electricsheepasia/asia-who-historical-data-for-oman
Oman - Historical Health Indicators Publisher: World Health Organization · Source: HDX · License: hdx-other · Updated: 2025-02-07 Abstract This dataset contains historical data from WHO's data portal. Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-02-07. Geographic scope: OMN. Curated into ML-ready Parquet format by Electric Sheep Africa. Dataset Characteristics… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-historical-data-for-oman.
Oman - Historical Health Indicators
Publisher: World Health Organization · Source: HDX · License: hdx-other · Updated: 2025-02-07
Abstract
This dataset contains historical data from WHO's data portal.
Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-02-07. Geographic scope: OMN.
Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).
Dataset Characteristics
Variables
Geographic — gho_display (Mean BMI (kg/m²) (crude estimate), Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol), Adolescent mortality rate (per 1 000 age specific cohort)), year_display (range 1961.0–2025.0), startyear (range 1961.0–2025.0), endyear (range 1961.0–2025.0), region_code (EMR, #region+code) and 4 others.
Outcome / Measurement — value (No, 0, Yes).
Identifier / Metadata — gho_code (NCDBMIMEANC, SA0000001400ARCHIVED, CHILDMORT10TO19), dimension_code (SEXFMLE, SEXMLE, SEXBTSX), `dimensionname (Female, Male, Both sexes), esasource`, `esaprocessed`.
Other — numeric (range 0.0–39627329.0), low (range 0.0–9601.0), high (range 0.0–19412.0).
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/asia-who-historical-data-for-oman")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()Schema
Numeric Summary
Curation
Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snakecase. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 1 column(s) with >80% missing values were removed: `ghourl`. 59 exact duplicate rows were removed. 6 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
Limitations
- Data originates from World Health Organization and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling:
dimension_type,dimension_code,dimension_name,numeric,low,high. - Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.
Citation
@dataset{hdx_asia_who_historical_data_for_oman,
title = {Oman - Historical Health Indicators},
author = {World Health Organization},
year = {2025},
url = {https://data.humdata.org/dataset/who-historical-data-for-omn},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.
