[](https://pypi.python.org/pypi/wooldridge/)
[](https://github.com/spring-haru/wooldridge/actions?query=workflow%codeql-analysis)
[](https://pepy.tech/project/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](https://py4etrics.github.io) (Japanese). Its Google-translated version (in the language of your choice) is also available in [Learning Introductory Econometrics with Python](https://translate.google.com/translate?sl=auto&tl=en&u=https://py4etrics.github.io).
It is also used in [Using Python for Introductory Econometrics](http://www.upfie.net), which is a sister book [Using R for Introductory Econometrics](http://www.urfie.net).
## 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.
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