electricsheepafrica/africa-nigeria-rail-transportation-data-833d5dce

Rail Transportation Data | Africa (Nigeria official open data)

34 rows - 1 Africa country - 2024-2025 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official ZIP resource from Nigeria as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• Source: Rail Transportation Data
• Publisher: National Bureau of Statistics, Nigeria
• Resource: Rail Transport Q4 2024-Q1 2025
• Format: ZIP
• License: Other open license
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
NGA	34	2024	2025	Nigeria

Indicators or Resource Contents

• This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier for tabular resources.	nbs-nada-150-1321:rail-transport-data-q4-2024-xlsx:0
country_iso3	string	ISO3 country code.	NGA
country_name	string	Country name.	Nigeria
source_sheet	string	Workbook sheet name, when the source is a spreadsheet.	Rail_Transport_Data_Q4 2024.xlsx::Sheet2
d_1	float64	Source column.	2.0
quantity_of_passengers_number	string	Source column.	Volume of Goods/Cargos (Tons)
d_723995	float64	Source column.	54099.0
d_748345	float64	Source column.	79750.0
d_815262	float64	Source column.	55630.0
d_602509	float64	Source column.	10634.0
d_2890111	float64	Source column.	200113.0
d_647055	float64	Source column.	18484.0
d_108238_2236916601	float64	Source column.	8691.1313518221
d_130258	float64	Source column.	24528.0
d_134817_03	float64	Source column.	35736.48
d_1020368_2536916601	float64	Source column.	87439.6113518221
d_424460	float64	Source column.	9071.0
d_565385	float64	Source column.	27695.0
d_696841	float64	Source column.	51726.0
d_1027772	float64	Source column.	53946.0
d_2714458	float64	Source column.	142438.0
d_953099	float64	Source column.	39379.0
d_422393	float64	Source column.	31197.0
d_500348	float64	Source column.	33312.0
d_1337108	float64	Source column.	53136.0
d_3212948	float64	Source column.	157024.0
d_441725	float64	Source column.	59966.0
d_474117	float64	Source column.	56936.0
d_594348	float64	Source column.	69003.0
d_672198	float64	Source column.	119286.0
d_2182388	float64	Source column.	305191.0
d_675293	float64	Source column.	160650.0
d_689263	float64	Source column.	143759.0
d_743205	float64	Source column.	96401.0
d_1037113	float64	Source column.	94750.0
d_3144874	float64	Source column.	495560.0
d_39_54602027704335	float64	Source column.	-1.7126378357070986
d_54_286832153621404	float64	Source column.	-20.569052529215497
source_period_start_year	Int64	First year inferred from source resource metadata.	2024
source_period_end_year	Int64	Last year inferred from source resource metadata.	2025
source_period_label	string	Human-readable period inferred from source resource metadata.	2024-2025
source_provider	string	Publishing organization.	National Bureau of Statistics, Nigeria
source_dataset	string	Source package title.	Rail Transportation Data
source_resource	string	Source resource title.	Rail Transport Q4 2024-Q1 2025
source_package_id	string	CKAN package UUID.	NGA-NBS-RAIL
source_resource_id	string	CKAN resource UUID.	nbs-nada-150-1321
source_url	string	Original source resource URL.	https://microdata.nigerianstat.gov.ng/index.php/catalog/150/download/132
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC retrieval timestamp.	2026-07-19T10:27:56Z
d_929553	string	Source column.	``
d_10_3710974599682	float64	Source column.	``
d_37_65180447598302	float64	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-rail-transportation-data-833d5dce")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "NGA"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_nigeria_rail_transportation_data_833d5dce_2025,
  title        = {Rail Transportation Data | Africa (Nigeria official open data)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/150/related-materials},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-rail-transportation-data-833d5dce}}
}

License

Released under Other open license.

Original data (c) National Bureau of Statistics, Nigeria. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-07-19 via the Electric Sheep pipeline. Source URL: https://microdata.nigerianstat.gov.ng/index.php/catalog/150/download/1321