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electricsheepasia/asia-owid-incidence-of-child-labour-boys-vs-girls

Incidence Of Child Labour Boys Vs Girls | Asia (Our World in Data) 🌏 65 observations · 26 Asia countries · 1996–2016 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 65 observations of Incidence Of Child Labour Boys Vs Girls data across 26 Asia countries, spanning 1996–2016. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Incidence Of Child Labour Boys Vs Girls… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-owid-incidence-of-child-labour-boys-vs-girls.

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Dataset Card

Incidence Of Child Labour Boys Vs Girls | Asia (Our World in Data)

🌏 65 observations · 26 Asia countries · 1996–2016 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

TL;DR

This dataset contains 65 observations of Incidence Of Child Labour Boys Vs Girls data across 26 Asia countries, spanning 1996–2016.

About the source

—Source: Our World in Data
—Publisher: Our World in Data
—License: cc-by-4.0
—Topic: Incidence Of Child Labour Boys Vs Girls

Geographic coverage

26 Asia countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
`IND`	5	2000	2012
`MNG`	5	2000	2013
`KGZ`	4	1998	2014
`KHM`	4	2001	2012
`IRQ`	3	2000	2011
`YEM`	3	1999	2010
`NPL`	3	1999	2014
`IDN`	3	2000	2010
`UZB`	3	2000	2006
`BGD`	3	2003	2013
`VNM`	3	2006	2012
`PAK`	2	2008	2011
`PHL`	2	2001	2011
`KAZ`	2	1996	2006
`AZE`	2	2000	2005
...	11 more countries

Schema

Column	Type	Description	Example
`country_name`	`string`	—	`Afghanistan`
`country_iso3`	`string`	—	`AFG`
`year`	`int64`	—	`2011`
`Girls in employment`	`float64`	—	`5.1`
`Boys in employment`	`float64`	—	`13.1`
`Population`	`int64`	—	`29347708`
`World region according to OWID`	`string`	—	`Asia`

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-owid-incidence-of-child-labour-boys-vs-girls")
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.sort_values("year")
sample.plot(x="year", y="Girls in employment")

Citation

bibtex

@misc{asia_owid_incidence_of_child_labour_boys_vs_girls_2016,
  title        = {Incidence Of Child Labour Boys Vs Girls | Asia (Our World in Data)},
  author       = {Our World in Data},
  year         = {2016},
  url          = {https://ourworldindata.org/grapher/incidence-of-child-labour-boys-vs-girls},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-incidence-of-child-labour-boys-vs-girls}}
}

License

Released under cc-by-4.0.

Original data © Our World in Data. 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 2026-06-11 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/incidence-of-child-labour-boys-vs-girls