electricsheepafrica/africa-rwanda-table-3-2-percentage-of-population-reporting-health-proble-b29a30d5

Table 3.2: Percentage (%) of population reporting health problem and medical consultation status according to area of residence, province, consumption quintile and sex | Africa (Rwanda Data Sharing Platform - NISR)

15 rows - 1 Africa country - 2023-10-16-2024-10-15 - 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: Table 3.2: Percentage (%) of population reporting health problem and medical consultation status according to area of residence, province, consumption quintile and sex
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 663f5ace-a725-45cc-8608-cbadc6d1405a
• Schema: EICV7_Main_Indicators
• Table: eicv7_main_indicators_table3.2
• Sectors: National Statistics, Social Protection
• Source tags: Aggregated data
• Period: 2023-10-16-2024-10-15
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This aggregated data table contains data on the percentage (%) of the population reporting health problems and medical consultation status according to area of residence, province, consumption quintile and sex. This data was collected in the seventh Integrated Household Living Conditions Survey, known as EICV7 (Enquête Intégrale sur les Conditions de Vie des ménages). 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. Population/Units: Household members Key Variables: % reporting health problem in last 4 weeks, Total population (000s), Made medical consultation?, Persons reporting health problem in last 4 weeks (000s) Purpose: This survey serves as a key source of socio-economic data on the living conditions of Rwandan households. It plays a critical role in the ongoing monitoring and evaluation of national and international development frameworks, including the Second National Strategy for Transformation (NST2), the 2030 Sustainable Development Goals (SDGs), and Vision 2050, among others. The survey data are also vital for compiling national accounts and updating the Consumer Price Index (CPI). Data Quality Notes: The response rate exceeded 99% by the end of the survey, with 15,054 out of the 15,066 targeted households successfully interviewed. More details can be found in the EICV7 Methodological notes report.

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
RWA	15	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.	663f5ace-a725-45cc-8608-cbadc6d1405a:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
area_of_residence_province_sex_consumption_quintile	string	Area of residence/Province/Sex/Consumption quintile	Rwanda
reporting_health_problem_in_last_4_weeks	float64	% reporting health problem in last 4 weeks	27.0812375
total_population_000s	float64	Total population (000s)	13549.45694
made_medical_consultation_yes	float64	Made medical consultation? Yes	70.9664711
made_medical_consultation_no	float64	Made medical consultation? No	29.0335289
persons_reporting_health_problem_in_last_4_weeks_000s	float64	Persons reporting health problem in last 4 weeks (000s)	3669.360614
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	Table 3.2: Percentage (%) of population reporting health problem and me...
source_resource	string	Source table name.	eicv7_main_indicators_table3.2
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	663f5ace-a725-45cc-8608-cbadc6d1405a
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	663f5ace-a725-45cc-8608-cbadc6d1405a
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/663f5ace-a725-45cc-8608-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T11:48:51Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-table-3-2-percentage-of-population-reporting-health-proble-b29a30d5")
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_table_3_2_percentage_of_population_reporting_health_proble_b29a30d_2026,
  title        = {Table 3.2: Percentage (%) of population reporting health problem and medical consultation status according to area of residence, province, consumption quintile and sex | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/663f5ace-a725-45cc-8608-cbadc6d1405a},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-table-3-2-percentage-of-population-reporting-health-proble-b29a30d5}}
}

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/663f5ace-a725-45cc-8608-cbadc6d1405a/download?format=csv