TrendPy: Time Series Regression with Python ON PIP now

[Zoufiné Lauer-Baré]

Dear SymPy Community,

 I just wanted to share with you, that the TrendPy Project about Time Series Regressions with Python 

https://github.com/zolabar/trendPy

is now uploaded to pip (as trendpy2, i.e. pip install trendpy2).

Reminder:

The trendpy2 package makes it easy to approximate time series regressions in a determinstic way. The following trends are supported:

linear

polynomial

exponential

trigonometric

“free”, for max. three parameters, e.g. (the intial guess for a, b, c is 1.)

A standalone feature of the trendpy2 package is, that it combines least-squares approaches, Fourier analysis approaches, numerical Python packages as Numpy and Scipy and the symbolic Python package Sympy for time series regressions.

SymPy is makes it possible to easlily implement a "free" regression approach.

A streamlit web app is now released, additionally to the voila web app. It can be tried out using this link (also linked in the github page)

https://zolabar-trendpy-trendpy2-app-kfqshb.streamlit.app/

Testdata in

https://github.com/zolabar/trendPy/tree/main/data

Enjoy! Feedback is welcome ;)

Regards,

Zoufiné