Timestamp format
- Dominant language
- Python
- Stars
- 1.2k
- Forks
- 217
- PR merge metrics
- No merged PRs in 30d
Description
Hi
i'm looking for toolkits for timeseries anomaly detection, i think this cloud help me but i didn't understand how to exactly work with luminol, how is the data format or the input format,can some one provide me with a simple example, for example i have a .csv file with values and date/time and i want to detect anomalies.. what format should i use for input?
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reviewing luminol's existing documentation and input-handling guidance for time series data. Add a simple CSV example showing the expected date/time and value format, and make the documented input requirements clear enough for a user to run anomaly detection.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100