electricsheepafrica/africa-rwanda-eicv7-expenditure-last-4-weeks-2e19f647

EICV7: Expenditure (last 4 weeks) | Africa (Rwanda Data Sharing Platform - NISR)

978,382 rows - 1 Africa country/area - 2023-10-16-2024-10-15 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 978,382 rows from Rwanda Data Sharing Platform - NISR, covering EICV7: Expenditure (last 4 weeks). 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 expenditure in the last 4 weeks 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. 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.

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	978,382
Countries/areas	1
First period	2023-10-16
Last period	2024-10-15
Indicators	0
Columns	29
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
RWA	978,382	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.	e8aad2a9-1860-44f1-81e0-1c12cd3ace39:0
country_iso3	string	ISO3 country or area code.	RWA
country_name	string	Country or area name.	Rwanda
id	int64	Row ID	439699
hhid	double	Household Identification	306766.0
clust	double	Cluster	10753.0
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.	Western
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.	Rutsiro
ur	string	Residence area	Rural
s8a2q0	string	Item name	Beauty Treatment/Massage(Non-medical)/ Manicure & steam bath
s8a2q2	bool	Article purchased	False
s8a2q3	double	Amount spent to purchase in last 4 weeks	``
s8a2q4	string	Place where purchased in the last 4 weeks	``
s8a2q5	bool	Article received as gifts and in-kind	False
s8a2q6	double	Value of article received as gifts and in-kind	``
strata_id	int64	Strata ID	322
weight	double	Household Weight	182.12543457099156
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	Q2
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset or package title.	EICV7: Expenditure (last 4 weeks)
source_resource	string	Source resource title, table name, or file name.	eicv7_s8a2_expenditure
source_package_id	string	Source package identifier.	e8aad2a9-1860-44f1-81e0-1c12cd3ace39
source_resource_id	string	Source resource identifier.	e8aad2a9-1860-44f1-81e0-1c12cd3ace39
source_url	string	Original source URL or download URL.	https://api.data.gov.rw/api/v1/datasets/public/e8aad2a9-1860-44f1-81e...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-18T11:48:51Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-eicv7-expenditure-last-4-weeks-2e19f647")
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_s8a2_expenditure
• License: CC BY 4.0
• Retrieved/generated: 2026-07-18T12:40:00Z
• Hugging Face repo: electricsheepafrica/africa-rwanda-eicv7-expenditure-last-4-weeks-2e19f647

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_expenditure_last_4_weeks_2e19f647_2024,
  title        = {EICV7: Expenditure (last 4 weeks) | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2024},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/e8aad2a9-1860-44f1-81e0-1c12cd3ace39},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-eicv7-expenditure-last-4-weeks-2e19f647}}
}

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.

---

Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://api.data.gov.rw/api/v1/datasets/public/e8aad2a9-1860-44f1-81e0-1c12cd3ace39