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electricsheepasia/asia-who-pharmaceutical-technicians-and-assistants

Pharmaceutical Technicians and Assistants (number) | Asia (WHO GHO) ๐ŸŒ 182 observations ยท 28 Asia countries ยท 1983โ€“2024 ยท Repackaged by Electric Sheep Asia TL;DR This dataset contains 182 observations of Pharmaceutical Technicians and Assistants (number) data across 28 Asia countries, spanning 1983โ€“2024, covering 1 distinct indicators. About the source Source: WHO Global Health Observatory Publisher: World Health Organization License:โ€ฆ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-pharmaceutical-technicians-and-assistants.

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Dataset Card

Pharmaceutical Technicians and Assistants (number) | Asia (WHO GHO)

๐ŸŒ 182 observations ยท 28 Asia countries ยท 1983โ€“2024 ยท Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 182 observations of Pharmaceutical Technicians and Assistants (number) data across 28 Asia countries, spanning 1983โ€“2024, covering 1 distinct indicators.

About the source

Geographic coverage

28 Asia countries ยท top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
MYS4219832024
OMN2619852022
BGD1220082023
ISR1220102024
IDN1119922024
VNM1120052017
NPL920042024
BTN920042022
TLS820042015
MNG620022024
TUR520192023
KHM519962014
YEM419972014
MDV320152020
QAT220232024
...13 more countries

Indicators (sample)

  • โ€”HWF_0016

Schema

ColumnTypeDescriptionExample
indicator_codeobjectโ€”HWF_0016
country_iso3objectโ€”AFG
who_regionobjectโ€”EMR
yearint64โ€”2023
value_numericfloat64โ€”4805.0
value_lowobjectโ€”โ€”
value_highobjectโ€”โ€”
value_displayobjectโ€”4805
last_updatedobjectโ€”2026-01-23T14:42:53.613+01:00

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-who-pharmaceutical-technicians-and-assistants")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
indonesia = df[df["country_iso3"] == "IDN"]

Time-series for a single indicator

python
sample = (df[df["indicator_code"] == "HWF_0016"]
          .sort_values("year"))
sample.plot(x="year", y="value_numeric", title="HWF_0016")

Pivot to country ร— year matrix

python
matrix = (df[df["indicator_code"] == "HWF_0016"]
          .pivot_table(index="year", columns="country_iso3", values="value_numeric"))
print(matrix.tail())

Citation

bibtex
@misc{asia_who_pharmaceutical_technicians_and_assistants_2024,
  title        = {Pharmaceutical Technicians and Assistants  (number) | Asia (WHO GHO)},
  author       = {World Health Organization},
  year         = {2024},
  url          = {https://www.who.int/data/gho},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-who-pharmaceutical-technicians-and-assistants}}
}

License

Released under cc-by-4.0.

Original data ยฉ 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