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Lectures on Computational Communication

Home Page: https://chengjun.github.io/mybook/

License: GNU General Public License v3.0

Jupyter Notebook 82.75% HTML 16.37% CSS 0.01% JavaScript 0.02% Python 0.21% Rich Text Format 0.61% TeX 0.03% Shell 0.01% Common Lisp 0.01% Makefile 0.01% Batchfile 0.01% R 0.01% Perl 0.01%

computational-communication computational-social-science jupyter-notebook python

mybook's Introduction

🌱 Know thyself and kindle the fire in your heart!

mybook's People

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mybook's Issues

Panel Data Regression with Python

https://www.douban.com/group/topic/226722163/

linearmodels

https://bashtage.github.io/linearmodels/panel/examples/examples.html

Non-consecutive header level

Discussed in #25

^{Originally posted by chengjun October 27, 2021}

/home/runner/work/mybook/mybook/03-UK-MPS-Scandal.ipynb:70002: WARNING: Non-consecutive header level increase; 0 to 2 [myst.header]
/home/runner/work/mybook/mybook/03-UK-MPS-Scandal.ipynb:120002: WARNING: Non-consecutive header level increase; 0 to 2 [myst.header]
/home/runner/work/mybook/mybook/03-UK-MPS-Scandal.ipynb:220002: WARNING: Non-consecutive header level increase; 0 to 2 [myst.header]
/home/runner/work/mybook/mybook/03-umbrella-of-love.ipynb:400002: WARNING: Non-consecutive header level increase; 0 to 2 [myst.header]

gini coefficient

def gini(list_of_values):
    sorted_list = sorted(list_of_values)
    height, area = 0, 0
    for value in sorted_list:
        height += value
        area += height - value / 2.
    fair_area = height * len(list_of_values) / 2.
    return (fair_area - area) / fair_area

github actions

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Issue on page /13-recsys-intro.html

images do not show https://chengjun.github.io/mybook/13-recsys-intro.html

https://nbviewer.jupyter.org/github/chengjun/mybook/blob/main/13-recsys-intro.ipynb

VIF: variance_inflation_factor

from statsmodels.stats.outliers_influence import variance_inflation_factor
variables = data[['type_num', 'male', 'age', 'job1', 'job2', 'edu', 'income', 'all_freq_log', 
               'freq1_log', 'freq2_log', 'freq3_log', 'freq6_log', 'freq7_log', 'freq13_log', 'freq19_log']]
vif = pd.DataFrame()
vif['VIF'] = [variance_inflation_factor(variables.values,i) for i in range(variables.shape[1])]
vif['features'] = variables.columns
vif

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