matplotlib / matplotlib/napari-matplotlib
Integrate with tabular functionality
- Dominant language
- Python
- Stars
- 46
- Forks
- 24
- PR merge metrics
- No merged PRs in 30d
Description
Hi @dstansby ,
I was recently discussing with @zoccoler about how to further improving napari-matplotlib. One thing that appeared to be a natural extension for plotting functionality would be the support for some sort of tabular interaction: Clicking on column heads could trigger the display of feature scatter/histogram plots, similarly for metadata. We could introduce standardized column headers (`label` already exists) such as `frame` for the time dimension, etc.
Now such things obviously already exist (e.g., in the scope of [napari-spreadsheet](https://www.napari-hub.org/plugins/napari-spreadsheet)) and it would be superfluous effort to create this functionality from scratch. Another place where tabular functionality exists (and is actively used) is [napari-skimage-regionprops](https://www.napari-hub.org/plugins/napari-skimage-regionprops) (see [code here](https://github.com/haesleinhuepf/napari-skimage-regionprops/blob/master/napari_skimage_regionprops/_table.py)).
## Pitch:
In order to make the most of both functionality (current napari-matplotlib and table from napari-skimage-regionprops), we suggest to join efforts and merge these two pieces of code under one hood. This would greatly enhance the reach of napari-matplotlib, its usability and spread the effort of maintenance over more shoulders.
Would love to hear your thoughts!
Also tagging @haesleinhuepf as the maintainer of napari-skimage-regionprops
Contributor guide
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Research direction
Start by reviewing the existing napari-matplotlib plotting functionality and the referenced napari-skimage-regionprops/_table.py implementation. Clarify whether the goal is code integration, standardized column headers, or interactions with napari-spreadsheet; done would require an agreed scope and an explicit integration plan.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- matplotlib, python
- Domain
- data-visualization
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100