Correlation Analysis handling of time properties
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- Python
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Description
Is your feature request related to a problem?
Correlation analysis on datetime based properties is mostly useless, since the aggregation here doesn't happen properly. It's rare for even two users to share the same time, upto the second.
Describe the solution you'd like
When doing correlation analysis, group time-based properties into intervals. Perhaps make this configurable. This allows correlation analysis to say that people with createdAt between 0 and 3 months are 10x more likely to ___.
Describe alternatives you've considered
None so far.
Additional context
cc: @joesaunderson for the good idea!
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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 locating the correlation analysis entry point and the aggregation handling for datetime properties. Define how time intervals should be represented and whether interval sizing is configurable. The work is done when datetime-based properties are grouped into meaningful intervals and correlation results can express ranges such as users created within a three-month period.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- analytics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100