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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.

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Dataset Card

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

DomainHumanitarian and development data
Unit of observationFirst-level administrative unit observations
Rows (total)6,456
Columns18 (6 numeric, 12 categorical, 0 datetime)
Train split5,164 rows
Test split1,291 rows
Geographic scopeOMN
PublisherWorld Health Organization
HDX last updated2025-02-07

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

python
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

ColumnTypeNull %Range / Sample Values
gho_codeobject0.0%NCDBMIMEANC, SA0000001400ARCHIVED, CHILDMORT10TO19
gho_displayobject0.0%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_displayfloat640.0%1961.0 – 2025.0 (mean 2007.4017)
startyearfloat640.0%1961.0 – 2025.0 (mean 2007.3856)
endyearfloat640.0%1961.0 – 2025.0 (mean 2007.4017)
region_codeobject0.0%EMR, #region+code
region_displayobject0.0%Eastern Mediterranean, #region+name
country_codeobject0.0%OMN, #country+code
country_displayobject0.0%Oman, #country+name
dimension_typeobject31.0%SEX, ALCOHOLTYPE, TB_CASETYPE
dimension_codeobject31.0%SEXFMLE, SEXMLE, SEX_BTSX
dimension_nameobject31.0%Female, Male, Both sexes
numericfloat6426.4%0.0 – 39627329.0 (mean 31113.9731)
valueobject1.1%No, 0, Yes
lowfloat6455.3%0.0 – 9601.0 (mean 46.8847)
highfloat6455.3%0.0 – 19412.0 (mean 83.8707)
esa_sourceobject0.0%
esa_processedobject0.0%

Numeric Summary

ColumnMinMaxMeanMedian
year_display1961.02025.02007.40172010.0
startyear1961.02025.02007.38562010.0
endyear1961.02025.02007.40172010.0
numeric0.039627329.031113.973120.1368
low0.09601.046.884718.8645
high0.019412.083.870725.2811

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

bibtex
@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.