electricsheepafrica/africa-rwanda-eicv7-vup-transfers-in-d6285be2

EICV7 (VUP): Transfers in | Africa (Rwanda Data Sharing Platform - NISR)

9,313 rows - 1 Africa country - 2023-10-16-2024-10-15 - 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. If the public CSV omits an API-declared column, that column is included with null values and recorded in the source snapshot metadata.

About the source

• Source: EICV7 (VUP): Transfers in
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: b3a7b91f-de30-4018-8f5b-a85bec42d18c
• Schema: EICV7_VUP
• Table: eicv7_vup_s9b_transfers_in
• Sectors: National Statistics, Social Protection
• Source tags: Microdata
• Period: 2023-10-16-2024-10-15
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This microdata table contains information on inbound value transfers of households, collected in the seventh Integrated Household Living Conditions Survey, known as EICV7 (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 VUP sample survey. Geographic Coverage: National coverage (Rwanda), including rural and urban households and allowing province- and district-level estimation of key indicators. Time Period: The EICV7 data collection covered a 12 month period (October 2023 to October 2024). In order to represent the seasonality in the income and consumption data, the fieldwork was divided into nine nationally representative cycles. Frequency: The EICV is conducted every three years; 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: During the last 12 months has this household received money, How many people did you send money, ID number of concern, ID number of sender, Relation with head of household Purpose: This survey serves as a key source of socio-economic data on the living conditions of Rwandan households. It plays a critical role in the ongoing monitoring and evaluation of national and international development frameworks, including the Second National Strategy for Transformation (NST2), the 2030 Sustainable Development Goals (SDGs), and Vision 2050, among others. The survey data are also vital for compiling national accounts and updating the Consumer Price Index (CPI). Data Quality Notes: The response rate exceeded 99% by the end of the survey, with 15,054 out of the 15,066 targeted households successfully interviewed. For more information on the EICV7 VUP 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	9,313	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.	b3a7b91f-de30-4018-8f5b-a85bec42d18c:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
hhid	float64	Household Identification	120385.0
clust	float64	Clust	12248.0
province	bool	Province	True
district	float64	District	11.0
ur	int64	Residence area	2
s9bq0	int64	During the last 12 months has this household received money	2
s9bq1a	float64	How many people did [name] send money	``
s9bq2	float64	ID number of concern	``
s9bq3	float64	ID number of sender	``
s9bq4	float64	Relation with head of household	``
s9bq5	float64	Sex	``
s9bq6	float64	Location of sender	``
s9bq8	float64	Total amount of cash received in the last 12 months	``
s9bq9	float64	Main method for receiving money	``
s9bq99	float64	More transfers in?	``
weight	float64	Household Weight	78.135704
quintile	int64	Quintiles of real consumption per ae	2
pov_jan	float64	Total Poverty Headcount Ratio	100.0
poverty	float64	Welfare Categories	2.0
epov_jan	float64	Extreme Poverty Headcount Ratio	0.0
strata_id	int64	VUP Strata	5
s9bq7	string	Sent any cash to the HH	``
s9bq10	string	Payments require remboursment	``
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	EICV7 (VUP): Transfers in
source_resource	string	Source table name.	eicv7_vup_s9b_transfers_in
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	b3a7b91f-de30-4018-8f5b-a85bec42d18c
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	b3a7b91f-de30-4018-8f5b-a85bec42d18c
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/b3a7b91f-de30-4018-8f5b-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T16:36:19Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv7-vup-transfers-in-d6285be2")
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_eicv7_vup_transfers_in_d6285be2_2026,
  title        = {EICV7 (VUP): Transfers in | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/b3a7b91f-de30-4018-8f5b-a85bec42d18c},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv7-vup-transfers-in-d6285be2}}
}

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/b3a7b91f-de30-4018-8f5b-a85bec42d18c/download?format=csv