pymc-labs / pymc-labs/CausalPy
Time series decomposition plots for BSTS
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- Dominant language
- Python
- Stars
- 1.2k
- Forks
- 115
- Avg merge
- 6d 1h
- Merged PRs (30d)
- 11
Description
AFTER https://github.com/pymc-labs/CausalPy/issues/52 IS CLOSED
At that point we can add additional time series decomposition plots, such as trend, seasonality (monthly/yearly), residuals.
This could be expanded beyond just the time series component and be more like a holistic contribution-over-time plot, which could incorporate contributions from all drivers.
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
First check whether issue #52 is closed, since this work is explicitly blocked on it. No files, tests, or plotting entry points are named; inspect the BSTS implementation and existing plot APIs to determine where trend, monthly/yearly seasonality, residuals, and broader driver contributions belong. Done means the intended decomposition plots are implemented with clear scope and coverage.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- 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