electricsheepafrica/africa-worldbank-teaching-staff-compensation-as-a-percentage-of-total-expenditure-in-lower-secon

Teaching staff compensation as a percentage of total expenditure in lower secondary public institutions (%) | Africa (World Bank — Education Statistics)

🌍 91 observations · 20 Africa countries · 1999–2019 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 91 observations of Education Statistics data across 20 Africa countries, spanning 1999–2019, 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

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

Country	Rows	First year	Last year
CIV	13	2006	2018
GIN	12	2008	2019
MLI	10	2008	2017
GHA	8	2004	2012
BFA	6	2011	2016
GMB	6	2008	2013
KEN	5	2011	2015
GNB	4	2010	2013
CMR	4	2008	2011
BEN	3	2010	2013
MOZ	3	2004	2013
DJI	3	2008	2016
TCD	3	2009	2012
MDG	3	2007	2013
CAF	2	2005	2008
...	5 more countries

Indicators (sample)

• UIS.XSPENDP.2.FDPUB.FNTS — Teaching staff compensation as a percentage of total expenditure in lower secondary public institutions (%)

Schema

Column	Type	Description	Example
indicator_id	string	—	UIS.XSPENDP.2.FDPUB.FNTS
indicator_name	string	—	Teaching staff compensation as a perc…
country_iso3	string	—	DZA
country_name	string	—	Algeria
year	int64	—	2017
value	float64	—	22.1494

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-worldbank-teaching-staff-compensation-as-a-percentage-of-total-expenditure-in-lower-secon")
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.2.FDPUB.FNTS"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="UIS.XSPENDP.2.FDPUB.FNTS")

Pivot to country × year matrix

matrix = (df[df["indicator_id"] == "UIS.XSPENDP.2.FDPUB.FNTS"]
          .pivot_table(index="year", columns="country_iso3", values="value"))
print(matrix.tail())

Citation

@misc{africa_worldbank_teaching_staff_compensation_as_a_percentage_of_total_expenditure_in_lower_secon_2019,
  title        = {Teaching staff compensation as a percentage of total expenditure in lower secondary 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-teaching-staff-compensation-as-a-percentage-of-total-expenditure-in-lower-secon}}
}

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/