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country_name
stringclasses
43 values
country_iso3
stringclasses
43 values
year
int64
2k
2.02k
Proportion of population with primary reliance on clean fuels and technologies for cooking (%) - Residence area type: Total
float64
0
100
Algeria
DZA
2,000
96.5
Algeria
DZA
2,001
97
Algeria
DZA
2,002
97.45
Algeria
DZA
2,003
97.8
Algeria
DZA
2,004
98.1
Algeria
DZA
2,005
98.4
Algeria
DZA
2,006
98.6
Algeria
DZA
2,007
98.8
Algeria
DZA
2,008
99
Algeria
DZA
2,009
99.2
Algeria
DZA
2,010
99.2
Algeria
DZA
2,011
99.3
Algeria
DZA
2,012
99.4
Algeria
DZA
2,013
99.5
Algeria
DZA
2,014
99.5
Algeria
DZA
2,015
99.6
Algeria
DZA
2,016
99.6
Algeria
DZA
2,017
99.6
Algeria
DZA
2,018
99.7
Algeria
DZA
2,019
99.7
Algeria
DZA
2,020
99.7
Algeria
DZA
2,021
99.7
Algeria
DZA
2,022
99.7
Algeria
DZA
2,023
99.7
Angola
AGO
2,000
40.3
Angola
AGO
2,001
41
Angola
AGO
2,002
41.4
Angola
AGO
2,003
41.7
Angola
AGO
2,004
42.1
Angola
AGO
2,005
42.8
Angola
AGO
2,006
43.2
Angola
AGO
2,007
43.35
Angola
AGO
2,008
43.9
Angola
AGO
2,009
44.1
Angola
AGO
2,010
44.7
Angola
AGO
2,011
44.9
Angola
AGO
2,012
45.6
Angola
AGO
2,013
46.1
Angola
AGO
2,014
46.8
Angola
AGO
2,015
47
Angola
AGO
2,016
48
Angola
AGO
2,017
48.2
Angola
AGO
2,018
48.8
Angola
AGO
2,019
49.2
Angola
AGO
2,020
49.4
Angola
AGO
2,021
49.8
Angola
AGO
2,022
50
Angola
AGO
2,023
50.2
Benin
BEN
2,000
0.7
Benin
BEN
2,001
0.9
Benin
BEN
2,002
1.2
Benin
BEN
2,003
1.5
Benin
BEN
2,004
1.9
Benin
BEN
2,005
2.3
Benin
BEN
2,006
2.8
Benin
BEN
2,007
3.3
Benin
BEN
2,008
3.8
Benin
BEN
2,009
4.2
Benin
BEN
2,010
4.5
Benin
BEN
2,011
4.7
Benin
BEN
2,012
4.9
Benin
BEN
2,013
5
Benin
BEN
2,014
5.1
Benin
BEN
2,015
5.2
Benin
BEN
2,016
5.2
Benin
BEN
2,017
5.4
Benin
BEN
2,018
5.4
Benin
BEN
2,019
5.5
Benin
BEN
2,020
5.7
Benin
BEN
2,021
5.8
Benin
BEN
2,022
5.9
Benin
BEN
2,023
6
Botswana
BWA
2,000
44.7
Botswana
BWA
2,001
46.5
Botswana
BWA
2,002
48.2
Botswana
BWA
2,003
49.6
Botswana
BWA
2,004
50.9
Botswana
BWA
2,005
52.1
Botswana
BWA
2,006
53.1
Botswana
BWA
2,007
54.8
Botswana
BWA
2,008
55.9
Botswana
BWA
2,009
57.4
Botswana
BWA
2,010
58.3
Botswana
BWA
2,011
59.8
Botswana
BWA
2,012
60.5
Botswana
BWA
2,013
61.2
Botswana
BWA
2,014
62
Botswana
BWA
2,015
62.4
Botswana
BWA
2,016
63.1
Botswana
BWA
2,017
63.5
Botswana
BWA
2,018
64.1
Botswana
BWA
2,019
64.7
Botswana
BWA
2,020
65.1
Botswana
BWA
2,021
65.6
Botswana
BWA
2,022
66
Botswana
BWA
2,023
66.4
Burkina Faso
BFA
2,000
2.6
Burkina Faso
BFA
2,001
2.9
Burkina Faso
BFA
2,002
3.1
Burkina Faso
BFA
2,003
3.4
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Access To Clean Fuels And Technologies For Cooking | Africa (Our World in Data)

🌍 1,272 observations · 53 Africa countries · 2000–2023 · Repackaged by Electric Sheep Africa

rows countries years license

TL;DR

This dataset contains 1,272 observations of Access To Clean Fuels And Technologies For Cooking data across 53 Africa countries, spanning 2000–2023.

About the source

  • Source: Our World in Data
  • Publisher: Our World in Data
  • License: cc-by-4.0
  • Topic: Access To Clean Fuels And Technologies For Cooking

Geographic coverage

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

Country Rows First year Last year
AGO 24 2000 2023
BDI 24 2000 2023
BEN 24 2000 2023
BFA 24 2000 2023
BWA 24 2000 2023
CAF 24 2000 2023
CIV 24 2000 2023
CMR 24 2000 2023
COD 24 2000 2023
COG 24 2000 2023
COM 24 2000 2023
CPV 24 2000 2023
DJI 24 2000 2023
DZA 24 2000 2023
EGY 24 2000 2023
... 38 more countries

Schema

Column Type Description Example
country_name string Algeria
country_iso3 string DZA
year int64 2000
Proportion of population with primary reliance on clean fuels and technologies for cooking (%) - Residence area type: Total float64 96.5

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-owid-access-to-clean-fuels-and-technologies-for-cooking")
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.sort_values("year")
sample.plot(x="year", y="Proportion of population with primary reliance on clean fuels and technologies for cooking (%) - Residence area type: Total")

Citation

@misc{africa_owid_access_to_clean_fuels_and_technologies_for_cooking_2023,
  title        = {Access To Clean Fuels And Technologies For Cooking | Africa (Our World in Data)},
  author       = {Our World in Data},
  year         = {2023},
  url          = {https://ourworldindata.org/grapher/access-to-clean-fuels-and-technologies-for-cooking},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-access-to-clean-fuels-and-technologies-for-cooking}}
}

License

Released under cc-by-4.0.

Original data © Our World in Data. 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


Provenance: ingested 2026-06-01 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/access-to-clean-fuels-and-technologies-for-cooking

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