| Name | Version | Summary | date |
| graph-structure-learning |
0.1.2 |
Extracting graphs from signals on nodes |
2024-11-11 13:33:19 |
| gwdatalens |
0.2.5 |
Dashboard for groundwater time series validation. |
2024-11-08 16:13:00 |
| hg-systematic |
0.0.3 |
A library and examples to show how HGraph can be used for systematic trading. |
2024-11-07 18:23:05 |
| arch |
7.2.0 |
ARCH for Python |
2024-11-04 16:01:44 |
| hg-oap |
0.1.10 |
A library to faciliate building order and pricing strategies |
2024-11-03 15:17:17 |
| BOWaves |
0.0.26 |
Learning representative waveforms |
2024-10-29 02:17:34 |
| logicsponge-monitoring |
0.0.2 |
A real-time data processing pipeline |
2024-10-16 20:42:47 |
| pastastore |
1.7.2 |
Tools for managing Pastas time series models. |
2024-10-15 13:03:04 |
| SCALECAST |
0.19.10 |
The practitioner's time series forecasting library |
2024-10-14 22:58:10 |
| deFit |
0.3.0 |
Fitting Differential Equations to Time Series Data |
2024-10-14 08:44:54 |
| logicsponge |
0.0.9 |
A real-time data processing pipeline |
2024-10-08 12:09:40 |
| jumpmodels |
0.1.1 |
Statistical Jump Models in Python, with `scikit-learn`-style APIs |
2024-10-04 21:19:23 |
| datasponge-monitoring |
0.0.1 |
A real-time data processing pipeline |
2024-10-04 14:50:13 |
| datasponge-core |
0.0.6 |
A real-time data processing pipeline |
2024-10-04 14:30:23 |
| datasponge |
0.0.1 |
A real-time data processing pipeline |
2024-10-04 10:50:36 |
| traval |
0.5.1 |
Python package for applying automatic error detection algorithms to time series. Create custom error detection algorithms to support data validation workflows. |
2024-09-27 08:25:36 |
| pypots |
0.8.1 |
A Python Toolbox for Machine Learning on Partially-Observed Time Series |
2024-09-26 05:57:24 |
| MilPython |
0.5.0 |
Framework for building MILP optimizations for time series with gurobipy |
2024-09-24 14:03:22 |
| ai4ts |
0.0.3 |
AI for Time Series |
2024-09-14 02:08:54 |
| kisters.water.time-series |
2.5.0 |
KISTERS Time Series Access library |
2024-09-12 12:17:54 |