Dataset Viewer
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Year
stringdate
1960-01-01 00:00:00
2024-01-01 00:00:00
adjusted_savings_net_forest_depletion_of_gni_
float64
0
44.9
carbon_dioxide_co2_emissions_excluding_lulucf_per_capita_t_co2e_capita_
float64
0.02
19
forest_area_of_land_area_
float64
0.04
96.2
terrestrial_and_marine_protected_areas_of_total_territorial_area_
float64
0
59.7
1960-01-01
0
1.42854
0.699908
7.1
1961-01-01
0
1.42854
0.699908
7.1
1962-01-01
0
1.42854
0.699908
7.1
1963-01-01
0
1.42854
0.699908
7.1
1964-01-01
0
1.42854
0.699908
7.1
1965-01-01
0
1.42854
0.699908
7.1
1966-01-01
0
1.42854
0.699908
7.1
1967-01-01
0
1.42854
0.699908
7.1
1968-01-01
0
1.42854
0.699908
7.1
1969-01-01
0
1.42854
0.699908
7.1
1970-01-01
0
1.42854
0.699908
7.1
1971-01-01
0
1.632116
0.699908
7.1
1972-01-01
0
2.436468
0.699908
7.1
1973-01-01
0
3.202128
0.699908
7.1
1974-01-01
0
2.636561
0.699908
7.1
1975-01-01
0
2.322108
0.699908
7.1
1976-01-01
0
2.868768
0.699908
7.1
1977-01-01
0
3.064734
0.699908
7.1
1978-01-01
0
3.276072
0.699908
7.1
1979-01-01
0
3.183706
0.699908
7.1
1980-01-01
0
3.074277
0.699908
7.1
1981-01-01
0
2.809548
0.699908
7.1
1982-01-01
0
2.861418
0.699908
7.1
1983-01-01
0
2.879301
0.699908
7.1
1984-01-01
0
2.931487
0.699908
7.1
1985-01-01
0
3.257108
0.699908
7.1
1986-01-01
0
3.295105
0.699908
7.1
1987-01-01
0
3.081017
0.699908
7.1
1988-01-01
0
3.025326
0.699908
7.1
1989-01-01
0
2.956793
0.699908
7.1
1990-01-01
0
2.843625
0.699908
7.1
1991-01-01
0
2.893336
0.696214
7.1
1992-01-01
0
3.183844
0.692519
7.1
1993-01-01
0
3.04185
0.688824
7.1
1994-01-01
0
2.910015
0.685129
7.1
1995-01-01
0
2.944016
0.681435
7.1
1996-01-01
0
2.807353
0.67774
7.1
1997-01-01
0
2.691774
0.674045
7.1
1998-01-01
0
2.70974
0.67035
7.1
1999-01-01
0
2.787675
0.666655
7.1
2000-01-01
0
2.845473
0.662961
7.1
2001-01-01
0
2.73913
0.677194
7.1
2002-01-01
0
2.824622
0.691427
7.1
2003-01-01
0
2.999221
0.705661
7.1
2004-01-01
0
2.961289
0.719894
7.1
2005-01-01
0
3.062498
0.734127
7.1
2006-01-01
0
3.137716
0.74836
7.1
2007-01-01
0
3.18555
0.762594
7.1
2008-01-01
0
3.265719
0.776827
7.1
2009-01-01
0
3.270894
0.79106
7.1
2010-01-01
0
3.277714
0.805294
7.1
2011-01-01
0
3.381669
0.808485
7.1
2012-01-01
0
3.725742
0.811675
7.1
2013-01-01
0
3.792954
0.814866
7.1
2014-01-01
0
3.95385
0.818057
7.1
2015-01-01
0
4.119541
0.821248
7.1
2016-01-01
0
3.940941
0.821248
7.1055
2017-01-01
0
3.995064
0.81579
7.1
2018-01-01
0
4.113294
0.810332
7.105493
2019-01-01
0
4.195662
0.81411
7.1
2020-01-01
0
3.902928
0.818309
4.4
2021-01-01
0
4.015587
0.822228
4.4
2022-01-01
0
4.104114
0.826333
4.4
2023-01-01
0
3.90687
0.826333
4.4
2024-01-01
0
3.90687
0.826333
4.4
1960-01-01
0.776319
1.526435
63.57807
8.9
1961-01-01
0.776319
1.526435
63.57807
8.9
1962-01-01
0.776319
1.526435
63.57807
8.9
1963-01-01
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63.57807
8.9
1964-01-01
0.776319
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1965-01-01
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1966-01-01
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1967-01-01
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1968-01-01
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1969-01-01
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1970-01-01
0.776319
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1971-01-01
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8.9
1972-01-01
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1973-01-01
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8.9
1974-01-01
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8.9
1975-01-01
0.776319
1.593568
63.57807
8.9
1976-01-01
0.776319
1.03072
63.57807
8.9
1977-01-01
0.776319
1.644408
63.57807
8.9
1978-01-01
0.776319
1.87631
63.57807
8.9
1979-01-01
0.776319
1.806936
63.57807
8.9
1980-01-01
0.776319
1.76006
63.57807
8.9
1981-01-01
0.776319
1.568625
63.57807
8.9
1982-01-01
0.776319
1.459325
63.57807
8.9
1983-01-01
0.776319
1.455612
63.57807
8.9
1984-01-01
0.776319
1.417008
63.57807
8.9
1985-01-01
0.776319
1.442226
63.57807
8.9
1986-01-01
1.094998
1.405027
63.57807
8.9
1987-01-01
1.101381
1.381387
63.57807
8.9
1988-01-01
1.148404
1.375601
63.57807
8.9
1989-01-01
0.825543
1.3439
63.57807
8.9
1990-01-01
1.116986
0.965969
63.57807
8.9
1991-01-01
1.013395
0.979787
63.453407
8.9
1992-01-01
3.237476
0.975473
63.328745
8.9
1993-01-01
3.53352
0.946556
63.204082
8.9
1994-01-01
6.485313
0.867215
63.079419
8.9
End of preview. Expand in Data Studio

Environment and Natural Resources Indicators For African Countries | Africa (World Health Organization)

Size category: 1K<n<10K - 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: Master Datacard for Environment and Natural Resources Indicators for African Countries This repository contains time-series datasets for key environment and natural resources indicators for 54 African countries. The data is sourced from The World Bank and has been cleaned, processed, and organized for analysis. Each country has its own set of files, including a main CSV dataset and a corresponding datacard in Markdown format. The data covers the period from 1960 to 2024, where… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Environment-and-Natural-Resources-Indicators-For-African-Countries.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/Environment-and-Natural-Resources-Indicators-For-African-Countries
Sector climate_environment
Topic tags climate_environment
Modalities tabular, text
Formats csv
Size category 1K<n<10K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2025-06-21 09:49:35+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/Environment-and-Natural-Resources-Indicators-For-African-Countries")
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, license, language.
  • 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_environment_and_natural_resources_indicators_for_african_countries_2026,
  title        = {Environment and Natural Resources Indicators For African Countries | Africa (World Health Organization)},
  author       = {WHO public data},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/Environment-and-Natural-Resources-Indicators-For-African-Countries},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/Environment-and-Natural-Resources-Indicators-For-African-Countries}}
}

License

Released under Source-specific or other license.

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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