Datasets:

electricsheepafrica
/

africa-nigeria-acute-food-insecurity-country-data

annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - en
license: other
multilinguality:
  - monolingual
size_categories:
  - n<1K
source_datasets:
  - original
task_categories:
  - tabular-classification
  - tabular-regression
task_ids: []
tags:
  - africa
  - humanitarian
  - hdx
  - electric-sheep-africa
  - food-security
  - integrated-food-security-phase-classification-ipc
  - nga
pretty_name: 'Nigeria: Acute Food Insecurity Country Data'
dataset_info:
  splits:
    - name: train
      num_examples: 11
    - name: test
      num_examples: 2

Nigeria: Acute Food Insecurity Country Data

Publisher: Integrated Food Security Phase Classification (IPC) · Source: HDX · License: other-pd-nr · Updated: 2026-02-16

Abstract

The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.

There is also a global dataset.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the date_of_analysis, from column(s). Geographic scope: NGA.

Curated into ML-ready Parquet format by Electric Sheep Africa.

Dataset Characteristics


Domain	Food security and nutrition
Unit of observation	Country-level aggregates
Rows (total)	14
Columns	11 (3 numeric, 5 categorical, 3 datetime)
Train split	11 rows
Test split	2 rows
Geographic scope	NGA
Publisher	Integrated Food Security Phase Classification (IPC)
HDX last updated	2026-02-16

Variables

Geographic — date_of_analysis, country (NGA), total_country_population (range 242431832.0–242431832.0), validity_period (current, first projection).

Demographic — percentage (range 0.0–1.0).

Outcome / Measurement — phase (all, 3+, 1), number (range 0.0–217933705.0).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-04).

Other — from, to.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-nigeria-acute-food-insecurity-country-data")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Column	Type	Null %	Range / Sample Values
`date_of_analysis`	datetime64[ns]	0.0%
`country`	object	0.0%	NGA
`total_country_population`	int64	0.0%	242431832.0 – 242431832.0 (mean 242431832.0)
`validity_period`	object	0.0%	current, first projection
`from`	datetime64[ns]	0.0%
`to`	datetime64[ns]	0.0%
`phase`	object	0.0%	all, 3+, 1
`number`	int64	0.0%	0.0 – 217933705.0 (mean 66154334.8571)
`percentage`	float64	0.0%	0.0 – 1.0 (mean 0.3029)
`esa_source`	object	0.0%	HDX
`esa_processed`	object	0.0%	2026-04-04

Numeric Summary

Column	Min	Max	Mean	Median
`total_country_population`	242431832.0	242431832.0	242431832.0	242431832.0
`number`	0.0	217933705.0	66154334.8571	27212934.0
`percentage`	0.0	1.0	0.3029	0.12

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 3 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

Limitations

Data originates from Integrated Food Security Phase Classification (IPC) and has not been independently validated by ESA.
Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_africa_nigeria_acute_food_insecurity_country_data,
  title     = {Nigeria: Acute Food Insecurity Country Data},
  author    = {Integrated Food Security Phase Classification (IPC)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/nigeria-acute-food-insecurity-country-data},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.