johannfaouzi/pyts
A Python package for time series classification
This tool helps data analysts and researchers automatically categorize time series data, like stock prices over time or sensor readings, into predefined groups. You feed it your raw time series datasets, and it outputs classifications for each series, helping you identify patterns or anomalies. This is ideal for anyone who needs to make sense of sequential data and group similar behaviors together.
1,873 stars. Used by 3 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you need to build models that automatically assign categories to time-ordered sequences of data, like predicting equipment failures from sensor data or classifying financial market trends.
Not ideal if you are looking for a general-purpose machine learning library not specifically focused on time series, or if you only need to visualize time series data without classification.
Stars
1,873
Forks
180
Language
Python
License
BSD-3-Clause
Category
Last pushed
Jun 18, 2025
Commits (30d)
0
Dependencies
5
Reverse dependents
3
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/johannfaouzi/pyts"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
sktime/sktime
A unified framework for machine learning with time series
aeon-toolkit/aeon
A toolkit for time series machine learning and deep learning
Nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.