/pdf/cheat-sheet-v2.pdf)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffranzdiebold%2Fdata-science-cheat-sheets","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffranzdiebold%2Fdata-science-cheat-sheets","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffranzdiebold%2Fdata-science-cheat-sheets/lists"}