PWTLoader 0.1.1

A lightweigh loader for data from Penn World Table datasets via Dataverse

PWTLoader

PWTLoader is a Python Package built as a lightweight loader for the main .dta file as well as additional .dta files from the Penn World Tables datasets hosted at dataverse into a pandas pd.

This project uses data from the Penn World Table (PWT), version 10.01, developed by
Robert C. Feenstra, Robert Inklaar, and Marcel P. Timmer
at the Groningen Growth and Development Centre.

Features

• Allows the download of the latest Penn World Table data from the dataverse
• Parse and preprocess data for further economic analysis.
• Work with data in pandas DataFrame format.

📘 Method Overview & Output

PWTLoader.load_data()----------------------------------------------

• Description:
  Downloads and loads the main .dta file from the latest Penn World Table version hosted on Dataverse.

• Returns:
  A pandas.DataFrame containing the main dataset.
  You can use the PWTLoader.labels["variable_name"] to access the description of a specific variable in the dataset.

• Example:

  df = pwt.load_data()
  print(df.head())
  print(pwt.labels["cgdpo"])  # Description of the "cgdpo" variable
  

PWTLoader.additional_data(merge=False)---------------------------

• Description:
  Loads additional .dta files (from the same version) that complement the main dataset. If merge=True, it merges all compatible files together on common keys (countrycode, year).

• Parameters:

  • merge (bool) — If True, merges all additional datasets into one. If False, returns each dataset separately.

• Returns:

  • merge=True → A dict with a single key "merge" and a merged DataFrame.
  • merge=False → A dict of dataframes keyed by a short name (e.g., 'trade-detail', 'na_data', etc.).

• Example:

  # Get separate dataframes
  addl_data = pwt.additional_data()
  print(addl_data.keys())
  print(addl_data["na_data"]["df"].head())  # Access specific dataframes
  
  # Get merged dataframe
  merged = pwt.additional_data(merge=True)
  print(merged["merged"].head())  # View merged dataframe
  

PWTLoader.describe_additional(data_dict)-------------------------

• Description:
  Prints a concise summary of additional data files in the given dictionary, including:

  • Dataset name
  • Description
  • Number of rows/columns

• Parameters:

  • data_dict (dict) — The dictionary returned from additional_data() (with merged=False).

• Returns:

  • Nothing (just prints to console).

• Example:

  # Get additional data
  addl_data = pwt.additional_data()
  
  # Print a summary of each dataset
  pwt.describe_additional(addl_data)
  

Installation

You can install PWTLoader directly via pip from Github;

pip install git+https://github.com/Sarv1926/notjustmacro/PWTLoader.git

To install the necessary dependencies, you can use the requirements.txt file:

pip install -r PWTLoader/requirements.txt

Requirements

• Python 3.7 or higher
• pandas
• requests
• beautifulsoup4
• html5lib

Example

Here's an example of how to run PWTLoader

from PWTLoader import PWTloader

# Create an instance of the loader
pwt = PWTloader()

# Load the main dataset
df = pwt.load_data()

# If you want additional data
additional_data = pwt.additional_data(merge=True)

# To understand the structure of the additional data
pwt.describe_additional()

# Print out a preview of the data
print(df.head())

Overview of Directory Structure

PWTLoader/ │ ├── init.py # Package initialization ├── loader.py # Main logic to load PWT data ├── requirements.txt # Dependencies ├── setup.py # Package setup ├── README.md # Project documentation ├── .gitignore # Files to ignore

License

This project is licensed under the MIT License - see the LICENSE file for details.

Credits and Citation

This project uses data from the Penn World Table (PWT), version 10.01, which includes information on relative levels of income, output, input, and productivity, covering 183 countries from 1950 to 2019.

The data can be accessed from Dataverse: https://doi.org/10.34894/QT5BCC.

Citation

Citation

When using this data (for any purpose), please use the following citation:

Feenstra, Robert C., Robert Inklaar, and Marcel P. Timmer (2015), “The Next Generation of the Penn World Table,” American Economic Review, 105(10), 3150-3182, DOI: 10.1257/aer.20130954.

License

The data is licensed under CC-BY-4.0, which allows you to share and adapt the data as long as you give appropriate credit.