electricsheepafrica/africa-rwanda-eicv5-vup-expenditure-last-7-days-1-57d41924

EICV5 (VUP): Expenditure (last 7 days) (1) | Africa (Rwanda Data Sharing Platform - NISR)

60,828 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 (VUP): Expenditure (last 7 days) (1)
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 5764bdd0-5cf1-4d28-b064-57c3d1b3a578
• Schema: EICV5_VUP
• Table: eicv5_vup_s8a3_expenditure
• 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 expenditure in the last 7 days 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 VUP 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: Article, Description, Coicop code, Months purchased, Amount spent over the last 7 days Purpose: The main objective of the EICV5 VUP Panel Survey is to provide longitudinal data for a nationally-representative panel of households that received VUP benefits at the time of the EICV4, in order to obtain reliable estimates of trends in the socioeconomic indicators for these households. Data Quality Notes: Following the EICV5 data collection it was found that 175 of these households could not be interviewed because of a death or move outside the country. Therefore the final number of eligible EICV5 VUP panel sample households was 1,642, including 324 households from split. For more information on the EICV5 VUP Sample 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	60,828	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.	5764bdd0-5cf1-4d28-b064-57c3d1b3a578:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
key_17	float64	EICV5 Household unique ID	11000100.0
hhid	float64	Household ID in EICV4	110001.0
clust	float64	Cluster	11231.0
province	string	Province	Kigali City
district	string	District Name	Nyarugenge
ur	string	Urban/Rural	Rural
weight	float64	Household weight	28.08333396911621
s8a3q0	string	Article	Kerosene
s8a3q0d	string	description	Peteroli
s8a3q1	string	COICOP code	04.5.3.1.01
s8a3q2	float64	Months purchased	``
s8a3q3	int64	Amount spent over the last 7 days	0
s8a3q4	float64	Visit 2	``
s8a3q5	float64	Visit 3	``
s8a3q6	float64	Visit 4	``
s8a3q7	float64	Visit 5	``
s8a3q8	float64	Visit 6	``
s8a3q9	float64	Visit 7	``
s8a3q10	float64	Visit 8	``
s8a3q11	float64	Visit 9	``
s8a3q12	float64	Visit 10	``
s8a3q13	float64	Visit 11	``
s8a3q14	string	Place of purchase	``
s0q18m	int64	Month of interview	4
s0q18y	int64	Year of interview	2017
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	EICV5 (VUP): Expenditure (last 7 days) (1)
source_resource	string	Source table name.	eicv5_vup_s8a3_expenditure
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	5764bdd0-5cf1-4d28-b064-57c3d1b3a578
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	5764bdd0-5cf1-4d28-b064-57c3d1b3a578
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/5764bdd0-5cf1-4d28-b064-...
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-vup-expenditure-last-7-days-1-57d41924")
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_vup_expenditure_last_7_days_1_57d41924_2026,
  title        = {EICV5 (VUP): Expenditure (last 7 days) (1) | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/5764bdd0-5cf1-4d28-b064-57c3d1b3a578},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv5-vup-expenditure-last-7-days-1-57d41924}}
}

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/5764bdd0-5cf1-4d28-b064-57c3d1b3a578/download?format=csv