electricsheepafrica/africa-rwanda-eicv5-vup-transfers-in-0795880b

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

10,844 rows - 1 Africa country/area - 2016-10-13-2017-10-22 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 10,844 rows from Rwanda Data Sharing Platform - NISR, covering EICV5 (VUP): Transfers in. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: 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 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.

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: not detected.
• Time coverage basis: source metadata period.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	10,844
Countries/areas	1
First period	2016-10-13
Last period	2017-10-22
Indicators	0
Columns	35
Source format	CSV

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
RWA	10,844	2016-10-13	2017-10-22	Rwanda

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	cce8d59c-599e-4dde-8b04-5e361adad4fc:0
country_iso3	string	ISO3 country or area code.	RWA
country_name	string	Country or area name.	Rwanda
id	int64	Row ID	1
key_17	double	EICV5 Household unique ID	11000100.0
hhid	double	Household ID in EICV4	110001.0
clust	double	Cluster	11231.0
province	string	Province	Kigali City
district	string	District Name	Nyarugenge
ur	string	Urban/Rural	Rural
weight	double	Household weight	28.083334
s9bq0	bool	Household received money or goods in kind from a member of the household or from others	True
s9bq1	string	Name of people who made the transfer to the hh	umugiraneza
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	Big town
s9bq7	double	Total amount of cash received in the last 12 months	80000.0
s9bq8	string	Main method for receiving money	In person
s9bq10	double	Total value of food products received from person in last 12 months	``
s9bq12	double	Total value of other in-kind transfers received from person in last 12 months	``
s0q18m	int64	Month of interview	4
s0q18y	int64	Year of interview	2017
s9bq6	string	Sent any cash to the HH	``
s9bq9	string	Sent food products to the HH	``
s9bq11	string	Sent other in-kind transfer	``
s9bq13	string	Payments require remboursment	``
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	EICV5 (VUP): Transfers in
source_resource	string	Source resource title, table name, or file name.	eicv5_vup_s9b_transfers_in
source_package_id	string	Source package identifier.	cce8d59c-599e-4dde-8b04-5e361adad4fc
source_resource_id	string	Source resource identifier.	cce8d59c-599e-4dde-8b04-5e361adad4fc
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/cce8d59c-599e-4dde-8b0...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T16:36:19Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv5-vup-transfers-in-0795880b")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "RWA"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: Rwanda Data Sharing Platform - NISR
• Publisher: NISR
• Portal: https://data.gov.rw/
• Resource: eicv5_vup_s9b_transfers_in
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T16:37:57Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-eicv5-vup-transfers-in-0795880b

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Profile the distribution of values
• Compare categories or geographies
• Join with complementary public datasets
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_rwanda_eicv5_vup_transfers_in_0795880b_2017,
  title        = {EICV5 (VUP): Transfers in | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2017},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/cce8d59c-599e-4dde-8b04-5e361adad4fc},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv5-vup-transfers-in-0795880b}}
}

License

Released under CC BY 4.0.

Original data is published by NISR. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://api.data.gov.rw/api/v1/datasets/public/cce8d59c-599e-4dde-8b04-5e361adad4fc