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stargazer

Python implementation of the R stargazer multiple regression model creation tool

https://github.com/statsreporting/stargazer

Science Score: 13.0%

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    CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary

Keywords

latex python regression-models stargazer
Last synced: 6 months ago · JSON representation

Repository

Python implementation of the R stargazer multiple regression model creation tool

Basic Info
  • Host: GitHub
  • Owner: StatsReporting
  • License: other
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 439 KB
Statistics
  • Stars: 203
  • Watchers: 5
  • Forks: 54
  • Open Issues: 33
  • Releases: 0
Topics
latex python regression-models stargazer
Created over 7 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Stargazer

This is a python port of the R stargazer package that can be found on CRAN. I was disappointed that there wasn't equivalent functionality in any python packages I was aware of so I'm re-implementing it here.

There is an experimental function in the statsmodels.regression.linear_model.OLSResults.summary2 that can report single regression model results in HTML/CSV/LaTeX/etc, but it still didn't quite fulfill what I was looking for.

The python package is object oriented now with chained commands to make changes to the rendering parameters, which is hopefully more pythonic and the user doesn't have to put a bunch of arguments in a single function.

Installation

You can install this package through PyPi with pip install stargazer or just clone the repo and take the stargazer.py file since it's the only one in the package.

Dependencies

It depends on statsmodels, which in turn depends on several other libraries like pandas, numpy, etc

Editing Features

This library implements many of the customization features found in the original package. Examples of most can be found in the examples jupyter notebook and a full list of the methods/features is here below:

  • title: custom title
  • show_header: display or hide model header data
  • show_model_numbers: display or hide model numbers
  • custom_columns: custom model names and model groupings
  • significance_levels: change statistical significance thresholds
  • significant_digits: change number of significant digits
  • show_confidence_intervals: display confidence intervals instead of variance
  • dependent_variable_name: rename dependent variable
  • rename_covariates: rename covariates
  • covariate_order: reorder covariates
  • reset_covariate_order: reset covariate order to original ordering
  • show_degrees_of_freedom: display or hide degrees of freedom
  • custom_note_label: label notes section at bottom of table
  • add_custom_notes: add custom notes to section at bottom of the table
  • add_line: add a custom line to the table
  • append_notes: display or hide statistical significance thresholds

These features are agnostic of the rendering type and will be applied whether the user outputs in HTML, LaTeX, etc

Example

Here is an examples of how to quickly get started with the library. More examples can be found in the examples.ipynb file in the github repo. The examples all use the scikit-learn diabetes dataset, but it is not a dependency for the package.

OLS Models Preparation

```python import pandas as pd from sklearn import datasets import statsmodels.api as sm from stargazer.stargazer import Stargazer

diabetes = datasets.load_diabetes() df = pd.DataFrame(diabetes.data) df.columns = ['Age', 'Sex', 'BMI', 'ABP', 'S1', 'S2', 'S3', 'S4', 'S5', 'S6'] df['target'] = diabetes.target

est = sm.OLS(endog=df['target'], exog=sm.addconstant(df[df.columns[0:4]])).fit() est2 = sm.OLS(endog=df['target'], exog=sm.addconstant(df[df.columns[0:6]])).fit()

stargazer = Stargazer([est, est2]) ```

HTML Example

python stargazer.render_html()

Dependent variable: target
(1)(2)
ABP416.674***397.583***
(69.495)(70.870)
Age37.24124.704
(64.117)(65.411)
BMI787.179***789.742***
(65.424)(66.887)
S1197.852
(143.812)
S2-169.251
(142.744)
Sex-106.578*-82.862
(62.125)(64.851)
const152.133***152.133***
(2.853)(2.853)
Observations442442
R20.4000.403
Adjusted R20.3950.395
Residual Std. Error59.976 (df=437)59.982 (df=435)
F Statistic72.913*** (df=4; 437)48.915*** (df=6; 435)
Note:*p<0.1; **p<0.05; ***p<0.01

LaTeX Example

python stargazer.render_latex()

Owner

  • Name: StatsReporting
  • Login: StatsReporting
  • Kind: organization

GitHub Events

Total
  • Issues event: 1
  • Watch event: 13
  • Issue comment event: 4
  • Pull request event: 2
  • Fork event: 5
Last Year
  • Issues event: 1
  • Watch event: 13
  • Issue comment event: 4
  • Pull request event: 2
  • Fork event: 5

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 103
  • Total Committers: 11
  • Avg Commits per committer: 9.364
  • Development Distribution Score (DDS): 0.417
Past Year
  • Commits: 21
  • Committers: 2
  • Avg Commits per committer: 10.5
  • Development Distribution Score (DDS): 0.048
Top Committers
Name Email Commits
Pietro Battiston me@p****t 60
Max Ghenis m****s@g****m 15
csemken c****n 10
mwburke m****e@g****m 7
Christoph Semken e****l 3
leogoldman l****n@L****n 2
Brandon Zborowski b****5@g****m 2
Matthew Burke m****e@c****m 1
maruoss m****s@h****m 1
Alex Dong 6****k 1
Isaac Liu 6****u 1
Committer Domains (Top 20 + Academic)
creditsesame.com: 1 leos-mbp-2.lan: 1 pietrobattiston.it: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 8
  • Total pull requests: 16
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 5 months
  • Total issue authors: 7
  • Total pull request authors: 7
  • Average comments per issue: 2.38
  • Average comments per pull request: 2.44
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 1.0
  • Average comments per pull request: 3.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • SwannChelly (2)
  • randomgambit (1)
  • elemn (1)
  • SimaFT (1)
  • javier-garcia-tilburg (1)
  • msh855 (1)
  • toobaz (1)
Pull Request Authors
  • vlshields (4)
  • jsr-p (3)
  • dsliwka (3)
  • s3alfisc (2)
  • javier-garcia-tilburg (2)
  • jpweytjens (1)
  • maruoss (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 4,837 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 33
  • Total versions: 7
  • Total maintainers: 2
pypi.org: stargazer

Nicely formatted regression reporting

  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 33
  • Downloads: 4,837 Last month
Rankings
Dependent repos count: 2.5%
Downloads: 4.3%
Average: 4.7%
Dependent packages count: 4.8%
Stargazers count: 5.5%
Forks count: 6.2%
Maintainers (2)
PietroBattiston mwburke
Last synced: 6 months ago

Dependencies

setup.py pypi