electricsheepafrica/africa-worldbank-initial-household-funding-per-primary-student-as-a-percentage-of-gdp-per-capita

Initial household funding per primary student as a percentage of GDP per capita | Africa (World Bank — Education Statistics)

🌍 107 observations · 16 Africa countries · 1999–2016 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 107 observations of Education Statistics data across 16 Africa countries, spanning 1999–2016, 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

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

Country	Rows	First year	Last year
CPV	10	2003	2016
BDI	9	2002	2010
CIV	9	2006	2015
BFA	9	1999	2007
CMR	9	2004	2012
MLI	9	2002	2010
MAR	9	2002	2010
GMB	9	2005	2013
BEN	8	2006	2014
GHA	8	2006	2014
MWI	8	2000	2008
TCD	5	2009	2013
ETH	2	2011	2012
GIN	1	2012	2012
LBY	1	2006	2006
...	1 more countries

Indicators (sample)

• UIS.XUNIT.GDPCAP.1.FSHH — Initial household funding per primary student as a percentage of GDP per capita

Schema

Column	Type	Description	Example
indicator_id	string	—	UIS.XUNIT.GDPCAP.1.FSHH
indicator_name	string	—	Initial household funding per primary…
country_iso3	string	—	BEN
country_name	string	—	Benin
year	int64	—	2014
value	float64	—	5.22345

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-worldbank-initial-household-funding-per-primary-student-as-a-percentage-of-gdp-per-capita")
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.XUNIT.GDPCAP.1.FSHH"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="UIS.XUNIT.GDPCAP.1.FSHH")

Pivot to country × year matrix

matrix = (df[df["indicator_id"] == "UIS.XUNIT.GDPCAP.1.FSHH"]
          .pivot_table(index="year", columns="country_iso3", values="value"))
print(matrix.tail())

Citation

@misc{africa_worldbank_initial_household_funding_per_primary_student_as_a_percentage_of_gdp_per_capita_2016,
  title        = {Initial household funding per primary student as a percentage of GDP per capita | Africa (World Bank — Education Statistics)},
  author       = {World Bank},
  year         = {2016},
  url          = {https://databank.worldbank.org/},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-worldbank-initial-household-funding-per-primary-student-as-a-percentage-of-gdp-per-capita}}
}

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/