electricsheepafrica/africa-nigeria-transport-fare-watch-da443013

Transport Fare Watch | Africa (Nigeria official open data)

146 rows - 1 Africa country - 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: Transport Fare Watch
• Publisher: National Bureau of Statistics, Nigeria
• Resource: Transport Fare Watch Report Nov-Dec 2025
• Format: ZIP
• License: Other open license
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
NGA	146	2025	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-161-1344:transport-cost-watch-nov-2025-xl: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.	TRANSPORT COST Watch NOV_2025_.xlsx::Transport November 2025
year	Int64	Observation year.	2025
zone	string	Source column.	Air fare charg.for specified routes single journey
average_of_nov_24	float64	Source column.	126146.31378378376
average_of_oct_25	float64	Source column.	131557.53303485893
average_of_nov_25	float64	Source column.	133415.03043487915
mom	float64	Source column.	1.411927813763456
yoy	float64	Source column.	5.762131633552168
source_period_start_year	Int64	First year inferred from source resource metadata.	2025
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.	2025
source_provider	string	Publishing organization.	National Bureau of Statistics, Nigeria
source_dataset	string	Source package title.	Transport Fare Watch
source_resource	string	Source resource title.	Transport Fare Watch Report Nov-Dec 2025
source_package_id	string	CKAN package UUID.	NGA-NBS-TRANSFW
source_resource_id	string	CKAN resource UUID.	nbs-nada-161-1344
source_url	string	Original source resource URL.	https://microdata.nigerianstat.gov.ng/index.php/catalog/161/download/134
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC retrieval timestamp.	2026-07-19T10:27:56Z
state	string	Source column.	``
air_fare_charg_for_specified_routes_single_journey	float64	Source column.	``
bus_journey_intercity_state_route_charg_per_per	float64	Source column.	``
bus_journey_within_city_per_drop_constant_rou	float64	Source column.	``
journey_by_motorcycle_okada_per_drop	float64	Source column.	``
water_transport_water_way_passenger_transportat	float64	Source column.	``
average_of_dec_24	float64	Source column.	``
average_of_dec_25	float64	Source column.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-transport-fare-watch-da443013")
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_transport_fare_watch_da443013_2025,
  title        = {Transport Fare Watch | Africa (Nigeria official open data)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/161/related-materials},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-transport-fare-watch-da443013}}
}

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/161/download/1344