Deltares / Deltares/imod-python
Expand documentation for IPF writer
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documentation
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- Python
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Description
In GitLab by @Huite on Feb 14, 2019, 15:47
The IPF writer makes a significant number of non-obvious assumptions about the dataframe to write.
Off the top of my head:
- Long table format (vs wide), with suggestion that pandas.melt is quite useful in this regard.
- A real-world example of wide vs long format data, e.g. a set of timeseries of boreholes.
- A clear specification of what the minimum necessary columns (and names) are for the different ipf types.
- Maybe a few examples + samples of the output (e.g. non-unique columns are written to "mother" IPF).
Contributor guide
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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.
Research direction
Start with the IPF writer and review how it handles dataframe shape, required columns, IPF types, and non-unique columns. Use pandas.melt when preparing long-format examples, and document wide versus long data, minimum column names, and representative output including the mother IPF. Done means the writer's non-obvious assumptions and examples are clearly covered.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100