Dataset Viewer
Auto-converted to Parquet Duplicate
terminal_id
string
name
string
location
string
capacity_mmbbl
float64
throughput_bpd
int64
TERM-01
Terminal_1
Bonny
2.745573
311,920
TERM-02
Terminal_2
Brass
2.67638
489,273
TERM-03
Terminal_3
Qua Iboe
3.319276
415,317
TERM-04
Terminal_4
Forcados
4.854238
480,637
TERM-05
Terminal_5
Forcados
1.768199
317,802
TERM-06
Terminal_6
Forcados
3.971635
275,765
TERM-07
Terminal_7
Bonny
3.958444
177,478
TERM-08
Terminal_8
Bonny
3.925688
410,320
TERM-09
Terminal_9
Brass
3.287489
106,283
TERM-10
Terminal_10
Bonny
3.992311
208,991
TERM-11
Terminal_11
Brass
3.862238
321,544
TERM-12
Terminal_12
Brass
3.928248
473,377
TERM-13
Terminal_13
Brass
4.418129
304,621
TERM-14
Terminal_14
Bonny
3.437799
426,027
TERM-15
Terminal_15
Forcados
1.995326
467,915
TERM-16
Terminal_16
Brass
3.052774
136,809
TERM-17
Terminal_17
Forcados
2.788963
143,289
TERM-18
Terminal_18
Brass
3.441549
437,378
TERM-19
Terminal_19
Qua Iboe
1.425081
313,983
TERM-20
Terminal_20
Qua Iboe
3.810765
369,010

Africa Synth Energy Oilgas Terminals Nigeria | Africa (Electric Sheep Africa metadata inventory)

Size category: n<1K - Formats: csv - 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: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Nigerian Oilgas Terminals Dataset Description This dataset is part of the Nigerian Oil & Gas Sector collection, containing comprehensive data on Nigeria's petroleum industry from 1999-2025. Rows: 20 Columns: 5 Period: 1999-2025 (where applicable) License: MIT Data Quality 1999-2014: ⭐⭐⭐⭐⭐ Based on official… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-terminals-nigeria.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-synth-energy-oilgas-terminals-nigeria
Sector energy
Topic tags nigeria, oil-and-gas, energy, petroleum, synthetic
Modalities tabular, text
Formats csv
Size category n<1K
Countries Nigeria
ISO3 coverage NGA
Last modified on HF 2026-04-14 22:33:13+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-synth-energy-oilgas-terminals-nigeria")
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: 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_synth_energy_oilgas_terminals_nigeria_2026,
  title        = {Africa Synth Energy Oilgas Terminals Nigeria | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-terminals-nigeria},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-terminals-nigeria}}
}

License

Released under mit.

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
33

Collections including electricsheepafrica/africa-synth-energy-oilgas-terminals-nigeria