[Analysis] Data Reliability Score
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 20/100
- Issue type
- Refactor
- Clarity
- Needs clarification
- Activity status
- Quiet
- Domain
- data
Research direction
The issue provides no file, test, or entry point, and refers to an implementation discussed in issue #221. Start by reviewing that referenced implementation and the listed production limitations; the issue does not define a concrete change or completion criteria.
Written by the indexing model from the issue text.
Description
Adding for reference
This implementation is not ready for production because:
- it relies on computed indicators (not present in the script - the prerequisite would be to have a package that compute indicator for any household survey, which we do not have yet)
- does not generalize checks (i.e. relies on specific livelihood coping strategies present in the dataset)
- is it not efficient (i.e. checks 10000 variables to see if 9999 is present)
- it cannot be called from an another piece of code (i.e. cannot be automated)
- does not have validations and does not handle errors (i.e. the code will crash if the input data is not what it expects)
Originally posted by @AlexGherardelli in https://github.com/WFP-VAM/RAMResourcesScripts/issues/221#issuecomment-4388198331
- Dominant language
- Scheme
- Stars
- 35
- Forks
- 32
- Avg merge
- 1d 1h
- Merged PRs (30d)
- 4
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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