electricsheepasia/asia-who-mean-systolic-blood-pressure-bp06
Africa — WHO GHO: Mean systolic blood pressure (age-standardized estimate) Indicator code: BP_06 HuggingFace slug: electricsheepafrica/asia-who-mean-systolic-blood-pressure-bp06 Source: WHO Global Health Observatory License: CC BY 4.0 — WHO Open Data Dataset Description This dataset contains country-level observations for the WHO GHO indicator "Mean systolic blood pressure (age-standardized estimate)" (BP_06) across Asian nations, spanning 1975–2015. It is part… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-mean-systolic-blood-pressure-bp06.
Africa — WHO GHO: Mean systolic blood pressure (age-standardized estimate)
Indicator code: BP_06 HuggingFace slug: electricsheepafrica/asia-who-mean-systolic-blood-pressure-bp06 Source: WHO Global Health Observatory License: CC BY 4.0 — WHO Open Data
Dataset Description
This dataset contains country-level observations for the WHO GHO indicator "Mean systolic blood pressure (age-standardized estimate)" (BP_06) across Asian nations, spanning 1975–2015. It is part of the Electric Sheep Asia collection — a unified, ML-ready repository of African data.
Data is sourced directly from the WHO Global Health Observatory OData API and repackaged as Parquet files with a consistent schema. All values are drawn from NumericValue (the float-precision field), not the display string. Confidence interval bounds (value_low, value_high) are included where available.
Coverage
Countries included: AFG, ARE, ARM, AZE, BGD, BHR, BRN, BTN, CHN, CYP, GEO, IDN, IND, IRN, IRQ, ISR, JOR, JPN, KAZ, KGZ … and 27 more
Sub-dimensions
- SEX: SEXFMLE, SEXMLE
When an indicator is stratified (e.g., by sex or age group), each unique combination of country × year × dimension produces a separate row. Filter on dim1 / dim2 for the stratum you need, or aggregate across strata.
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/asia-who-mean-systolic-blood-pressure-bp06")
df = ds["train"].to_pandas()
# Both-sexes, national level only
national = df[df.get("dim1", "").str.endswith("_BTSX") | df.get("dim1", pd.Series()).isna()]
# Time series for one country
kenya = df[df["country_iso3"] == "KEN"].sort_values("year")Citation
@misc{who_gho_bp_06,
title = {WHO Global Health Observatory: Mean systolic blood pressure (age-standardized estimate)},
author = {World Health Organization},
year = {2015},
url = {https://www.who.int/data/gho/data/indicators/indicator-details/GHO/BP_06},
note = {Repackaged by Electric Sheep Asia}
}Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia) from WHO GHO open data. Original data © World Health Organization, licensed CC BY 4.0.
