{"id":13556226,"url":"https://github.com/datamade/data-analysis-guidelines","last_synced_at":"2025-04-03T09:31:03.373Z","repository":{"id":146795956,"uuid":"100283526","full_name":"datamade/data-analysis-guidelines","owner":"datamade","description":"📒 Analyzing Data, the DataMade Way","archived":true,"fork":false,"pushed_at":"2021-03-11T20:56:35.000Z","size":93,"stargazers_count":36,"open_issues_count":7,"forks_count":4,"subscribers_count":8,"default_branch":"master","last_synced_at":"2024-11-04T05:33:48.371Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Makefile","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/datamade.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":"2017-08-14T15:40:53.000Z","updated_at":"2024-02-18T09:54:08.000Z","dependencies_parsed_at":"2024-01-19T18:02:31.440Z","dependency_job_id":null,"html_url":"https://github.com/datamade/data-analysis-guidelines","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datamade%2Fdata-analysis-guidelines","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datamade%2Fdata-analysis-guidelines/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datamade%2Fdata-analysis-guidelines/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/datamade%2Fdata-analysis-guidelines/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/datamade","download_url":"https://codeload.github.com/datamade/data-analysis-guidelines/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246976185,"owners_count":20863031,"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":"2024-08-01T12:03:42.722Z","updated_at":"2025-04-03T09:31:03.005Z","avatar_url":"https://github.com/datamade.png","language":"Makefile","funding_links":[],"categories":["Makefile","others"],"sub_categories":[],"readme":"# Analyzing Data, the DataMade Way\n\n**⚠️ Deprecation warning**: *This documentation no longer represents DataMade's current best practices for data analysis. For contemporary guidance on data analysis, refer to the [`how-to`](https://github.com/datamade/how-to/tree/master/data-analysis) repo.*\n\nYou've [_extracted_ and _transformed_ the data](https://github.com/datamade/data-making-guidelines).\nNow it's time to _load_ (analyze) it. Here, you'll find the principles that\ninform DataMade's approach to data analysis, as well as the tools and\norganizational practices that make it possible.\n\n## Principles\n\nDataMade's approach to data analysis combines [our principles for making data](https://github.com/datamade/data-making-guidelines#basic-principles)\nwith the basic principles of [literate programming](https://en.wikipedia.org/wiki/Literate_programming).\n\nNamely, data analysis should:\n\n1. be **reproducible** with one command.\n2. be conducted using **standard tools**.\n3. be kept under **version control**.\n4. **prioritize legibility** to other humans.\n\n## Guides\n\n- **[Data analysis 001](/001-setting-up.md) - Setup**\n  - Setting up your environment\n  - Organizing your analysis\n- **[Data analysis 101](/101-intro-to-pweave.md) - Standard toolkit**\n  - Introduction to `pweave`\n- **[Data analysis 201](/201-multi-part-patterns.md) - Putting it all together**\n  - Patterns for multi-part analysis\n- **[Appendix A](/appendix_a-latex.md) - LaTeX**\n- **[Appendix B](/appendix_b-pandas.md) - pandas**\n- **[Appendix C](https://github.com/datamade/how-to/issues/34#issue-483477936) (external issue) – matplotlib**\n\n## Examples\n\nUnder construction in the `examples` dir! 👷\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatamade%2Fdata-analysis-guidelines","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatamade%2Fdata-analysis-guidelines","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatamade%2Fdata-analysis-guidelines/lists"}