Windowed operations (rolling average, etc.)
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- Dominant language
- Kotlin
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Description
Hello,
Kotlin offers the windowed function over iterables to create sub-lists of items along the data. This function can be used to calculate various metrics, such as moving averages and more.
Is this use case somehow supported in dataframe right now? Is it considered? It would be great to have a pretty way (even less tricky than using windowed), to quickly calculate moving averages, or any other more advanced functions which use rolling windows.
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
Start by reviewing the existing Kotlin DataFrame operations and comparing them with Kotlin's windowed function linked in the issue. Determine the intended rolling-window API and which moving-average or other rolling calculations should be supported. Done would require an agreed scope and implementation plan, but no files or tests are identified in the issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- kotlin
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100