pycensuskr

A Python package for Korean district-level census and geographic data.

Installation

PyPI

pip install pycensuskr

From source

git clone https://github.com/sigmafelix/pycensuskr.git
cd pycensuskr
pip install -e .

# python setup.py install

For development

git clone https://github.com/sigmafelix/pycensuskr.git
cd pycensuskr
pip install -e ".[dev]"

Usage

from pycensuskr import __version__
from pycensuskr import CensusKR
from matplotlib import pyplot as plt
import geopandas as gpd

# Print version
print(__version__)

# Create a CensusData instance
census = CensusKR()

# load specific year data
data_2020 = census.load_data(2020)
print(data_2020)

# load district boundaries for a specific year
districts_2020 = census.load_districts(2020)
districts_2020["adm2_re"] = districts_2020["adm2_code"].astype(str).str.slice(0,4)
# aggregate geometries by adm2_re
districts_2020 = districts_2020.dissolve(by="adm2_re", as_index=False)
districts_2020["adm2_code"] = districts_2020["adm2_re"] + "0"
districts_2020["adm2_code"] = districts_2020["adm2_code"].astype(int)

# cleaned data with variable types
df_tax_2020 = census.anycensus(year = 2020, type = "tax", aggregator = "sum")

districts_tax_2020 = districts_2020.merge(df_tax_2020, on="adm2_code")
print(districts_tax_2020)

districts_tax_2020.plot("income_labor_mil")
plt.show()

Notes on data updates

Our data cleaning and processing pipeline is based on the original R package tidycensuskr. We periodically synchronize the bundled datasets used in this package with those in R tidycensuskr and tidycensussfkr to ensure accuracy and relevance. Please refer to the tidycensuskr webpage for details on the latest data updates and changes.

Development

Running tests

pytest

License

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