Skip to main content

Utilities for fast timeseries analysis

Project description

pyg-timeseries

pandas is great but pyg-timeseries introduces a few improvements.

  • pyg is designed so that for dataframes/series without nans, it matches pandas exactly
  • consistent treatments of nan's: unlike pandas, pyg ignores nans everywhere in its calculations.
  • np.ndarray and pandas dataframes are treated the same and pyg operates on np.arrays seemlessly
  • state-management: pyg introduces a framework for returning not just the timeseries, but also the state of the calculation. This can be fed into the next calculation batch, allowing us not to have to 're-run' everything from the distant past.
  • performance-wise, pyg is implemented via numba with performance times comparable to pandas

pip install from https://pypi.org/project/pyg-timeseries/

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

pyg_timeseries-0.0.30.tar.gz (70.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyg_timeseries-0.0.30-py3-none-any.whl (76.7 kB view details)

Uploaded Python 3

File details

Details for the file pyg_timeseries-0.0.30.tar.gz.

File metadata

  • Download URL: pyg_timeseries-0.0.30.tar.gz
  • Upload date:
  • Size: 70.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.1

File hashes

Hashes for pyg_timeseries-0.0.30.tar.gz
Algorithm Hash digest
SHA256 e9c648b26c3d47874237f7d760a9d25e2cdd7920c7bae3ca3b3c4f0fed580145
MD5 1001fce749f8d8ffc8d2d1a2d1bd2296
BLAKE2b-256 2ef34567d79d3e571fd94391370dcf63ee75f6597939ecf51a42e443e290565f

See more details on using hashes here.

File details

Details for the file pyg_timeseries-0.0.30-py3-none-any.whl.

File metadata

File hashes

Hashes for pyg_timeseries-0.0.30-py3-none-any.whl
Algorithm Hash digest
SHA256 aef69214f870118b64eb09b3b7f64a1565bfe1fd2d63e8aeecc0d4802fd5b709
MD5 c439aaf9c1019d6cdbbbf59494243207
BLAKE2b-256 9cb5bc31b34600447372865be44147a9403c481334ae154bcfd0a3998314487c

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