electricsheepafrica/africa-fewsnet-staple-food-price-data-for-nigeria-weekly-6837

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- tabular-regression
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- economics
- food-security
- indicators
- markets
- nga
pretty_name: "Nigeria Weekly FEWS NET Staple Food Price Data"
dataset_info:
splits:
- name: train
num_examples: 244230
- name: test
num_examples: 61057
---

# Nigeria Weekly FEWS NET Staple Food Price Data

**Publisher:** FEWS NET · **Source:** [HDX](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_nigeria_weekly_6837) · **License:** `cc-by` · **Updated:** 2026-04-01

---

## Abstract

Nigeria Weekly staple food price data collected by FEWS NET since 2021.

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

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Food security and nutrition |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 305,288 |
| **Columns** | 17 (3 numeric, 13 categorical, 1 datetime) |
| **Train split** | 244,230 rows |
| **Test split** | 61,057 rows |
| **Geographic scope** | NGA |
| **Publisher** | FEWS NET |
| **HDX last updated** | 2026-04-01 |

---

## Variables

**Geographic** — `country` (Nigeria), `admin_1` (Kaduna, Borno, Yobe), `longitude` (range 3.3958–13.265), `latitude` (range 4.812–13.7273), `price_type` (Retail, Wholesale) and 2 others.

**Temporal** — `period_date`.

**Outcome / Measurement** — `value` (range 1.0–799000.0).

**Identifier / Metadata** — `source_document` (Famine Early Warning Systems Network (FEWS NET), Nigeria, Price (weekly), Famine Early Warning Systems Network (FEWS NET), Nigeria, Livestock Price (weekly)), `product_source` (Local, Import), `esa_source`, `esa_processed`.

**Other** — `market` (Dandume, Ibadan, Bodija, Gombe), `cpcv2` (R01122AC, R01142AD, R01709AC), `product` (Maize Grain (White), Sorghum (White), Cowpeas (White)), `unit` (kg, 100_kg, L).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-nigeria-weekly-6837")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country` | object | 0.0% | Nigeria |
| `market` | object | 0.0% | Dandume, Ibadan, Bodija, Gombe |
| `admin_1` | object | 0.0% | Kaduna, Borno, Yobe |
| `longitude` | float64 | 0.0% | 3.3958 – 13.265 (mean 8.5099) |
| `latitude` | float64 | 0.0% | 4.812 – 13.7273 (mean 10.4386) |
| `cpcv2` | object | 0.0% | R01122AC, R01142AD, R01709AC |
| `product` | object | 0.0% | Maize Grain (White), Sorghum (White), Cowpeas (White) |
| `source_document` | object | 0.0% | Famine Early Warning Systems Network (FEWS NET), Nigeria, Price (weekly), Famine Early Warning Systems Network (FEWS NET), Nigeria, Livestock Price (weekly) |
| `period_date` | datetime64[ns] | 0.0% | |
| `price_type` | object | 0.0% | Retail, Wholesale |
| `product_source` | object | 0.0% | Local, Import |
| `unit` | object | 0.0% | kg, 100_kg, L |
| `unit_type` | object | 0.0% | Weight, Volume, Item |
| `currency` | object | 0.0% | |
| `value` | float64 | 18.3% | 1.0 – 799000.0 (mean 13108.5953) |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `longitude` | 3.3958 | 13.265 | 8.5099 | 8.5364 |
| `latitude` | 4.812 | 13.7273 | 10.4386 | 11.28 |
| `value` | 1.0 | 799000.0 | 13108.5953 | 528.63 |

---

## 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`. 1 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 FEWS NET 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](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_nigeria_weekly_6837) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_fewsnet_staple_food_price_data_for_nigeria_weekly_6837,
title = {Nigeria Weekly FEWS NET Staple Food Price Data},
author = {FEWS NET},
year = {2026},
url = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_nigeria_weekly_6837},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*