electricsheepafrica/africa-rwanda-eicv5-credits-127f9652

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

14,580 rows - 1 Africa country/area - 2016-10-13-2017-10-22 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 14,580 rows from Rwanda Data Sharing Platform - NISR, covering EICV5: Credits. 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 credits 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.

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	14,580
Countries/areas	1
First period	2016-10-13
Last period	2017-10-22
Indicators	0
Columns	24
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
RWA	14,580	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.	e4d5344a-bf28-4d1d-8261-02113921862a: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 ID	200001.0
clust	double	Cluster	10001.0
province	string	Province	Kigali City
district	string	District Name	Nyarugenge
ur	string	Urban/Rural	Urban
region	string	Region	Kigali
weight	double	Household weight	159.24864
poverty	string	Welfare categories	Non Poor
quintile	string	Quintile	Q5
s10aq1	bool	Household member tried to obtain a loan	False
s10aq2	string	Reason why loan was denied	``
s10aq3	bool	Household members owe money	False
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	EICV5: Credits
source_resource	string	Source resource title, table name, or file name.	eicv5_s10a1_credits
source_package_id	string	Source package identifier.	e4d5344a-bf28-4d1d-8261-02113921862a
source_resource_id	string	Source resource identifier.	e4d5344a-bf28-4d1d-8261-02113921862a
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/e4d5344a-bf28-4d1d-826...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T10:37:04Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv5-credits-127f9652")
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_s10a1_credits
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T10:39:44Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-eicv5-credits-127f9652

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_credits_127f9652_2017,
  title        = {EICV5: Credits | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2017},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/e4d5344a-bf28-4d1d-8261-02113921862a},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv5-credits-127f9652}}
}

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/e4d5344a-bf28-4d1d-8261-02113921862a