maxbenchrist / awesome_time_series_in_python Goto Github PK

great material thanks
may you clarify :
where to find repo for multivariate time series classification or regression
1
where all values are continues values
2
or even will it work for multivariate time series where values are mixture of continues and categorical values
for example 2 dimensions have continues values and 3 dimensions are categorical values

color        weight     gender  height  age  

1 black 56 m 160 34
2 white 77 f 170 54
3 yellow 87 m 167 43
4 white 55 m 198 72
5 white 88 f 176 32

Thanks for the great list.!

I think you should add the following: matrixprofile-ts[https://github.com/target/matrixprofile-ts]

Helps find the matrixprofile of time series, which then can be used to quickly find other information (like motifs).

I started a file at

https://github.com/MaxBenChrist/awesome_time_series_in_python/blob/master/standardize_time_series_formats.md

to trigger a discussion regarding the time series formats for python packages to analyze time series data.

This issue should be used to discuss the file.

Hi,
Recommend an automatic time series toolkit HyperTS.
Github： https://github.com/DataCanvasIO/HyperTS

Easy-to-use, powerful, unified full pipeline automated time series toolkit. Supports forecasting, classification and regression.

HyperTS is a Python package that provides an end-to-end time series (TS) analysis toolkit. It covers complete and flexible AutoML workflows for TS, including data clearning, preprocessing, feature engineering, model selection, hyperparamter optimization, result evaluation, and visualization.

Multi-mode drive, light-heavy combination is the highlighted features of HyperTS. Therefore, statistical models (STATS), deep learning (DL), and neural architecture search (NAS) can be switched arbitrarily to get a powerful TS estimator.

The darts package is interesting. https://github.com/unit8co/darts

Sorry to ask a question using issue.
You have a tremendous article on time series analysis. Please, may you suggest a tool/python library preferably that works well for predicting a number of cars on the street at hourly level.
Right now I am using FbProphet, the predictions are off by 20% (MAPE). Trying to predict one week into the future.

Arrow would also fit quite nicely here, in the general timestamps & dates handling category. From the docs:

Arrow is a Python library that offers a sensible, human-friendly approach to creating, manipulating, formatting and converting dates, times, and timestamps. It implements and updates the datetime type, plugging gaps in functionality, and provides an intelligent module API that supports many common creation scenarios. Simply put, it helps you work with dates and times with fewer imports and a lot less code.

First of all, looks like a great resource - definitely some libraries I haven't seen before, thanks.

I think traces would fit very well here. From the docs:

A Python library for unevenly-spaced time series analysis.

https://github.com/tgsmith61591/pyramid

Hi,

I would humbly like to ask you to include my library pyFTS on your awesome list. pyFTS is a free and open-source library for Fuzzy Time Series in Python programming language. Here follow some materials about it:

• Digital Object Identifier: https://doi.org/10.5281/zenodo.597359
• Official site and documentation: https://pyfts.github.io/pyFTS/
• Code repository and issue tracking: https://github.com/PYFTS/pyFTS
• PhD Thesis on Fuzzy Time Series: https://doi.org/10.5281/zenodo.3374641
• A short tutorial on Fuzzy Time Series:
  Part I: Introduction to the Fuzzy Logic, Fuzzy Time Series and the pyFTS library (https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-dcc6d4eb1b15)

Part II: High order, weighted and multivariate methods and a case study of solar energy forecasting. (https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-part-ii-with-an-case-study-on-solar-energy-bda362ecca6d )

Part III: Interval and probabilistic forecasting, non-stationary time series, concept drifts and time variant models. (https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-part-iii-69445dff83fb)

More example codes: https://github.com/PYFTS/notebooks

Please do not hesitate to get in touch and ask any questions. Thanks in advance.

I recommend you insert tsmoothie: A python library for time-series smoothing and outlier detection in a vectorized way

Hi, I took the liberty to update your list of time series related software and copy it into our wiki here, hope that's okay, of course feel free to include any of my changes into your list (I'm happy to work on this list together, but PRs seemed a little too complicated for that).

Thanks for organizing the time series packages in python. Here is one that is fascinating to me regarding time to event prediction. I'll let you be the judge if this qualifies for your list.

https://github.com/ragulpr/wtte-rnn/

microprediction

Thanks a lot for this awesome repo ;)
I only found a few data sets that include time series data.
Do you know a way to artificially generate time series data?
That'd be incredibly helpful.
Thanks a lot!
Willi