electricsheepasia/asia-who-prevalence-of-anaemia-in-women-of-reproductive-age
Prevalence of anaemia in women of reproductive age (aged 15-49) (%) | Asia (WHO GHO) π 3,456 observations Β· 48 Asia countries Β· 2000β2023 Β· Repackaged by Electric Sheep Asia TL;DR This dataset contains 3,456 observations of Prevalence of anaemia in women of reproductive age (aged 15-49) (%) data across 48 Asia countries, spanning 2000β2023, covering 1 distinct indicators. About the source Source: WHO Global Health Observatory Publisher: Worldβ¦ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-prevalence-of-anaemia-in-women-of-reproductive-age.
Prevalence of anaemia in women of reproductive age (aged 15-49) (%) | Asia (WHO GHO)
π 3,456 observations Β· 48 Asia countries Β· 2000β2023 Β· Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)
TL;DR
This dataset contains 3,456 observations of Prevalence of anaemia in women of reproductive age (aged 15-49) (%) data across 48 Asia countries, spanning 2000β2023, covering 1 distinct indicators.
About the source
- Source: WHO Global Health Observatory
- Publisher: World Health Organization
- License: cc-by-4.0
- Topic: Prevalence of anaemia in women of reproductive age (aged 15-49) (%)
Geographic coverage
48 Asia countries Β· top rows shown below, sorted by row count:
Indicators (sample)
NUTRITION_ANAEMIA_REPRODUCTIVEAGE_PREV
Schema
Disaggregation dimensions
The following columns provide disaggregation dimensions:
- `dim1_type` (1 unique values):
SEX - `dim1` (1 unique values):
SEX_FMLE - `dim2_type` (1 unique values):
PREGNANCYSTATUS - `dim2` (3 unique values):
PREGNANCYSTATUS_NONPREGNANT,PREGNANCYSTATUS_PREGNANT,PREGNANCYSTATUS_TOTAL
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-who-prevalence-of-anaemia-in-women-of-reproductive-age")
df = ds["train"].to_pandas()
print(df.head())Filter to one country
indonesia = df[df["country_iso3"] == "IDN"]Time-series for a single indicator
sample = (df[df["indicator_code"] == "NUTRITION_ANAEMIA_REPRODUCTIVEAGE_PREV"]
.sort_values("year"))
sample.plot(x="year", y="value_numeric", title="NUTRITION_ANAEMIA_REPRODUCTIVEAGE_PREV")Pivot to country Γ year matrix
matrix = (df[df["indicator_code"] == "NUTRITION_ANAEMIA_REPRODUCTIVEAGE_PREV"]
.pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())Citation
@misc{asia_who_prevalence_of_anaemia_in_women_of_reproductive_age_2023,
title = {Prevalence of anaemia in women of reproductive age (aged 15-49) (%) | Asia (WHO GHO)},
author = {World Health Organization},
year = {2023},
url = {https://www.who.int/data/gho},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-who-prevalence-of-anaemia-in-women-of-reproductive-age}}
}License
Released under cc-by-4.0.
Original data Β© World Health Organization. When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.
About Electric Sheep
Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. 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/electricsheepasia
Provenance: ingested 2026-05-29 via the Electric Sheep pipeline. Source URL: https://www.who.int/data/gho
