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-0.0.40.tar.gz
(75.1 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-0.0.40.tar.gz.
File metadata
- Download URL: pyg_timeseries-0.0.40.tar.gz
- Upload date:
- Size: 75.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d123609d714a2e074807e2efdbb5f36eacfebc2f68fe600c4aa1d6655cd74c66
|
|
| MD5 |
3b899dbcf0b87ff9856e666a88461899
|
|
| BLAKE2b-256 |
67a2dcb5880b90506f087d239ed215f65e8808377746ea8f53f4174094eb29c8
|
File details
Details for the file pyg_timeseries-0.0.40-py3-none-any.whl.
File metadata
- Download URL: pyg_timeseries-0.0.40-py3-none-any.whl
- Upload date:
- Size: 81.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
525a98faf39cf4ef0710b6b27f2046aab2af0b7850f34db6879c9f307598939e
|
|
| MD5 |
1a94d3dda7f756757ba2fd3c097b20e0
|
|
| BLAKE2b-256 |
2f5bdb11105149e3f59c6c6d87e729d44f99153675ba37aba145f190e1244ee6
|