A collection of Scikit-Learn compatible time series transformers and tools.
Project description
tsfeast
A collection of Scikit-Learn compatible time series transformers and tools.
Installation
pip install tsfeast
Documentation
Documentation hosted on Github Pages: https://chris-santiago.github.io/tsfeast/
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tsfeast-0.1.1.tar.gz
(34.0 kB
view details)
Built Distribution
tsfeast-0.1.1-py3-none-any.whl
(13.0 kB
view details)
File details
Details for the file tsfeast-0.1.1.tar.gz
.
File metadata
- Download URL: tsfeast-0.1.1.tar.gz
- Upload date:
- Size: 34.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f6894981480bb2645fa25ab3dbe3a983d03c23635d7f307874246b59174975db |
|
MD5 | d4b606deb2f9200a342d0107b597f54b |
|
BLAKE2b-256 | 7c198f4296c97dd76b7e82983bccb071011e1cfec8ec85e196ded153beab7949 |
File details
Details for the file tsfeast-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: tsfeast-0.1.1-py3-none-any.whl
- Upload date:
- Size: 13.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.15
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ae42087db2b3470392e3a87d355bdf89b45597b5cbc7bde80b7397843af33812 |
|
MD5 | cf4a2a2342631089a6ac475b7ec164d5 |
|
BLAKE2b-256 | c0c2a5028b40ebaeeb9bb36e142b24ae08e1afba9b1ccfaa6bbb64fb032008af |