electricsheepasia/asia-humanitarian-needs-who-historical-data-for-philippines

Philippines - 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: PHL.

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), Composite coverage index (%), Alcohol, recorded per capita (15+) consumption (in litres of pure alcohol)), year_display (range 1961.0–2025.0), startyear (range 1961.0–2025.0), endyear (range 1961.0–2025.0), region_code (WPR, #region+code) and 4 others.

Outcome / Measurement — value (No data, No, Yes).

Identifier / Metadata — gho_code (NCDBMIMEANC, SA0000001400ARCHIVED, CHILDMORT10TO19), dimension_code (SEXFMLE, SEXMLE, SEXBTSX), `dimensionname (Female, Male, Both sexes), esasource`, `esaprocessed`.

Other — numeric (range 0.0–93260800.0), low (range 0.0–771359.0), high (range 0.0–1237902.0).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-humanitarian-needs-who-historical-data-for-philippines")
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`. 36 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: numeric, low, high.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_humanitarian_needs_who_historical_data_for_philippines,
  title     = {Philippines - Historical Health Indicators},
  author    = {World Health Organization},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/who-historical-data-for-phl},
  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.