yottoo / wooldridge

A Python package containing 111 data sets of Introductory Econometrics: A Modern Approach (7th ed, J.M. Wooldridge)

Wooldridge Meets Python

Data sets from Introductory Econometrics: A Modern Approach (7th ed, J.M. Wooldridge)

Description

A Python package which contains 111 data sets from one of the most famous econometrics textbooks for undergraduates.

It is extensively used in Pythonで学ぶ入門計量経済学 (Japanese). Its Google-translated version (in the language of your choice) is also available in Learning Introductory Econometrics with Python.

It is also used in Using Python for Introductory Econometrics, which is a sister book Using R for Introductory Econometrics.

How to Use

First things first.

import wooldridge

To load a data set named <dataset>:

wooldridge.data('<dataset>')

It returns pandas DataFrame. Note that <dataset> is entered in strings. For example, to load a data set mroz into df:

df = wooldridge.data('mroz')

To show the description (e.g. variable definitions and sources) of a data set:

wooldridge.data('mroz', description=True)

To show the list of 111 data sets contained in the package

wooldridge.data()

How to Install

pip install wooldridge

or

git clone https://github.com/spring-haru/wooldridge.git
pip install .

Note

The function dataWoo() introduced in the previous versions also works:

from wooldridge import *

df = dataWoo('<dataset>')

dataWoo('<dataset>', description=True)

dataWoo()

Reference

J.M. Wooldridge (2019) Introductory Econometrics: A Modern Approach, Cengage Learning, 7th edition.