https://github.com/datamade/data-analysis-guidelines

📒 Analyzing Data, the DataMade Way
https://github.com/datamade/data-analysis-guidelines

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📒 Analyzing Data, the DataMade Way

• Host: GitHub
• URL: https://github.com/datamade/data-analysis-guidelines
• Owner: datamade
• License: mit
• Archived: true
• Created: 2017-08-14T15:40:53.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2021-03-11T20:56:35.000Z (almost 4 years ago)
• Last Synced: 2024-08-01T12:36:30.191Z (4 months ago)
• Language: Makefile
• Size: 90.8 KB
• Stars: 36
• Watchers: 8
• Forks: 4
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Analyzing Data, the DataMade Way

**⚠️ Deprecation warning**: *This documentation no longer represents DataMade's current best practices for data analysis.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.*

You've [_extracted_ and _transformed_ the data](https://github.com/datamade/data-making-guidelines).

Now it's time to _load_ (analyze) it. Here, you'll find the principles that

inform DataMade's approach to data analysis, as well as the tools and

organizational practices that make it possible.

## Principles

DataMade's approach to data analysis combines [our principles for making data](https://github.com/datamade/data-making-guidelines#basic-principles)

with the basic principles of [literate programming](https://en.wikipedia.org/wiki/Literate_programming).

Namely, data analysis should:

1. be **reproducible** with one command.

2. be conducted using **standard tools**.

3. be kept under **version control**.

4. **prioritize legibility** to other humans.

## Guides

- **[Data analysis 001](/001-setting-up.md) - Setup**

  - Setting up your environment

  - Organizing your analysis

- **[Data analysis 101](/101-intro-to-pweave.md) - Standard toolkit**

  - Introduction to `pweave`

- **[Data analysis 201](/201-multi-part-patterns.md) - Putting it all together**

  - Patterns for multi-part analysis

- **[Appendix A](/appendix_a-latex.md) - LaTeX**

- **[Appendix B](/appendix_b-pandas.md) - pandas**

- **[Appendix C](https://github.com/datamade/how-to/issues/34#issue-483477936) (external issue) – matplotlib**

## Examples

Under construction in the `examples` dir! 👷