matplotlib / matplotlib/mpl_data_containers
Data library sources that are worth integrating with
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 10
- Forks
- 6
- PR merge metrics
- No merged PRs in 30d
Description
Some of these may be proof of concept level at best while they are under our control, but good to keep many in mind to avoid overspecializing and painting ourselves into a corner:
- numpy arrays (or rather dictionaries of numpy arrays)
- pandas
- xarray
- dask
- tiled
- WrightTools (It's my graduate work, so useful as a test bed for integrations into libraries themselves)
- raw h5py
- Zarr
- functions
- web APIs
- databases
- networkx (graph data rather than array-like)
Contributor 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.
Research direction
The issue lists possible integrations, including NumPy arrays, pandas, xarray, dask, tiled, WrightTools, h5py, Zarr, functions, web APIs, databases, and networkx, but names no files, tests, or entry points. Start by defining which source or sources are in scope and what integration behavior is required. Done is not specified beyond avoiding overspecialization and supporting useful data sources.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, pandas, python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100