electricsheepafrica/africa-rwanda-eicv5-transfers-in-29935fad

EICV5: Transfers in | Africa (Rwanda Data Sharing Platform - NISR)

89,487 rows - 1 Africa country - 2016-10-13-2017-10-22 - 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: EICV5: Transfers in
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 54f987be-dd25-4bfe-b690-7ccd1656103f
• Schema: EICV5_Cross-Sectional Sample
• Table: eicv5_s9b_transfers_in
• Sectors: National Statistics, Social Protection
• Source tags: Microdata
• Period: 2016-10-13-2017-10-22
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This microdata table contains information on inbound transfers of households collected in the fifth Integrated Household Living Conditions Survey, known as EICV5 (Enquête Intégrale sur les Conditions de Vie des ménages). A main cross-sectional sample survey, a panel survey and a VUP (Vision Umurenge Programme) sample survey were conducted simultaneously; this microdata table relates to the cross-sectional sample survey. Geographic Coverage: National coverage (Rwanda), including rural and urban households and allowing province- and district-level estimation of key indicators. Data are disaggregated up to the district level. Time Period: The EICV5 survey was conducted over a 12-month cycle from October 2016 to October 2017. Data collection was divided into 10 cycles in order to represent seasonality in the income and consumption data. Frequency: The EICV5 took place three years after the EICV4 was conducted (October 2013-October 2014); prior to EICV4, the survey was conducted every five years, with the first survey (EICV1) conducted in 2000/01. Population/Units: Household members Key Variables: Household received money or goods in kind from a member of the household or from others, ID number of sender, Relation with head of household, Sex, Location of sender Purpose: EICV5 aims to provide timely and updated statistics to facilitate monitoring progress on poverty reduction programmes and evaluation of different policies as stipulated in the First National Strategy for Transformation (NST1), the 2030 Sustainable Development Goals (SDGs) as well as the Vision 2020 and Vision 2050. The survey data are also very important for national accounts and updating the consumer price index (CPI). Data Quality Notes: The response rate for EICV5 (cross-sectional) is 100%. All households sampled (14,580) were interviewed with no refusal. For more information on the EICV5 Cross-Sectional Survey including further details on methodology, please see the collection-level description.

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
RWA	89,487	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.	54f987be-dd25-4bfe-b690-7ccd1656103f:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
hhid	float64	Household id	200001.0
clust	float64	Cluster	10001.0
province	string	Province	Kigali City
district	string	District Name	Nyarugenge
ur	string	Urban/Rural	Urban
region	string	Region	Kigali
weight	float64	Household weight	159.24864
poverty	string	Welfare categories	Non Poor
quintile	string	Quintile	Q5
s9bq0	bool	Household received money or goods in kind from a member of the household or from others	True
s9bq2	string	ID number of sender	Not a household member
s9bq3	string	Relation with head of household	No relatiive-rwandese
s9bq4	string	Sex	Female
s9bq5	string	Location of sender	Other countryside
s9bq6	string	Sent any cash to the HH	False
s9bq7	float64	Total amount of cash received in the last 12 months	``
s9bq8	string	Main method for receiving money	``
s9bq9	string	Sent food products to the HH	True
s9bq10	float64	Total value of food products received from person in last 12 months	4000.0
s9bq11	string	Sent other in-kind transfer	False
s9bq12	float64	Total value of other in-kind transfers received from person in last 12 months	``
s9bq13	string	Payments require remboursment	False
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	EICV5: Transfers in
source_resource	string	Source table name.	eicv5_s9b_transfers_in
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	54f987be-dd25-4bfe-b690-7ccd1656103f
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	54f987be-dd25-4bfe-b690-7ccd1656103f
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/54f987be-dd25-4bfe-b690-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T10:37:04Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv5-transfers-in-29935fad")
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_eicv5_transfers_in_29935fad_2026,
  title        = {EICV5: Transfers in | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/54f987be-dd25-4bfe-b690-7ccd1656103f},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv5-transfers-in-29935fad}}
}

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/54f987be-dd25-4bfe-b690-7ccd1656103f/download?format=csv