gla-data

Shared tools for loading, transforming, and visualising the GLA datasets used in City Data analysis.

Installation

Global install (CLI)

To install gla-data globally so the gla-data CLI is available anywhere in your terminal, use uv tool:

uv tool install gla-data

Normally pixi global install would be the preferred approach, but it does not yet support PyPI packages — so uv tool is the right choice for now.

If you don't have uv installed, you can install it via pixi:

pixi global install uv

pip

pip install gla-data

pixi

pixi add gla-data

Pixi pulls geospatial dependencies (geopandas, pyproj, etc.) from conda-forge, which provides reliable pre-built binaries across all platforms and Python versions.

Usage

Python API

import gla_data

# Load 2021 LSOA boundaries for London
lsoa_gdf = gla_data.load_boundaries(geography='lsoa', year=2021)

# Load census dwelling counts
dwellings_2021 = gla_data.load_census_dwellings(year=2021)
dwellings_2011 = gla_data.load_census_dwellings(year=2011)

# Crosswalk 2011 dwelling counts onto 2021 LSOA boundaries
dwellings_2011_xw = gla_data.crosswalk(
    dwellings_2011,
    from_year=2011,
    to_year=2021,
    value_cols=['dwellings_total'],
)

# Load an OA → LSOA geography lookup
lookup = gla_data.load_geography_lookup(year=2021, smallest_geography='oa')

# Aggregate OA-level data up to LSOA level
lsoa_totals = gla_data.aggregate(
    df,
    from_geography='oa',
    to_geography='lsoa',
    value_cols=['count'],
    year=2021,
)

CLI

The package installs a gla-data command. Run catalogue to list all available datasets:

gla-data catalogue

This prints a table of every dataset, the function used to load it, a description, and its access tier (public/S3).

Development

git clone <repo-url>
cd gla-data
pixi install

pixi run test       # run tests
pixi run lint       # check code style
pixi run format     # auto-format
pixi run typecheck  # type checking

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