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  1. Just released my first Python library on PyPI!

    `ig_degree_betweenness` is a Python implementation of the "Smith-Pittman" community detection algorithm.

    This library brings the power the the {ig.degree.betweenness} R package to Python

    Install from PyPI with: `pip install ig-degree-betweenness`

    Link to GitHub + details in the comments.

    #python #rstats #datatscience #socialnetworks #technology

  2. Just released my first Python library on PyPI!

    `ig_degree_betweenness` is a Python implementation of the "Smith-Pittman" community detection algorithm.

    This library brings the power the the {ig.degree.betweenness} R package to Python

    Install from PyPI with: `pip install ig-degree-betweenness`

    Link to GitHub + details in the comments.

  3. Just released my first Python library on PyPI!

    `ig_degree_betweenness` is a Python implementation of the "Smith-Pittman" community detection algorithm.

    This library brings the power the the {ig.degree.betweenness} R package to Python

    Install from PyPI with: `pip install ig-degree-betweenness`

    Link to GitHub + details in the comments.

    #python #rstats #datatscience #socialnetworks #technology

  4. Just released my first Python library on PyPI!

    `ig_degree_betweenness` is a Python implementation of the "Smith-Pittman" community detection algorithm.

    This library brings the power the the {ig.degree.betweenness} R package to Python

    Install from PyPI with: `pip install ig-degree-betweenness`

    Link to GitHub + details in the comments.

    #python #rstats #datatscience #socialnetworks #technology

  5. Just released my first Python library on PyPI!

    `ig_degree_betweenness` is a Python implementation of the "Smith-Pittman" community detection algorithm.

    This library brings the power the the {ig.degree.betweenness} R package to Python

    Install from PyPI with: `pip install ig-degree-betweenness`

    Link to GitHub + details in the comments.

    #python #rstats #datatscience #socialnetworks #technology

  6. Check out the new user-contributed #gretl package "GlobalFactors".

    It does (a) estimates the number of global and local factors (b) consistently estimates (with PC) global & local factors and global & local loadings.

    Written by Ioannis A. Venetis.

    DOC: gretl.sourceforge.net/current_

    #econometrics #statistics #economics #datatscience

  7. Check out the new user-contributed #gretl package "GlobalFactors".

    It does (a) estimates the number of global and local factors (b) consistently estimates (with PC) global & local factors and global & local loadings.

    Written by Ioannis A. Venetis.

    DOC: gretl.sourceforge.net/current_

    #econometrics #statistics #economics #datatscience

  8. Version 2023.2 of the user-contributed #gretl package "getYahoo" for downloading financial data from "Yahoo Finance" is out now.

    Written by yinung.

    DOC: gretl.sourceforge.net/current_

    #economics #econometrics #datatscience #statistics

  9. Version 2023.2 of the user-contributed #gretl package "getYahoo" for downloading financial data from "Yahoo Finance" is out now.

    Written by yinung.

    DOC: gretl.sourceforge.net/current_

    #economics #econometrics #datatscience #statistics

  10. Version 2023.2 of the user-contributed #gretl package "getYahoo" for downloading financial data from "Yahoo Finance" is out now.

    Written by yinung.

    DOC: gretl.sourceforge.net/current_

    #economics #econometrics #datatscience #statistics

  11. Just to inform you:
    The next release will include native support for #AutoARIMA automatically determining the optimal ARIMA #timeseries model specification.

    This is will be pretty fast, as it's implemented in C.

    #gretl #econometrics #economics #statistics #datatscience

  12. Just to inform you:
    The next release will include native support for #AutoARIMA automatically determining the optimal ARIMA #timeseries model specification.

    This is will be pretty fast, as it's implemented in C.

    #gretl #econometrics #economics #statistics #datatscience