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electricsheepasia/asia-who-tobacco-mpower-overview-monitor

Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes | Asia (WHO GHO) ๐ŸŒ 3,248 observations ยท 48 Asia countries ยท 2007โ€“2024 ยท Repackaged by Electric Sheep Asia TL;DR This dataset contains 3,248 observations of Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes data across 48 Asia countries, spanning 2007โ€“2024, covering 1 distinct indicators.โ€ฆ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-tobacco-mpower-overview-monitor.

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Dataset Card

Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes | Asia (WHO GHO)

๐ŸŒ 3,248 observations ยท 48 Asia countries ยท 2007โ€“2024 ยท Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 3,248 observations of Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes data across 48 Asia countries, spanning 2007โ€“2024, covering 1 distinct indicators.

About the source

  • โ€”Source: WHO Global Health Observatory
  • โ€”Publisher: World Health Organization
  • โ€”License: cc-by-4.0
  • โ€”Topic: Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes

Geographic coverage

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

CountryRowsFirst yearLast year
AFG6820072024
ARE6820072024
ARM6820072024
AZE6820072024
BGD6820072024
BHR6820072024
CYP6820072024
CHN6820072024
IND6820072024
IRN6820072024
GEO6820072024
IDN6820072024
IRQ6820072024
ISR6820072024
JPN6820072024
...33 more countries

Indicators (sample)

  • โ€”TOBACCO_MPOWER_OVERVIEW

Schema

ColumnTypeDescriptionExample
indicator_codeobjectโ€”TOBACCO_MPOWER_OVERVIEW
country_iso3objectโ€”AFG
who_regionobjectโ€”EMR
yearint64โ€”2007
dim1_typeobjectโ€”TOBACCO_INDICATOR
dim1objectโ€”TOBACCO_INDICATOR_E_Group
value_numericfloat64โ€”4.0
value_lowobjectโ€”โ€”
value_highobjectโ€”โ€”
value_displayobjectโ€”4
last_updatedobjectโ€”2025-07-04T09:43:32.187+02:00

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • โ€”`dim1_type` (1 unique values): TOBACCO_INDICATOR
  • โ€”`dim1` (7 unique values): TOBACCO_INDICATOR_E_Group, TOBACCO_INDICATOR_M_Group, TOBACCO_INDICATOR_O_Group, TOBACCO_INDICATOR_P_Group, TOBACCO_INDICATOR_R_Group

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-who-tobacco-mpower-overview-monitor")
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"] == "TOBACCO_MPOWER_OVERVIEW"]
          .sort_values("year"))
sample.plot(x="year", y="value_numeric", title="TOBACCO_MPOWER_OVERVIEW")

Pivot to country ร— year matrix

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

Citation

bibtex
@misc{asia_who_tobacco_mpower_overview_monitor_2024,
  title        = {Tobacco MPOWER overview: Monitor, Protect people, Offer help, Warn of dangers, Enforce bans, Raise taxes | 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-tobacco-mpower-overview-monitor}}
}

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