electricsheepafrica/africa-worldbank-all-staff-compensation-as-of-total-expenditure-in-tertiary-public-institutions

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

🌍 115 observations · 25 Africa countries · 1998–2019 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 115 observations of Education Statistics data across 25 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

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

Country	Rows	First year	Last year
CIV	14	1998	2018
GHA	11	2001	2014
MLI	9	2009	2017
BDI	8	1999	2013
BEN	7	1998	2015
ETH	7	2009	2015
GIN	7	2013	2019
CMR	5	2008	2013
KEN	5	2011	2015
CPV	5	2004	2016
GMB	5	2008	2012
MDG	4	2013	2017
COM	4	1998	2015
CAF	4	2005	2010
GNB	4	2010	2013
...	10 more countries

Indicators (sample)

• UIS.XSPENDP.56.FDPUB.FNS — All staff compensation as % of total expenditure in tertiary public institutions (%)

Schema

Column	Type	Description	Example
indicator_id	string	—	UIS.XSPENDP.56.FDPUB.FNS
indicator_name	string	—	All staff compensation as % of total …
country_iso3	string	—	BEN
country_name	string	—	Benin
year	int64	—	2015
value	float64	—	57.47302

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-worldbank-all-staff-compensation-as-of-total-expenditure-in-tertiary-public-institutions")
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.FNS"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="UIS.XSPENDP.56.FDPUB.FNS")

Pivot to country × year matrix

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

Citation

@misc{africa_worldbank_all_staff_compensation_as_of_total_expenditure_in_tertiary_public_institutions_2019,
  title        = {All staff compensation 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-all-staff-compensation-as-of-total-expenditure-in-tertiary-public-institutions}}
}

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/