electricsheepafrica/africa-worldbank-current-expenditure-as-of-total-expenditure-in-tertiary-public-institutions-uis

Current expenditure as % of total expenditure in tertiary public institutions (%) | Africa (World Bank — Education Statistics)

🌍 150 observations · 29 Africa countries · 1998–2019 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 150 observations of Education Statistics data across 29 Africa countries, spanning 1998–2019, covering 1 distinct indicators.

About the source

• Source: World Bank — Education Statistics
• Publisher: World Bank
• License: cc-by-4.0
• Topic: Education Statistics

Geographic coverage

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

Country	Rows	First year	Last year
CIV	15	1998	2018
GIN	12	2008	2019
GHA	11	2001	2014
BEN	10	1998	2015
BDI	10	1999	2013
MDG	10	2005	2017
MLI	10	2008	2017
CPV	7	2004	2016
ETH	7	2009	2015
MWI	6	2010	2016
CMR	6	2008	2013
GMB	5	2008	2012
KEN	5	2011	2015
GNB	4	2010	2013
LSO	4	1999	2018
...	14 more countries

Indicators (sample)

• UIS.XSPENDP.56.FDPUB.FNCUR — Current expenditure as % of total expenditure in tertiary public institutions (%)

Schema

Column	Type	Description	Example
indicator_id	string	—	UIS.XSPENDP.56.FDPUB.FNCUR
indicator_name	string	—	Current expenditure as % of total exp…
country_iso3	string	—	AGO
country_name	string	—	Angola
year	int64	—	2006
value	float64	—	71.11404

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-worldbank-current-expenditure-as-of-total-expenditure-in-tertiary-public-institutions-uis")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

Time-series for a single indicator

sample = (df[df["indicator_id"] == "UIS.XSPENDP.56.FDPUB.FNCUR"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="UIS.XSPENDP.56.FDPUB.FNCUR")

Pivot to country × year matrix

matrix = (df[df["indicator_id"] == "UIS.XSPENDP.56.FDPUB.FNCUR"]
          .pivot_table(index="year", columns="country_iso3", values="value"))
print(matrix.tail())

Citation

@misc{africa_worldbank_current_expenditure_as_of_total_expenditure_in_tertiary_public_institutions_uis_2019,
  title        = {Current expenditure as % of total expenditure in tertiary public institutions (%) | Africa (World Bank — Education Statistics)},
  author       = {World Bank},
  year         = {2019},
  url          = {https://databank.worldbank.org/},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-worldbank-current-expenditure-as-of-total-expenditure-in-tertiary-public-institutions-uis}}
}

License

Released under cc-by-4.0.

Original data © World Bank. 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

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Provenance: ingested 2026-06-19 via the Electric Sheep pipeline. Source URL: https://databank.worldbank.org/