williambdean/latent-calendar

Analyze and model weekly calendar distributions using latent components

45
/ 100
Emerging

This helps you understand and predict recurring patterns in activities that happen throughout the week. You provide data points marked with their day and time, and it helps you see underlying weekly schedules or 'calendars' that drive these events. A data analyst, researcher, or anyone studying weekly behavioral trends would find this useful.

Available on PyPI.

Use this if you need to identify and model the distinct weekly rhythms present in your time-stamped activity data.

Not ideal if your data patterns are primarily driven by daily, monthly, or yearly cycles rather than weekly ones.

time-series-analysis behavioral-analytics scheduling-optimization event-patterning workforce-planning
Maintenance 10 / 25
Adoption 6 / 25
Maturity 25 / 25
Community 4 / 25

How are scores calculated?

Stars

21

Forks

1

Language

Python

License

BSD-3-Clause

Last pushed

Mar 09, 2026

Commits (30d)

0

Dependencies

5

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