Migrate classification user guide off datashader

Open
#3,457 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
68/100
Issue type
Refactor
Clarity
Clearly specified
Activity status
Quiet
Tech stack
matplotlib, python
Domain
data-visualization, documentation

Research direction

Start with docs/source/user_guide/classification.ipynb and run the notebook from top to bottom to inspect its current outputs. Replace the datashader-based aggregation and rendering as described, update the workflow prose, and re-execute it so the notebook and preview image produce the expected plots without importing datashader.

Written by the indexing model from the issue text.

Description

area:analysis documentation user-guide-example

Reason or Problem

docs/source/user_guide/classification.ipynb imports datashader, uses Canvas to aggregate values into a raster for the classification examples, and renders with shade/stack.

Proposal

  • Remove the datashader imports.
  • Replace the Canvas aggregation with arr.xrs.rasterize(...).
  • Replace shade/stack and datashader colormaps with matplotlib.
  • Update the prose cells that describe the datashader workflow.
  • Re-execute the notebook so outputs and the preview image regenerate cleanly.

Done when

  • The notebook runs top to bottom with no datashader import and produces the expected plots.

Part of removing datashader as a dependency; final packaging removal is tracked in #3450.

Dominant language
Python
Stars
972
Forks
92
Avg merge
2d 12h
Merged PRs (30d)
7

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from xarray-contrib/xarray-spatial

All issues in xarray-contrib/xarray-spatial

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.