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year
int64
1.96k
2.02k
Algeria
float64
22.4
28.2
Angola
float64
22.7
25.2
Benin
float64
42
66.7
Botswana
float64
18.9
22.7
Burkina Faso
float64
48.6
71.9
Burundi
float64
28.3
31.2
Cabo Verde
float64
24.9
53.9
Cameroon
float64
37
51.9
Central African Republic
float64
31.9
38.6
Chad
float64
46.8
64.4
Comoros
float64
10.4
12.3
Congo, Dem. Rep.
float64
24.6
28.5
Congo, Rep.
float64
24.2
30.6
Cote d'Ivoire
float64
38.9
62
Djibouti
float64
35.2
49.9
Egypt, Arab Rep.
float64
54.9
76.5
Equatorial Guinea
float64
29.6
38.5
Eritrea
float64
32.4
43.6
Eswatini
float64
18.8
24.3
Ethiopia
float64
22.7
32.6
Gabon
float64
26.3
30.7
Gambia, The
float64
47.6
66.4
Ghana
float64
44
68
Guinea
float64
37.4
54.3
Guinea-Bissau
float64
41.5
57.1
Kenya
float64
16.3
25.6
Lesotho
float64
20.6
26.9
Liberia
float64
31.7
51.1
Libya
float64
32.8
50.1
Madagascar
float64
10.5
16.1
Malawi
float64
19.9
26.5
Mali
float64
51.3
74.1
Mauritania
float64
64.2
85.1
Mauritius
float64
8.74
11.3
Morocco
float64
20.5
28
Mozambique
float64
18.8
21.7
Namibia
float64
19.4
23.1
Niger
float64
71.7
107
Nigeria
float64
48.1
77.1
Rwanda
float64
30
31.9
Sao Tome and Principe
float64
19.7
27.3
Senegal
float64
50.8
72
Seychelles
float64
8.5
10.5
Sierra Leone
float64
34.4
51.8
Somalia
float64
15.8
29.2
South Africa
float64
22.5
25
South Sudan
float64
29.6
39.1
Sudan
float64
45.6
64.1
Tanzania
float64
16.2
25.6
Togo
float64
43
67.3
Tunisia
float64
21.4
27.5
Uganda
float64
28.6
36.4
Zambia
float64
22.2
26.9
Zimbabwe
float64
18
23.6
1,960
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,961
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,962
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,963
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,964
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,965
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,966
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,967
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,968
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,969
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,970
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,971
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,972
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
43.178979
22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,973
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
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24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
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22.511865
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33.462368
53.719272
16.545563
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22.251441
28.62121
23.389564
20.805737
1,974
22.35937
23.831767
56.749703
19.673677
57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
24.577635
24.222807
50.621861
37.204443
57.426748
36.072505
42.714828
24.030284
26.018151
27.247781
61.222579
60.845899
48.855697
57.075794
16.284488
26.369423
39.461578
32.815049
10.706008
21.719669
65.838408
78.562022
8.736035
20.51349
19.649249
20.065162
81.72352
65.044158
30.376417
24.264683
66.603048
8.725009
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22.511865
24.567974
33.462368
53.719272
16.545563
60.04387
22.251441
28.62121
23.389564
20.805737
1,975
22.35937
23.831767
56.749703
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57.097641
29.422711
42.971688
43.722249
32.834747
55.277604
10.554342
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50.621861
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57.426748
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26.018151
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61.222579
60.845899
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57.075794
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26.369423
39.461578
32.815049
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65.838408
78.562022
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19.649249
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81.72352
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37.204443
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78.562022
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50.621861
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65.838408
78.562022
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56.749703
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29.422711
42.971688
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50.621861
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39.461578
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65.838408
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24.308592
19.49418

Air Pollution Mean Annual Exposure Micrograms Per Cubic Meter Africa | Africa (World Bank)

Size category: n<1K - Formats: csv - Sector: climate_environment - Engineered by Electric Sheep Africa

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.

Dataset context from the existing Hugging Face card: Africa: PM2.5 air pollution, mean annual exposure (micrograms per cubic meter) Dataset summary This dataset provides values for "PM2.5 air pollution, mean annual exposure (micrograms per cubic meter)" across African countries, standardized and made ML-ready. Geographic scope: 54 African countries. Temporal coverage: 1960–2024 (annual). Units: As defined by the World Bank indicator. Source & licensing Source: World Bank – World Development Indicators (WDI)… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/air-pollution-mean-annual-exposure-micrograms-per-cubic-meter-africa.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/air-pollution-mean-annual-exposure-micrograms-per-cubic-meter-africa
Sector climate_environment
Topic tags biology, medical, climate
Modalities tabular
Formats csv
Size category n<1K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2025-08-16 16:18:42+00:00
Inventory snapshot 2026-07-16T16:00:34Z

How To Read This Dataset

  • Start from the repository files and the dataset viewer when available.
  • Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/air-pollution-mean-annual-exposure-micrograms-per-cubic-meter-africa")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • Exact schema, row counts, and source files should be inspected in the repository data files.
  • Metadata gaps from the inventory: country, upstream_publisher.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • Inspect schema and missingness before modeling.
  • Profile variables by geography, time, and subgroup columns where present.
  • Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_air_pollution_mean_annual_exposure_micrograms_per_cubic_meter_africa_2026,
  title        = {Air Pollution Mean Annual Exposure Micrograms Per Cubic Meter Africa | Africa (World Bank)},
  author       = {World Bank open data},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/air-pollution-mean-annual-exposure-micrograms-per-cubic-meter-africa},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/air-pollution-mean-annual-exposure-micrograms-per-cubic-meter-africa}}
}

License

Released under gpl.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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