Dataset Viewer
Auto-converted to Parquet Duplicate
facility_id
stringlengths
7
7
type
stringclasses
3 values
operator
stringclasses
3 values
capacity_mmscfd
int64
110
993
GAS-001
pipeline
NNPC
981
GAS-002
pipeline
Shell
215
GAS-003
pipeline
NNPC
713
GAS-004
distribution
Chevron
277
GAS-005
processing
Chevron
311
GAS-006
pipeline
NNPC
643
GAS-007
distribution
NNPC
530
GAS-008
distribution
Chevron
691
GAS-009
distribution
Shell
188
GAS-010
distribution
NNPC
235
GAS-011
pipeline
Shell
212
GAS-012
distribution
NNPC
993
GAS-013
pipeline
Shell
273
GAS-014
processing
NNPC
442
GAS-015
processing
NNPC
203
GAS-016
pipeline
NNPC
351
GAS-017
distribution
Shell
389
GAS-018
pipeline
NNPC
666
GAS-019
pipeline
Chevron
316
GAS-020
distribution
NNPC
981
GAS-021
processing
Chevron
523
GAS-022
distribution
NNPC
606
GAS-023
distribution
Shell
854
GAS-024
pipeline
Shell
800
GAS-025
distribution
Shell
254
GAS-026
processing
Shell
901
GAS-027
pipeline
Chevron
963
GAS-028
processing
Chevron
365
GAS-029
processing
NNPC
959
GAS-030
pipeline
Shell
611
GAS-031
processing
NNPC
925
GAS-032
processing
Shell
884
GAS-033
distribution
Chevron
860
GAS-034
processing
Shell
509
GAS-035
pipeline
Shell
236
GAS-036
processing
NNPC
718
GAS-037
distribution
Shell
265
GAS-038
distribution
Shell
529
GAS-039
processing
Chevron
430
GAS-040
distribution
Chevron
965
GAS-041
processing
Chevron
337
GAS-042
pipeline
NNPC
250
GAS-043
processing
Shell
944
GAS-044
pipeline
Chevron
896
GAS-045
pipeline
NNPC
713
GAS-046
distribution
Shell
685
GAS-047
processing
NNPC
888
GAS-048
distribution
NNPC
192
GAS-049
distribution
Shell
720
GAS-050
processing
NNPC
213
GAS-051
processing
Shell
224
GAS-052
processing
Shell
752
GAS-053
processing
Chevron
573
GAS-054
processing
Shell
373
GAS-055
pipeline
Shell
216
GAS-056
pipeline
Chevron
635
GAS-057
processing
Chevron
927
GAS-058
processing
NNPC
944
GAS-059
processing
Shell
737
GAS-060
processing
Shell
705
GAS-061
distribution
NNPC
903
GAS-062
processing
NNPC
119
GAS-063
distribution
Chevron
862
GAS-064
distribution
Chevron
838
GAS-065
processing
Chevron
656
GAS-066
processing
Chevron
603
GAS-067
distribution
Chevron
891
GAS-068
distribution
Shell
206
GAS-069
processing
Shell
712
GAS-070
pipeline
NNPC
306
GAS-071
distribution
Shell
531
GAS-072
pipeline
NNPC
426
GAS-073
pipeline
NNPC
527
GAS-074
pipeline
Chevron
206
GAS-075
pipeline
Chevron
910
GAS-076
processing
NNPC
674
GAS-077
processing
Chevron
728
GAS-078
processing
NNPC
687
GAS-079
distribution
Shell
499
GAS-080
distribution
Shell
671
GAS-081
distribution
Shell
918
GAS-082
distribution
NNPC
181
GAS-083
distribution
Shell
752
GAS-084
pipeline
Chevron
169
GAS-085
distribution
NNPC
623
GAS-086
processing
Shell
818
GAS-087
processing
NNPC
277
GAS-088
distribution
NNPC
110
GAS-089
processing
NNPC
991
GAS-090
distribution
NNPC
305
GAS-091
distribution
NNPC
698
GAS-092
processing
Chevron
197
GAS-093
distribution
NNPC
412
GAS-094
distribution
Shell
766
GAS-095
processing
Chevron
330
GAS-096
processing
Shell
988
GAS-097
distribution
NNPC
611
GAS-098
processing
Shell
976
GAS-099
pipeline
NNPC
322
GAS-100
pipeline
Chevron
364

Africa Synth Energy Oilgas Gas Infrastructure 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 Gas Infrastructure 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: 100 Columns: 4 Period: 1999-2025 (where applicable) License: MIT Data Quality 1999-2014: ⭐⭐⭐⭐⭐ Based on… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-gas-infrastructure-nigeria.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-synth-energy-oilgas-gas-infrastructure-nigeria
Sector energy
Topic tags nigeria, oil-and-gas, energy, petroleum, synthetic
Modalities text
Formats csv
Size category n<1K
Countries Nigeria
ISO3 coverage NGA
Last modified on HF 2026-04-14 22:31:50+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-gas-infrastructure-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_gas_infrastructure_nigeria_2026,
  title        = {Africa Synth Energy Oilgas Gas Infrastructure Nigeria | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-gas-infrastructure-nigeria},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-energy-oilgas-gas-infrastructure-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
386

Collections including electricsheepafrica/africa-synth-energy-oilgas-gas-infrastructure-nigeria