Dataset Viewer
Auto-converted to Parquet Duplicate
country_name
stringclasses
44 values
country_iso3
stringclasses
44 values
year
int64
2k
2.02k
Solar
float64
0
2.59
Algeria
DZA
2,010
0.025
Algeria
DZA
2,011
0.025
Algeria
DZA
2,012
0.025
Algeria
DZA
2,013
0.025
Algeria
DZA
2,014
0.0283
Algeria
DZA
2,015
0.06174
Algeria
DZA
2,016
0.26174
Algeria
DZA
2,017
0.35474
Algeria
DZA
2,018
0.36674
Algeria
DZA
2,019
0.36674
Algeria
DZA
2,020
0.36674
Algeria
DZA
2,021
0.36674
Algeria
DZA
2,022
0.4508
Algeria
DZA
2,023
0.4618
Algeria
DZA
2,024
0.4618
Angola
AGO
2,013
0.000021
Angola
AGO
2,014
0.00032
Angola
AGO
2,015
0.00032
Angola
AGO
2,016
0.000328
Angola
AGO
2,017
0.000424
Angola
AGO
2,018
0.000437
Angola
AGO
2,019
0.001366
Angola
AGO
2,020
0.001374
Angola
AGO
2,021
0.001441
Angola
AGO
2,022
0.28546
Angola
AGO
2,023
0.31046
Angola
AGO
2,024
0.36189
Benin
BEN
2,014
0.00025
Benin
BEN
2,015
0.001436
Benin
BEN
2,016
0.002195
Benin
BEN
2,017
0.002436
Benin
BEN
2,018
0.002585
Benin
BEN
2,019
0.003806
Benin
BEN
2,020
0.004847
Benin
BEN
2,021
0.006016
Benin
BEN
2,022
0.033382
Benin
BEN
2,023
0.035258
Benin
BEN
2,024
0.035258
Botswana
BWA
2,009
0.00002
Botswana
BWA
2,010
0.000139
Botswana
BWA
2,011
0.000169
Botswana
BWA
2,012
0.001615
Botswana
BWA
2,013
0.001715
Botswana
BWA
2,014
0.00186
Botswana
BWA
2,015
0.002153
Botswana
BWA
2,016
0.00328
Botswana
BWA
2,017
0.003415
Botswana
BWA
2,018
0.00372
Botswana
BWA
2,019
0.005919
Botswana
BWA
2,020
0.005918
Botswana
BWA
2,021
0.006301
Botswana
BWA
2,022
0.006289
Botswana
BWA
2,023
0.0103
Botswana
BWA
2,024
0.0103
Burkina Faso
BFA
2,004
0.00011
Burkina Faso
BFA
2,005
0.00011
Burkina Faso
BFA
2,006
0.00011
Burkina Faso
BFA
2,007
0.00011
Burkina Faso
BFA
2,008
0.00011
Burkina Faso
BFA
2,009
0.000112
Burkina Faso
BFA
2,010
0.000209
Burkina Faso
BFA
2,011
0.000267
Burkina Faso
BFA
2,012
0.000833
Burkina Faso
BFA
2,013
0.001341
Burkina Faso
BFA
2,014
0.001824
Burkina Faso
BFA
2,015
0.00275
Burkina Faso
BFA
2,016
0.003165
Burkina Faso
BFA
2,017
0.038252
Burkina Faso
BFA
2,018
0.053695
Burkina Faso
BFA
2,019
0.058027
Burkina Faso
BFA
2,020
0.058517
Burkina Faso
BFA
2,021
0.059302
Burkina Faso
BFA
2,022
0.089897
Burkina Faso
BFA
2,023
0.177042
Burkina Faso
BFA
2,024
0.205642
Burundi
BDI
2,012
0.000403
Burundi
BDI
2,013
0.000413
Burundi
BDI
2,014
0.000426
Burundi
BDI
2,015
0.000723
Burundi
BDI
2,016
0.00152
Burundi
BDI
2,017
0.001868
Burundi
BDI
2,018
0.00188
Burundi
BDI
2,019
0.00192
Burundi
BDI
2,020
0.00206
Burundi
BDI
2,021
0.009018
Burundi
BDI
2,022
0.008863
Burundi
BDI
2,023
0.009528
Burundi
BDI
2,024
0.009528
Cameroon
CMR
2,003
0.0001
Cameroon
CMR
2,004
0.0001
Cameroon
CMR
2,005
0.0001
Cameroon
CMR
2,006
0.0001
Cameroon
CMR
2,007
0.0002
Cameroon
CMR
2,008
0.0002
Cameroon
CMR
2,009
0.00001
Cameroon
CMR
2,010
0.00001
Cameroon
CMR
2,011
0.00004
Cameroon
CMR
2,012
0.000053
Cameroon
CMR
2,013
0.000062
Cameroon
CMR
2,014
0.000067
End of preview. Expand in Data Studio

Installed Solar Pv Capacity | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)

Size category: n<1K - Formats: parquet - Sector: energy - 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: Installed Solar Pv Capacity | Africa (Our World in Data) 🌍 874 observations · 54 Africa countries · 2000–2024 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 874 observations of Installed Solar Pv Capacity 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: Installed Solar Pv Capacity Geographic coverage 54… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-installed-solar-pv-capacity.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-owid-installed-solar-pv-capacity
Sector energy
Topic tags tabular, our-world-in-data, installed-solar-pv-capacity, owid, long-run-series, time-series
Modalities tabular, text
Formats parquet
Size category n<1K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2026-06-08 14:12:31+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-installed-solar-pv-capacity")
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_africa_owid_installed_solar_pv_capacity_2026,
  title        = {Installed Solar Pv Capacity | 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-installed-solar-pv-capacity},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-installed-solar-pv-capacity}}
}

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