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country_name
stringclasses
44 values
country_iso3
stringclasses
44 values
year
int64
2k
2.02k
Safely managed
float64
5.17
80
Basic
float64
12.1
60.9
Limited
float64
0
31.8
Unimproved
float64
0
53.8
No access (surface water only)
float64
0
37.5
Algeria
DZA
2,000
69.49311
19.500694
5.466502
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Algeria
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2,002
70.47035
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Algeria
DZA
2,003
70.93791
18.577198
5.382409
2.448877
2.653606
Algeria
DZA
2,004
71.39134
18.29288
5.354475
2.361297
2.600007
Algeria
DZA
2,005
71.830215
18.020557
5.326697
2.27512
2.54741
Algeria
DZA
2,006
72.255196
17.759823
5.298989
2.190275
2.495715
Algeria
DZA
2,007
72.66588
17.510868
5.271442
2.10681
2.445004
Algeria
DZA
2,008
73.06289
17.273312
5.24397
2.024652
2.395179
Algeria
DZA
2,009
73.44309
17.048773
5.217203
1.944097
2.346838
Algeria
DZA
2,010
73.80806
16.836283
5.190924
1.864993
2.299742
Algeria
DZA
2,011
74.157486
16.63587
5.165272
1.787377
2.253999
Algeria
DZA
2,012
74.492
16.462713
5.124573
1.711175
2.209546
Algeria
DZA
2,013
74.81179
16.30107
5.084373
1.636367
2.166403
Algeria
DZA
2,014
75.11766
16.150404
5.044591
1.562883
2.124465
Algeria
DZA
2,015
75.409615
16.010536
5.005333
1.490722
2.083794
Algeria
DZA
2,016
74.78149
16.787912
4.966517
1.419796
2.044287
Algeria
DZA
2,017
74.068275
17.647364
4.928246
1.350113
2.006004
Algeria
DZA
2,018
73.326546
18.532576
4.890441
1.281595
1.968844
Algeria
DZA
2,019
72.218796
19.781008
4.853158
1.214215
1.932825
Algeria
DZA
2,020
70.52516
21.61266
4.816361
1.147925
1.897889
Algeria
DZA
2,021
68.83924
23.43399
4.780063
1.08269
1.864015
Algeria
DZA
2,022
68.90451
23.419163
4.75592
1.075955
1.844452
Algeria
DZA
2,023
68.967865
23.404772
4.732486
1.06941
1.825464
Algeria
DZA
2,024
69.02918
23.390846
4.709808
1.063076
1.807088
Angola
AGO
2,000
null
null
17.506655
13.604651
31.046457
Angola
AGO
2,001
null
null
17.687513
13.462249
30.511421
Angola
AGO
2,002
null
null
17.868372
13.319846
29.976389
Angola
AGO
2,003
null
null
17.673738
13.290092
28.639654
Angola
AGO
2,004
null
null
17.44198
13.254322
27.32646
Angola
AGO
2,005
null
null
17.172518
13.213433
26.039705
Angola
AGO
2,006
null
null
16.82217
13.219726
24.944105
Angola
AGO
2,007
null
null
16.4441
13.222496
23.86475
Angola
AGO
2,008
null
null
16.038727
13.221515
22.80074
Angola
AGO
2,009
null
null
15.605931
13.217344
21.753548
Angola
AGO
2,010
null
null
15.146217
13.209616
20.721884
Angola
AGO
2,011
null
null
14.659748
13.198483
19.706028
Angola
AGO
2,012
null
null
14.146717
13.184136
18.706211
Angola
AGO
2,013
null
null
13.607363
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17.722645
Angola
AGO
2,014
null
null
13.042014
13.146258
16.754816
Angola
AGO
2,015
null
null
12.450808
13.124043
15.805518
Angola
AGO
2,016
null
null
11.834292
13.099932
14.873714
Angola
AGO
2,017
null
null
11.192957
13.074163
13.959368
Angola
AGO
2,018
null
null
10.527334
13.047174
13.062701
Angola
AGO
2,019
null
null
10.639081
13.01859
12.182419
Angola
AGO
2,020
null
null
10.747963
12.988997
11.31901
Angola
AGO
2,021
null
null
10.854042
12.958191
10.471509
Angola
AGO
2,022
null
null
10.957437
12.926436
9.6398
Angola
AGO
2,023
null
null
11.058246
12.893849
8.823479
Angola
AGO
2,024
null
null
11.156571
12.86054
8.022146
Benin
BEN
2,000
14.208856
46.844574
7.690267
20.237602
11.018702
Benin
BEN
2,001
14.312766
47.098278
7.688483
20.246237
10.654236
Benin
BEN
2,002
14.431884
47.350803
7.682202
20.250063
10.285048
Benin
BEN
2,003
14.576163
47.601604
7.66885
20.245745
9.907638
Benin
BEN
2,004
14.720905
47.84857
7.655481
20.24246
9.532583
Benin
BEN
2,005
14.865664
48.091637
7.642242
20.240381
9.160078
Benin
BEN
2,006
15.010659
48.33076
7.629099
20.239433
8.790049
Benin
BEN
2,007
15.156113
48.56589
7.61602
20.239548
8.42243
Benin
BEN
2,008
15.3018
48.796974
7.603091
20.240812
8.057323
Benin
BEN
2,009
15.44728
49.024
7.590451
20.243376
7.694893
Benin
BEN
2,010
15.592993
49.246902
7.578012
20.247099
7.334995
Benin
BEN
2,011
15.738938
49.46563
7.565799
20.251987
6.977645
Benin
BEN
2,012
15.885113
49.680134
7.553843
20.258049
6.62286
Benin
BEN
2,013
16.031076
49.890438
7.542271
20.265432
6.270783
Benin
BEN
2,014
16.17837
50.09623
7.53075
20.273666
5.920984
Benin
BEN
2,015
16.326546
50.29748
7.519424
20.282911
5.573638
Benin
BEN
2,016
16.475605
50.4941
7.508331
20.293182
5.228782
Benin
BEN
2,017
16.625542
50.68599
7.497507
20.304506
4.886457
Benin
BEN
2,018
16.776356
50.873055
7.486991
20.316896
4.546701
Benin
BEN
2,019
16.928041
51.05521
7.476824
20.330372
4.209553
Benin
BEN
2,020
17.080595
51.232357
7.467042
20.344954
3.875054
Benin
BEN
2,021
17.233578
51.404545
7.457774
20.360773
3.543328
Benin
BEN
2,022
17.387426
51.571556
7.448968
20.377733
3.214318
Benin
BEN
2,023
17.541918
51.733376
7.440704
20.395905
2.8881
Benin
BEN
2,024
17.696833
51.890007
7.433061
20.415358
2.564742
Botswana
BWA
2,000
59.196995
16.262573
20.62517
0.868597
3.046666
Botswana
BWA
2,001
59.602856
16.152092
20.357685
0.99167
2.895697
Botswana
BWA
2,002
59.82907
16.084833
20.198135
1.120279
2.76768
Botswana
BWA
2,003
60.028244
16.02374
20.054205
1.24926
2.64455
Botswana
BWA
2,004
60.226437
15.962446
19.910057
1.37769
2.52337
Botswana
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2,005
60.422066
15.901342
19.766666
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Botswana
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2,006
61.690678
15.688697
18.700453
1.633015
2.287158
Botswana
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2,007
63.508972
15.308667
17.325354
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Botswana
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2,008
65.30496
14.903392
15.99233
1.836705
1.962609
Botswana
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2,009
67.07313
14.47508
14.704028
1.936487
1.81128
Botswana
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2,010
68.81618
14.02352
13.458376
2.034899
1.667031
Botswana
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2,011
70.53226
13.549985
12.255775
2.132082
1.529902
Botswana
BWA
2,012
70.44698
14.672835
11.219528
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Botswana
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2,013
69.875435
16.228096
10.228397
2.352603
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Botswana
BWA
2,014
69.30036
17.761646
9.259588
2.462855
1.215548
Botswana
BWA
2,015
68.72162
19.273657
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Botswana
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Botswana
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2,019
66.36296
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Botswana
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2,020
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Botswana
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Botswana
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End of preview. Expand in Data Studio

Access Drinking Water Stacked | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)

Size category: 1K<n<10K - Formats: parquet - Sector: other_unclassified - 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: Access Drinking Water Stacked | Africa (Our World in Data) 🌍 1,313 observations · 54 Africa countries · 2000–2024 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 1,313 observations of Access Drinking Water Stacked data across 54 Africa countries, spanning 2000–2024. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Access Drinking Water Stacked Geographic coverage… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-access-drinking-water-stacked.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-owid-access-drinking-water-stacked
Sector other_unclassified
Topic tags tabular, our-world-in-data, access-drinking-water-stacked, owid, long-run-series, time-series
Modalities tabular, text
Formats parquet
Size category 1K<n<10K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2026-06-01 18:32:18+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/africa-owid-access-drinking-water-stacked")
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, sector, 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_africa_owid_access_drinking_water_stacked_2026,
  title        = {Access Drinking Water Stacked | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-owid-access-drinking-water-stacked},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-access-drinking-water-stacked}}
}

License

Released under CC BY 4.0.

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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