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electricsheepafrica/africa-nigeria-consumer-price-index-and-inflation-caed8cff

Consumer Price Index and Inflation | Africa (National Bureau of Statistics, Nigeria) 54 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 54 rows from National Bureau of Statistics, Nigeria, covering Consumer Price Index and Inflation. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-consumer-price-index-and-inflation-caed8cff.

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Dataset Card

Consumer Price Index and Inflation | Africa (National Bureau of Statistics, Nigeria)

54 rows - 1 Africa country/area - 2025 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 54 rows from National Bureau of Statistics, Nigeria, covering Consumer Price Index and Inflation. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

Source-provided context: Table [tbl]

How To Read This Dataset

  • —One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
  • —Primary geography column: country_iso3.
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows54
Countries/areas1
First period2025
Last period2025
Indicators0
Columns117
Source formatXLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
NGA5420252025Nigeria

Indicators, Variables, Or Resource Contents

  • —This repo preserves one source tabular resource with its usable columns kept together.

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.nbs-nada-154-1233:table1:0
country_iso3stringISO3 country or area code.NGA
country_namestringCountry or area name.Nigeria
source_sheetstringSource column from the original resource.Table1
yearint64Observation year.2025
2025stringSource column from the original resource.Feb
d_110_68doubleSource column from the original resource.112.93923
d_102_92820367975021doubleSource column from the original resource.104.69929325544756
d_10_680000000000007doubleSource column from the original resource.2.0412269606071334
d_24_47934910392557doubleSource column from the original resource.23.18024448416243
d_30_881495103561804doubleSource column from the original resource.30.091499739581764
d_110_7doubleSource column from the original resource.113.116378
d_102_58393350660627doubleSource column from the original resource.104.2873129300328
d_10_700000000000003doubleSource column from the original resource.2.182816621499555
d_21_92765550320803doubleSource column from the original resource.22.05597101402641
d_24_731571804364933doubleSource column from the original resource.24.489448616690492
d_110_33doubleSource column from the original resource.112.176425
d_103_1693097746528doubleSource column from the original resource.104.94841594782676
d_10_329999999999998doubleSource column from the original resource.1.6735475392005696
d_26_07587479771773doubleSource column from the original resource.23.505387828846366
d_36_09156128152901doubleSource column from the original resource.34.739677860673055
d_110_87doubleSource column from the original resource.113.661447
d_102_66453320579392doubleSource column from the original resource.104.43609800959624
d_10_870000000000005doubleSource column from the original resource.2.517765851898602
d_22_59124992827124doubleSource column from the original resource.23.006670471930704
d_25_531817585393043doubleSource column from the original resource.25.32838122940421
2025_2stringSource column from the original resource.Feb
source_period_start_yearint64Start year inferred from source metadata.2025
source_period_end_yearint64End year inferred from source metadata.2025
source_period_labelstringSource column from the original resource.2025
source_providerstringPublishing organization.National Bureau of Statistics, Nigeria
source_datasetstringSource dataset or package title.Consumer Price Index and Inflation
source_resourcestringSource resource title, table name, or file name.May 2025 CPI Tables
source_package_idstringSource package identifier.NGA-NBS-CPI
source_resource_idstringSource resource identifier.nbs-nada-154-1233
source_urlstringOriginal source URL or download URL.https://microdata.nigerianstat.gov.ng/index.php/catalog/154/download/...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-19T04:13:01Z
d_111_47doubleSource column from the original resource.``
d_110_5doubleSource column from the original resource.``
d_108_91doubleSource column from the original resource.``
d_110_41doubleSource column from the original resource.``
d_110_79doubleSource column from the original resource.``
d_110_64doubleSource column from the original resource.``
d_114_7989doubleSource column from the original resource.``
d_112_734doubleSource column from the original resource.``
d_107_6146doubleSource column from the original resource.``
d_111_482doubleSource column from the original resource.``
d_109_417doubleSource column from the original resource.``
d_112_7659doubleSource column from the original resource.``
d_107_5387doubleSource column from the original resource.``
d_106_8527doubleSource column from the original resource.``
d_104_8804doubleSource column from the original resource.``
d_114_1385doubleSource column from the original resource.``
d_104_653doubleSource column from the original resource.``
d_112_0402doubleSource column from the original resource.``
d_111_1859doubleSource column from the original resource.``
d_111_0659doubleSource column from the original resource.``
d_111_2949doubleSource column from the original resource.``
d_112_6677doubleSource column from the original resource.``
d_111_1456doubleSource column from the original resource.``
d_111_3583doubleSource column from the original resource.``
d_108_8475doubleSource column from the original resource.``
d_110_6382doubleSource column from the original resource.``
d_111_4726doubleSource column from the original resource.``
d_111_563254doubleSource column from the original resource.``
d_115_610117doubleSource column from the original resource.``
d_113_577006doubleSource column from the original resource.``
d_107_09951doubleSource column from the original resource.``
d_112_3353doubleSource column from the original resource.``
d_110_265294doubleSource column from the original resource.``
d_114_115116doubleSource column from the original resource.``
d_107_251684doubleSource column from the original resource.``
d_106_967382doubleSource column from the original resource.``
d_105_019004doubleSource column from the original resource.``
d_114_504004doubleSource column from the original resource.``
d_104_834431doubleSource column from the original resource.``
d_112_120888doubleSource column from the original resource.``
d_11_18589999999999doubleSource column from the original resource.``
d_26_087001103673373doubleSource column from the original resource.``
d_33_015163367503874doubleSource column from the original resource.``
d_109_4697doubleSource column from the original resource.``
d_109_7349doubleSource column from the original resource.``
d_109_783doubleSource column from the original resource.``
d_109_253doubleSource column from the original resource.``
d_108_6858doubleSource column from the original resource.``
d_108_8997doubleSource column from the original resource.``
d_109_107doubleSource column from the original resource.``
d_109_7192doubleSource column from the original resource.``
d_109_3588doubleSource column from the original resource.``
d_108_7702doubleSource column from the original resource.``
d_113_0705doubleSource column from the original resource.``
d_111_0863doubleSource column from the original resource.``
d_110_7025doubleSource column from the original resource.``
d_109_7418doubleSource column from the original resource.``
d_108_288doubleSource column from the original resource.``
d_108_814doubleSource column from the original resource.``
d_108_4919doubleSource column from the original resource.``
d_106_324doubleSource column from the original resource.``
d_104_228doubleSource column from the original resource.``
d_113_228doubleSource column from the original resource.``
d_104_169doubleSource column from the original resource.``
d_111_8739doubleSource column from the original resource.``
d_9_469700000000003doubleSource column from the original resource.``
d_22_14981459645486doubleSource column from the original resource.``
d_28_871419440294517doubleSource column from the original resource.``
statestringSource column from the original resource.``
fooddoubleSource column from the original resource.``
all_itemsdoubleSource column from the original resource.``
food_2doubleSource column from the original resource.``
all_items_2doubleSource column from the original resource.``
food_3doubleSource column from the original resource.``
all_items_3doubleSource column from the original resource.``
food_4doubleSource column from the original resource.``
all_items_4doubleSource column from the original resource.``
food_5doubleSource column from the original resource.``
all_items_5doubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-consumer-price-index-and-inflation-caed8cff")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "NGA"]

Time-Series Pattern

python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

  • —Canonical time field: year.
  • —Missing values are preserved rather than silently imputed.
  • —Column names are standardized for machine use; source meanings are preserved where known.
  • —Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

Transformations Applied

  • —Converted the source table to Parquet for efficient analytics and ML workflows.
  • —Added or preserved source provenance columns where available.
  • —Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
  • —Preserved source-reported values without analytical imputation.

Suggested Analyses

  • —Build time-series dashboards
  • —Compare economic indicators
  • —Join with population or sector data
  • —Build time-series views and period-over-period comparisons
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_nigeria_consumer_price_index_and_inflation_caed8cff_2025,
  title        = {Consumer Price Index and Inflation | Africa (National Bureau of Statistics, Nigeria)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/154/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-consumer-price-index-and-inflation-caed8cff}}
}

License

Released under other-open.

Original data is published by National Bureau of Statistics, Nigeria. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://microdata.nigerianstat.gov.ng/index.php/catalog/154/related-materials