imibare
Programmatic access to Rwandan government statistical data.
imibare gives you clean, typed, versioned access to official statistics
published by Rwandan government institutions (NISR, BNR, MINECOFIN, RSSB, RRA,
and more) as pandas or polars DataFrames. No scraping, no PDF wrangling.
Install
pip install imibare
Optional extras:
pip install imibare[polars] # return polars DataFrames
pip install imibare[iceberg] # snapshot time travel via load(version=...)
Quick start
import imibare as imi
# Browse the catalog (works offline)
for d in imi.catalog(country="RW")[:5]:
print(d.id, "-", d.name)
# Load a dataset as a pandas DataFrame
df = imi.load("rw.nisr.cpi.monthly")
# Filter by date range
recent = imi.load("rw.nisr.cpi.monthly", start="2023-01-01")
# Return a polars DataFrame (requires the [polars] extra)
fx = imi.load("rw.bnr.fx.daily", engine="polars")
Catalog
catalog() returns dataset metadata you can filter by country, topic, or
frequency:
imi.catalog() # every dataset
imi.catalog(country="RW", topic="prices")
imi.catalog(frequency="daily")
Each entry carries its id, producing institution, coverage window, columns, source URL, and license.
Dataset IDs
Every dataset has a stable, country-prefixed id of four segments:
{country}.{institution}.{topic}.{frequency}
rw.nisr.cpi.monthly
Ids are permanent; a breaking schema change ships under a new suffix
(for example rw.nisr.cpi.monthly.v2).
Versioned data (time travel)
With the [iceberg] extra you can load a dataset as it stood on a given date:
imi.load("rw.nisr.cpi.monthly", version="2025-06-01")
Data access
catalog() works offline from metadata bundled in the package. load() fetches
Parquet data from imibare's object store; see the
documentation for access configuration.
Links
- Website: https://imibare.org
- Documentation: https://imibare.org/docs
License
Code is released under the MIT License. Data retrieved through this package remains under the license of each source institution; see each dataset's metadata for details.
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