Skip to main content

Library with compilation of features for time series

Project description

This is a fork of https://github.com/isadoranun/FATS focused on a high performance and low computation time.


Installation: Clone this repository and do python setup.py install. Don’t forget to install GCC of version 12.1.0 or higher.

Or pip install FFATS for the latest stable version.


An extended explanation of the original package is available at http://isadoranun.github.io/tsfeat/FeaturesDocumentation.html

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ffats-1.3.8.tar.gz (20.4 kB view details)

Uploaded Source

File details

Details for the file ffats-1.3.8.tar.gz.

File metadata

  • Download URL: ffats-1.3.8.tar.gz
  • Upload date:
  • Size: 20.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for ffats-1.3.8.tar.gz
Algorithm Hash digest
SHA256 f092038df3032868c38581f4acb7254d1d33f74683ad7ea14f3da004536ba6d5
MD5 8b13f79293fe3015349c32ebe8513c01
BLAKE2b-256 2494d7a247b71bb42be6b3f4e85c2db0b6845a319685ecb72a2c0d03f483201d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page