Data sets from Introductory Econometrics: A Modern Approach (7th ed, J.M. Wooldridge)
Project description
Wooldridge Meets Python
Data sets from Introductory Econometrics: A Modern Approach (7th ed, J.M. Wooldridge)
Description
A Python package which contains 115 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file wooldridge-0.5.0.tar.gz.
File metadata
- Download URL: wooldridge-0.5.0.tar.gz
- Upload date:
- Size: 5.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8875639fddc8fb1d1b93b34d5872864d8db03e1e80cade9146e6d0d5725e7b4d
|
|
| MD5 |
d124c142f787fa5d409610261d7c0384
|
|
| BLAKE2b-256 |
c150b5402e55b36107557e7c836673ba0956103dc1886b1cc411f53d26186655
|
File details
Details for the file wooldridge-0.5.0-py3-none-any.whl.
File metadata
- Download URL: wooldridge-0.5.0-py3-none-any.whl
- Upload date:
- Size: 5.5 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bd45afcd423cfa6288f48c9e4bc4b85e0cf4baf0462ee40c56c909b6a9b03724
|
|
| MD5 |
416b646ae277f1b2f84817230b8026bd
|
|
| BLAKE2b-256 |
687bef00b71eaae90f32032a5e4dde3ccd98b0a6698df6391b2166c5cd2ee9f9
|