Datasets:

electricsheepafrica
/

africa-arising-korean-labor-and-income-panel-study-klips-1998-2206-wav

	---
	license: cc-by-4.0
	language:
	- en
	task_categories:
	- tabular-classification
	- tabular-regression
	- time-series-forecasting
	multilinguality: monolingual
	size_categories:
	- 10K<n<100K
	tags:
	- tabular
	- africa
	- harvard-dataverse-(ifpri-africarising)
	- household-survey-microdata
	- ifpri
	- dataverse
	- africa-rising
	- microdata
	pretty_name: "Korean Labor and Income Panel Study (KLIPS), 1998-2206: Wave 1-9 (M1194) \| Africa (Harvard Dataverse / AfricaRISING)"
	---

	# Korean Labor and Income Panel Study (KLIPS), 1998-2206: Wave 1-9 (M1194) \| Africa (Harvard Dataverse / AfricaRISING)

	🌍 87,613 observations · 0 Africa countries · —–— · Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

	![rows](https://img.shields.io/badge/rows-87,613-blue) ![countries](https://img.shields.io/badge/countries-0-green) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)

	## TL;DR

	This dataset contains 87,613 observations of `Household Survey Microdata` data across 0 Africa countries.

	## About the source

	- Source: [Harvard Dataverse (IFPRI AfricaRISING)](https://dataverse.harvard.edu/dataverse/africaRISING)
	- Publisher: International Food Policy Research Institute
	- License: [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
	- Topic: Household Survey Microdata

	## Geographic coverage

	0 Africa countries · top rows shown below, sorted by row count:

	_Per-country coverage not computable for this schema._

	## Schema

	\| Column \| Type \| Description \| Example \|
	\|--------\|------\|-------------\|---------\|
	\| `PID` \| `int64` \| — \| `101` \|
	\| `jobwave` \| `int64` \| — \| `1` \|
	\| `jobseq` \| `int64` \| — \| `1` \|
	\| `jobnum` \| `int64` \| — \| `101` \|
	\| `jobnumc` \| `float64` \| — \| `101.0` \|
	\| `jobcens` \| `int64` \| — \| `3` \|
	\| `jobtype` \| `float64` \| — \| `1.0` \|
	\| `jobclass` \| `float64` \| — \| `1.0` \|
	\| `mainjob` \| `float64` \| — \| `1.0` \|
	\| `HHID98` \| `float64` \| — \| `1.0` \|
	\| `HMEM98` \| `float64` \| — \| `1.0` \|
	\| `HHID99` \| `float64` \| — \| `1.0` \|
	\| `HMEM99` \| `float64` \| — \| `1.0` \|
	\| `HHID00` \| `float64` \| — \| `1.0` \|
	\| `HMEM00` \| `float64` \| — \| `1.0` \|
	\| `HHID01` \| `float64` \| — \| `2.0` \|
	\| `HMEM01` \| `float64` \| — \| `1.0` \|
	\| `HHID02` \| `float64` \| — \| `1.0` \|
	\| `HMEM02` \| `float64` \| — \| `1.0` \|
	\| `HHID03` \| `float64` \| — \| `1.0` \|
	\| `HMEM03` \| `float64` \| — \| `1.0` \|
	\| `HHID04` \| `float64` \| — \| `1.0` \|
	\| `HMEM04` \| `float64` \| — \| `2.0` \|
	\| `HHID05` \| `float64` \| — \| `1.0` \|
	\| `HMEM05` \| `float64` \| — \| `1.0` \|
	\| `HHID06` \| `float64` \| — \| `1.0` \|
	\| `HMEM06` \| `float64` \| — \| `1.0` \|
	\| `J001` \| `float64` \| — \| `1988.0` \|
	\| `J002` \| `float64` \| — \| `10.0` \|
	\| `J003` \| `float64` \| — \| `20.0` \|
	\| `j004` \| `float64` \| — \| `2001.0` \|
	\| `j005` \| `float64` \| — \| `6.0` \|
	\| `j006` \| `float64` \| — \| `10.0` \|
	\| `j007` \| `float64` \| — \| `1.0` \|
	\| `j008` \| `float64` \| — \| `2002.0` \|
	\| `j009` \| `float64` \| — \| `4.0` \|
	\| `j010` \| `float64` \| — \| `2003.0` \|
	\| `j011` \| `float64` \| — \| `5.0` \|
	\| `j012` \| `float64` \| — \| `999.0` \|
	\| `j013` \| `float64` \| — \| `3.0` \|
	\| _... (113 more columns)_ \| \| \| \|

	## Usage

	```python
	from datasets import load_dataset

	ds = load_dataset("electricsheepafrica/africa-arising-korean-labor-and-income-panel-study-klips-1998-2206-wav")
	df = ds["train"].to_pandas()
	print(df.head())
	```

	### Filter to one country

	```python
	kenya = df[df["country_iso3"] == "KEN"]
	```

	### Time-series for a single indicator

	```python
	sample = df.sort_values("year")
	sample.plot(x="year", y="value")
	```

	## Citation

	```bibtex
	@misc{africa_arising_korean_labor_and_income_panel_study_klips_1998_2206_wav_2026,
	title = {Korean Labor and Income Panel Study (KLIPS), 1998-2206: Wave 1-9 (M1194) \| Africa (Harvard Dataverse / AfricaRISING)},
	author = {International Food Policy Research Institute},
	year = {2026},
	url = {https://dataverse.harvard.edu/dataverse/africaRISING},
	publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
	howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-arising-korean-labor-and-income-panel-study-klips-1998-2206-wav}}
	}
	```

	## License

	Released under [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/).

	Original data © International Food Policy Research Institute. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

	## About Electric Sheep

	Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa 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/electricsheepafrica](https://huggingface.co/electricsheepafrica)

	---

	_Provenance: ingested 2026-05-26 via the Electric Sheep pipeline. Source URL: https://dataverse.harvard.edu/dataverse/africaRISING_