electricsheepafrica/africa-rwanda-prevalence-of-malaria-in-women-2019-2020-1dbef4ed

Prevalence of Malaria in Women (2019-2020) | Africa (Rwanda Data Sharing Platform - NISR)

23 rows - 1 Africa country - 2019-10-01-2020-10-30 - 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: Prevalence of Malaria in Women (2019-2020)
• Publisher: NISR
• Portal: Rwanda Data Sharing Platform
• Dataset ID: 4741cb16-4f3c-4112-9cab-8564bbddd5ca
• Schema: DHS6_Final_Report
• Table: dhs6_final_report_table12.16
• Sectors: National Statistics, Health
• Source tags: Aggregated data
• Period: 2019-10-01-2020-10-30
• Resource: CSV package
• License: CC BY 4.0
• Packaging mode: tabular_resource

Source description

Summary: This aggregated data table contains data on the prevalence of malaria in women. This data was collected in the sixth Rwanda Demographic and Health Survey (DHS6), 2019-2020. The DHS6 (or RDHS-VI) involved interviewing a randomly selected group of women who are between 15 and 49 years of age. Additionally, a sub-sample of randomly selected men between 15 and 59 years of age were interviewed in one household in every two selected for the female survey. Geographic Coverage: The Rwanda Demographic and Health Survey 2019-2020 was a nation-wide survey (Rwanda). Time Period: Data collection began on 2019-10-01 and ended on 2020-10-30. Frequency: The Rwanda Demographic and Health Survey takes place every 5 years. The 2019-20 Rwanda Demographic and Health Survey (2019-20 RDHS) follows those implemented in 1992, 2000, 2005, 2010, and 2014-15. Population/Units: This sample survey covered men aged 15-59 years, Women aged 15-49 and Children aged 0-5 years. The unit analysis of this survey are households and individuals. Key variables: RDT positive, Microscopy positive Purpose: The Rwanda Demographic and Health Survey provides key information on population, family planning, maternal and child health, child survival, HIV/AIDS and sexually transmitted infections (STIs), reproductive health, and nutrition in Rwanda. Data Quality Notes: The household response rate was 99%; the individual women's response rate was 99%, and the individual men's response rate was also 99%. More details are available in the survey documentation.

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
RWA	23	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.	4741cb16-4f3c-4112-9cab-8564bbddd5ca:0
country_iso3	string	ISO3 country code.	RWA
country_name	string	Country name.	Rwanda
id	int64	Row ID	1
background_characteristic	string	Background characteristic	Age: 15-19
rdt_positive	float64	RDT positive	1.7
rdt_number_of_women	int64	RDT - Number of women	1620
microscopy_positive	float64	Microscopy positive	0.8
microscopy_number_of_women	int64	Microscopy - Number of women	1620
source_provider	string	Publishing organization.	NISR
source_dataset	string	Source dataset title.	Prevalence of Malaria in Women (2019-2020)
source_resource	string	Source table name.	dhs6_final_report_table12.16
source_package_id	string	Rwanda Data Sharing Platform dataset UUID.	4741cb16-4f3c-4112-9cab-8564bbddd5ca
source_resource_id	string	Rwanda Data Sharing Platform dataset UUID.	4741cb16-4f3c-4112-9cab-8564bbddd5ca
source_url	string	Original source download URL.	https://api.data.gov.rw/api/v1/datasets/public/4741cb16-4f3c-4112-9cab-...
license_id	string	Source license identifier.	cc-by-4.0
retrieved_at	string	UTC retrieval timestamp.	2026-07-18T10:37:04Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-prevalence-of-malaria-in-women-2019-2020-1dbef4ed")
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_prevalence_of_malaria_in_women_2019_2020_1dbef4ed_2026,
  title        = {Prevalence of Malaria in Women (2019-2020) | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2026},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/4741cb16-4f3c-4112-9cab-8564bbddd5ca},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-prevalence-of-malaria-in-women-2019-2020-1dbef4ed}}
}

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/4741cb16-4f3c-4112-9cab-8564bbddd5ca/download?format=csv