Analysis updated 2026-07-17 · repo last pushed 2013-11-25
Prepare a tidy dataset and code book before sending data to a statistician for analysis.
Document the exact steps used to transform raw data into a clean, analyzable format.
Avoid common data-sharing mistakes like messy multi-sheet Excel files with colored cells.
| tanykim/coursera-datasharing | 00kaku/gallery-slider-block | 04amanrajj/netwatch | |
|---|---|---|---|
| Stars | — | — | 0 |
| Language | — | JavaScript | Rust |
| Last pushed | 2013-11-25 | 2021-05-19 | — |
| Maintenance | Dormant | Dormant | — |
| Setup difficulty | easy | easy | moderate |
| Complexity | 1/5 | 2/5 | 3/5 |
| Audience | researcher | general | ops devops |
Figures from each repo's GitHub metadata at analysis time.
A practical guide explaining how to prepare and package data (raw data, tidy data, code book, and processing steps) for a statistician.
Dormant — no commits in 2+ years (last push 2013-11-25).
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.