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

Both catalog() and load() work with no setup. catalog() reads metadata bundled in the package; load() fetches the latest data from the public imibare API. The versioned load(version=...) path additionally requires the [iceberg] extra and R2 catalog credentials.

Links

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.

Project links

Key dates

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  • Released:
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PyPI data
Data sourced directly from PyPI's database.
Avatar for imibare from gravatar.com imibare

Credits

Author: imibare

License expression

MIT
View SPDX License List

Requires

Python >=3.11

Provides Extra

dev iceberg polars

Tags

africa economics government-data open-data rwanda statistics

Classifiers

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