docs/reference/.github/ISSUE_TEMPLATE/data_accuracy.md

In aclu-national/LibLabReviews: Encourage Effective Peer Review Practices with Useful Tooling

name: Data Accuracy about: Errors in raw or interim data which need to be checked title: '[Data Accuracy] [ISSUE TITLE]' labels: 'Data Accuracy :microscope:'

Data / Results

How'd You Find this Issue

- [ ] Spot check (eg randomly reviewed X rows from a dataset) - [ ] Fan out detection (eg number of rows increased somewhere) - [ ] Assertions / Tests (eg unit tests, formal expectations) - [ ] Informal Checks (eg added a bit of code to print summary statistic) - [ ] dbt tests (eg using reporting tables and included tests in dbt) - [ ] Comparison to alternatives (eg looked at a different report and similar number was wildly different) - [ ] Visualization (eg histogram had weird and unexpected values)

Possible Reasons for Error

Solutions

Possible Regression Prevention Measures

Context (Environment)

Reprodicibility Recceipt

# Datetime
Sys.time()

# Repo
git2r::repository()

# Session Info
sessioninfo::session_info()

aclu-national/LibLabReviews documentation built on Aug. 20, 2020, 7:23 a.m.