Dataset Viewer
Auto-converted to Parquet Duplicate
country_name
stringclasses
40 values
country_iso3
stringclasses
40 values
year
int64
1.99k
2.02k
Adjusted net savings, excluding particulate emission damage (current US$)
float64
-13,471,653,000
87.1B
Algeria
DZA
1,990
5,691,609,000
Algeria
DZA
1,991
8,140,226,000
Algeria
DZA
2,005
26,801,908,000
Algeria
DZA
2,006
32,760,844,000
Algeria
DZA
2,007
42,865,940,000
Algeria
DZA
2,008
55,543,476,000
Algeria
DZA
2,009
36,996,977,000
Algeria
DZA
2,010
48,381,178,000
Algeria
DZA
2,011
54,923,650,000
Algeria
DZA
2,012
59,655,655,000
Algeria
DZA
2,013
56,373,756,000
Algeria
DZA
2,014
51,428,210,000
Algeria
DZA
2,015
33,513,286,000
Algeria
DZA
2,016
35,897,127,000
Algeria
DZA
2,017
37,266,866,000
Algeria
DZA
2,018
35,706,480,000
Algeria
DZA
2,019
31,681,497,000
Algeria
DZA
2,020
20,289,407,000
Algeria
DZA
2,021
25,155,170,000
Angola
AGO
2,000
-685,403,260
Angola
AGO
2,001
-1,916,782,600
Angola
AGO
2,002
422,076,200
Angola
AGO
2,003
489,105,400
Angola
AGO
2,004
1,515,206,100
Angola
AGO
2,005
2,445,465,000
Angola
AGO
2,006
4,888,243,000
Angola
AGO
2,007
1,312,854,100
Angola
AGO
2,008
-6,090,181,600
Angola
AGO
2,009
-597,694,700
Angola
AGO
2,010
2,047,753,100
Angola
AGO
2,011
4,013,516,500
Angola
AGO
2,012
7,172,716,000
Angola
AGO
2,013
5,828,168,000
Angola
AGO
2,014
10,397,618,000
Angola
AGO
2,015
7,475,655,700
Angola
AGO
2,016
517,856,540
Angola
AGO
2,017
-2,065,262,000
Angola
AGO
2,018
-3,482,920,700
Angola
AGO
2,019
3,413,329,400
Angola
AGO
2,020
4,772,126,700
Angola
AGO
2,021
8,716,611,000
Benin
BEN
1,990
-66,848,330
Benin
BEN
1,991
-50,472,336
Benin
BEN
1,992
-120,225,380
Benin
BEN
1,993
-116,404,060
Benin
BEN
1,994
-106,069,620
Benin
BEN
1,995
-148,341,180
Benin
BEN
1,996
-191,794,560
Benin
BEN
1,997
-153,081,070
Benin
BEN
1,998
-165,361,760
Benin
BEN
1,999
-190,407,120
Benin
BEN
2,000
-142,787,230
Benin
BEN
2,001
-55,808,660
Benin
BEN
2,002
28,488,446
Benin
BEN
2,003
-26,776,260
Benin
BEN
2,004
137,548,800
Benin
BEN
2,005
114,767,260
Benin
BEN
2,006
127,950,020
Benin
BEN
2,007
281,527,140
Benin
BEN
2,008
248,192,000
Benin
BEN
2,009
101,868,590
Benin
BEN
2,010
108,925,130
Benin
BEN
2,011
269,575,260
Benin
BEN
2,012
580,329,200
Benin
BEN
2,013
1,148,120,000
Benin
BEN
2,014
1,539,909,900
Benin
BEN
2,015
633,652,860
Benin
BEN
2,016
1,043,814,700
Benin
BEN
2,017
1,051,287,400
Benin
BEN
2,018
1,486,213,400
Benin
BEN
2,019
1,757,582,700
Benin
BEN
2,020
1,806,896,000
Botswana
BWA
1,990
1,213,084,400
Botswana
BWA
1,991
1,387,131,500
Botswana
BWA
1,992
1,285,572,700
Botswana
BWA
1,993
1,418,857,200
Botswana
BWA
1,994
806,759,230
Botswana
BWA
1,995
843,663,000
Botswana
BWA
1,996
1,294,379,500
Botswana
BWA
1,997
1,428,065,400
Botswana
BWA
1,998
1,542,151,200
Botswana
BWA
1,999
1,762,903,700
Botswana
BWA
2,000
1,845,264,800
Botswana
BWA
2,001
2,086,366,500
Botswana
BWA
2,002
1,335,471,000
Botswana
BWA
2,003
1,600,507,800
Botswana
BWA
2,004
1,749,808,500
Botswana
BWA
2,005
2,908,745,000
Botswana
BWA
2,006
2,628,814,600
Botswana
BWA
2,007
2,973,439,700
Botswana
BWA
2,008
2,420,877,300
Botswana
BWA
2,009
1,345,802,000
Botswana
BWA
2,010
2,435,650,300
Botswana
BWA
2,011
4,192,167,400
Botswana
BWA
2,012
3,569,333,200
Botswana
BWA
2,013
3,187,005,700
Botswana
BWA
2,014
3,959,097,600
Botswana
BWA
2,015
2,646,247,700
Botswana
BWA
2,016
2,463,988,200
Botswana
BWA
2,017
2,795,188,000
End of preview. Expand in Data Studio

Adjusted Net Saving Current Us Dollars | 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: Adjusted Net Saving Current Us Dollars | Africa (Our World in Data) 🌍 1,150 observations · 49 Africa countries · 1990–2021 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 1,150 observations of Adjusted Net Saving Current Us Dollars data across 49 Africa countries, spanning 1990–2021. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Adjusted Net Saving Current Us Dollars… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-adjusted-net-saving-current-us-dollars.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-owid-adjusted-net-saving-current-us-dollars
Sector other_unclassified
Topic tags tabular, our-world-in-data, adjusted-net-saving-current-us-dollars, 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 18:34:52+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-adjusted-net-saving-current-us-dollars")
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_adjusted_net_saving_current_us_dollars_2026,
  title        = {Adjusted Net Saving Current Us Dollars | 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-adjusted-net-saving-current-us-dollars},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-adjusted-net-saving-current-us-dollars}}
}

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.

Downloads last month
19