electricsheepafrica/africa-rwanda-eicv7-transfers-in-3fe32c8b

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

33,353 rows - 1 Africa country/area - 2023-10-16-2024-10-15 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 33,353 rows from Rwanda Data Sharing Platform - NISR, covering EICV7: 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 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 cross-sectional 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.

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	33,353
Countries/areas	1
First period	2023-10-16
Last period	2024-10-15
Indicators	0
Columns	34
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
RWA	33,353	2023-10-16	2024-10-15	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.	4eb8c6f3-0945-4c09-bc42-fa27f64beb66:0
country_iso3	string	ISO3 country or area code.	RWA
country_name	string	Country or area name.	Rwanda
id	int64	Row ID	1
hhid	double	Household Identification	300001.0
clust	double	Cluster	10001.0
province	string	Numeric code (1–5) representing the administrative province of Rwanda where the survey respondent is located. 1 = Kigali City, 2 = Southern Province, 3 = Western Province, 4 = Northern Province, 5 = Eastern Province.	City of Kigali
district	string	Numeric code (11–57) representing the respondent's district in Rwanda. The first digit corresponds to the province (1-5), and the second digit identifies the district within that province. 11 = Nyarugenge, 12 = Gasabo, 13 = Kicukiro, 21 = Nyanza, 22 = Gisagara, 23 = Nyaruguru, 24 = Huye, 25 = Nyamagabe, 26 = Ruhango, 27 = Muhanga, 28 = Kamonyi, 31 = Karongi, 32 = Rutsiro, 33 = Rubavu, 34 = Nyabihu, 35 = Ngororero, 36 = Rusizi, 37 = Nyamasheke, 41 = Rulindo, 42 = Gakenke, 43 = Musanze, 44 = Burera, 45 = Gicumbi, 51 = Rwamagana, 52 = Nyagatare, 53 = Gatsibo, 54 = Kayonza, 55 = Kirehe, 56 = Ngoma, 57 = Bugesera.	Nyarugenge
ur	string	Residence area	Urban
s9bq0	bool	During the last 12 months, has this household received money or goods in kind from a member of the household or from another person?	True
s9bq1a	double	How many people did [name] send money	99.0
s9bq2	double	ID number of concern	97.0
s9bq3	double	ID number of sender	1.0
s9bq4	string	Relation with head of household	No relatiive-rwandese
s9bq5	string	Sex	Female
s9bq6	string	Location of sender	Kigali
s9bq8	double	Total amount of cash received in the last 12 months	100000.0
s9bq9	string	Main method for receiving money	Telephone
strata_id	int64	Strata ID	111
weight	double	Household Weight	170.95819504509035
epov_jan	string	Extreme Poverty	Non Extreme Poor
pov_jan	string	Poverty Rate	Non Poor
poverty	string	Welfare Categories	Non Poor
quintile	string	Quintiles of real consumption per ae	Q5
s9bq7	string	Sent any cash to the HH	``
s9bq10	string	Payments require reimbursement	``
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	EICV7: Transfers in
source_resource	string	Source resource title, table name, or file name.	eicv7_s9b_transfers_in
source_package_id	string	Source package identifier.	4eb8c6f3-0945-4c09-bc42-fa27f64beb66
source_resource_id	string	Source resource identifier.	4eb8c6f3-0945-4c09-bc42-fa27f64beb66
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/4eb8c6f3-0945-4c09-bc4...
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-eicv7-transfers-in-3fe32c8b")
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: eicv7_s9b_transfers_in
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T16:40:04Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-eicv7-transfers-in-3fe32c8b

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_eicv7_transfers_in_3fe32c8b_2024,
  title        = {EICV7: Transfers in | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2024},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/4eb8c6f3-0945-4c09-bc42-fa27f64beb66},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv7-transfers-in-3fe32c8b}}
}

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/4eb8c6f3-0945-4c09-bc42-fa27f64beb66