matplotlib / matplotlib/napari-matplotlib

Integrate with tabular functionality

Open
#66 1 comment 2 reactions 0 assignees View on GitHub
New feature
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

No contributing guide indexed for this repository

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

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.