Kernel density estimation instead of histogram
Maintainers usually reply within 1 day
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 30/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- data-visualization
Research direction
The issue proposes adding kernel density estimation as a complement to the existing histogram, but names no files, tests, or entry points. Start by locating the existing histogram implementation and its tests, then determine the KDE behavior and acceptance criteria before making changes.
Written by the indexing model from the issue text.
Description
I think it would be nice to include this as a complement to the existing histogram out of the box, as a KDE sidesteps the issues with selecting a correct bucket size for the histogram. I'm not really a stats person so I can't explain this very well, but Wikipedia has more info and you can see an example of this in use in the "criterion" benchmarking tool for Haskell: http://www.serpentine.com/criterion/fibber.html
- Dominant language
- Python
- Stars
- 967
- Forks
- 112
- Avg merge
- 5d 8h
- Merged PRs (30d)
- 9
Getting set up
This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.
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.
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