electricsheepafrica/africa-rwanda-recent-migration-matrix-by-province-2022-ad4930ba

Recent migration matrix by Province (2022) | Africa (Rwanda Data Sharing Platform - NISR)

7 rows - 1 Africa country - 2022-08-01-2022-08-31 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one public table from Rwanda's official Data Sharing Platform as ML-ready Parquet. The source package is the provenance boundary: all usable source columns from this table stay together in this repo.

About the source

• Source: Recent migration matrix by Province (2022)
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 5949cee0-b26b-4ea5-bc50-8d49898e693c
• Schema: PHC5_2022_Main_Indicators
• Table: phc5_2022_main_indicators_table31
• Sectors: National Statistics, Demographics
• Source tags: Aggregated data
• Period: 2022-08-01-2022-08-31
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This aggregated data table contains the recent migration matrix by Province. This data was collected in the 5th Rwanda Population and Housing Census (PHC5) in August 2022. Geographic Coverage: National coverage (Rwanda), with disaggregation up to Province and District level. Time Period: The 5th Rwanda Population and Housing Census was conducted in August 2022. Frequency: The Rwanda Population and Housing Census is conducted every 10 years. Population/Units: Household members Key Variables: Province of origin, Province of residence (Destination), In-migrants, Out-migrants Purpose: Measuring progress in Rwanda's development calls for the availability of economic, demographic and social statistical data necessary to compile developmental indicators at different levels and points in time. This census thus comes to serve that purpose. Data Quality Notes: Data quality assessment published at https://statistics.gov.rw/data-sources/censuses/Population-and-Housing-Census/fifth-population-and-housing-census-2022/rphc5-thematic-reports/rphc5-thematic-report-data-quality-assessment .

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
RWA	7	n/a	n/a	Rwanda

Indicators or Resource Contents

• This source package is published as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa packaging.	5949cee0-b26b-4ea5-bc50-8d49898e693c:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
province_of_origin	string	Province of origin	City of Kigali
province_of_residence_destination_city_of_kigali	int64	Province of residence (Destination): City of Kigali	146452
province_of_residence_destination_south	int64	Province of residence (Destination): South	47402
province_of_residence_destination_west	int64	Province of residence (Destination): West	13832
province_of_residence_destination_north	int64	Province of residence (Destination): North	25716
province_of_residence_destination_east	int64	Province of residence (Destination): East	93663
out_migrants	float64	Out-migrants	180613.0
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	Recent migration matrix by Province (2022)
source_resource	string	Source table name.	phc5_2022_main_indicators_table31
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	5949cee0-b26b-4ea5-bc50-8d49898e693c
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	5949cee0-b26b-4ea5-bc50-8d49898e693c
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/5949cee0-b26b-4ea5-bc50-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T11:48:51Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-recent-migration-matrix-by-province-2022-ad4930ba")
df = ds["train"].to_pandas()
print(df.head())

Filter to Rwanda

rwanda = df[df["country_iso3"] == "RWA"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_rwanda_recent_migration_matrix_by_province_2022_ad4930ba_2026,
  title        = {Recent migration matrix by Province (2022) | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/5949cee0-b26b-4ea5-bc50-8d49898e693c},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-recent-migration-matrix-by-province-2022-ad4930ba}}
}

License

Released under CC BY 4.0.

Original data (c) NISR. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-07-18 via the Electric Sheep pipeline. Source URL: https://api.data.gov.rw/api/v1/datasets/public/5949cee0-b26b-4ea5-bc50-8d49898e693c/download?format=csv