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
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
pyg_timeseries-0.0.30.tar.gz
(70.1 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
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
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e9c648b26c3d47874237f7d760a9d25e2cdd7920c7bae3ca3b3c4f0fed580145
|
|
| MD5 |
1001fce749f8d8ffc8d2d1a2d1bd2296
|
|
| BLAKE2b-256 |
2ef34567d79d3e571fd94391370dcf63ee75f6597939ecf51a42e443e290565f
|
File details
Details for the file pyg_timeseries-0.0.30-py3-none-any.whl.
File metadata
- Download URL: pyg_timeseries-0.0.30-py3-none-any.whl
- Upload date:
- Size: 76.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
aef69214f870118b64eb09b3b7f64a1565bfe1fd2d63e8aeecc0d4802fd5b709
|
|
| MD5 |
c439aaf9c1019d6cdbbbf59494243207
|
|
| BLAKE2b-256 |
9cb5bc31b34600447372865be44147a9403c481334ae154bcfd0a3998314487c
|