electricsheepafrica/africa-rwanda-table-4-11-proportion-of-individuals-aged-10-years-and-abo-0a0c6c4c

Table 4.11: Proportion of individuals aged 10 years and above who used computer skills in last three months according to area of residence, province and sex | Africa (Rwanda Data Sharing Platform - NISR)

9 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 4.11: Proportion of individuals aged 10 years and above who used computer skills in last three months according to area of residence, province and sex
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: a0977d71-895b-48f3-ae36-1621dd32c68e
• Schema: EICV7_Main_Indicators
• Table: eicv7_main_indicators_table4.11
• 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 proportion of individuals aged 10 years and above who used computer skills in last three months according to area of residence, province 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: Computer skills 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	9	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.	a0977d71-895b-48f3-ae36-1621dd32c68e:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
computer_skills	string	Computer skills	Copying or moving a file or a folder
rwanda	float64	Rwanda	5.573295744
sex_male	float64	Sex: Male	7.115198466
sex_female	float64	Sex: Female	4.203030877
area_of_residence_urban	float64	Area of residence: Urban	13.01300064
area_of_residence_rural	float64	Area of residence: Rural	2.582589957
province_city_of_kigali	float64	Province: City of Kigali	14.91073628
province_southern	float64	Province: Southern	4.098035358
province_western	float64	Province: Western	4.251136661
province_northern	float64	Province: Northern	4.00846831
province_eastern	float64	Province: Eastern	3.864835974
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	Table 4.11: Proportion of individuals aged 10 years and above who used...
source_resource	string	Source table name.	eicv7_main_indicators_table4.11
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	a0977d71-895b-48f3-ae36-1621dd32c68e
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	a0977d71-895b-48f3-ae36-1621dd32c68e
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/a0977d71-895b-48f3-ae36-...
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-4-11-proportion-of-individuals-aged-10-years-and-abo-0a0c6c4c")
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_4_11_proportion_of_individuals_aged_10_years_and_abo_0a0c6c4_2026,
  title        = {Table 4.11: Proportion of individuals aged 10 years and above who used computer skills in last three months according to area of residence, province and sex | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/a0977d71-895b-48f3-ae36-1621dd32c68e},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-table-4-11-proportion-of-individuals-aged-10-years-and-abo-0a0c6c4c}}
}

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/a0977d71-895b-48f3-ae36-1621dd32c68e/download?format=csv