Datasets:

electricsheepafrica
/

africa-fewsnet-staple-food-price-data-for-south-sudan-weekly-6857

annotations_creators:
  - no-annotation
language_creators:
  - found
language:
  - en
license: cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - tabular-regression
  - other
task_ids: []
tags:
  - africa
  - humanitarian
  - hdx
  - electric-sheep-africa
  - eastern-africa
  - economics
  - food-security
  - indicators
  - markets
  - ssd
pretty_name: South Sudan Weekly FEWS NET Staple Food Price Data
dataset_info:
  splits:
    - name: train
      num_examples: 38721
    - name: test
      num_examples: 9680

South Sudan Weekly FEWS NET Staple Food Price Data

Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-07

Abstract

South Sudan 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: SSD.

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)	48,402
Columns	17 (3 numeric, 13 categorical, 1 datetime)
Train split	38,721 rows
Test split	9,680 rows
Geographic scope	SSD
Publisher	FEWS NET
HDX last updated	2026-04-07

Variables

Geographic — country (South Sudan), admin_1 (Jonglei, Upper Nile, Central Equatoria), longitude (range 27.3979–33.9249), latitude (range 4.0928–9.8874), price_type (Retail, Wholesale, Wage) and 2 others.

Temporal — period_date.

Outcome / Measurement — value (range 1.0–1120000.0).

Identifier / Metadata — source_document (Famine Early Warning Systems Network (FEWS NET), South Sudan, Price), product_source (Local, Import), esa_source, esa_processed.

Other — market (Leer, Maiwut, Malakal, Aburoc), cpcv2 (R01122AC, R01142AC, R01142AH), product (Maize Grain (White), Sorghum (Red), Sorghum (Feterita)), unit (kg, 3.5_kg, ea).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-south-sudan-weekly-6857")
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%	South Sudan
`market`	object	0.0%	Leer, Maiwut, Malakal, Aburoc
`admin_1`	object	0.0%	Jonglei, Upper Nile, Central Equatoria
`longitude`	float64	0.0%	27.3979 – 33.9249 (mean 31.3085)
`latitude`	float64	0.0%	4.0928 – 9.8874 (mean 7.1659)
`cpcv2`	object	0.0%	R01122AC, R01142AC, R01142AH
`product`	object	0.0%	Maize Grain (White), Sorghum (Red), Sorghum (Feterita)
`source_document`	object	0.0%	Famine Early Warning Systems Network (FEWS NET), South Sudan, Price
`period_date`	datetime64[ns]	0.0%
`price_type`	object	0.0%	Retail, Wholesale, Wage
`product_source`	object	0.0%	Local, Import
`unit`	object	0.0%	kg, 3.5_kg, ea
`unit_type`	object	0.0%	Weight, Item, Volume
`currency`	object	0.0%
`value`	float64	54.2%	1.0 – 1120000.0 (mean 24287.4641)
`esa_source`	object	0.0%
`esa_processed`	object	0.0%

Numeric Summary

Column	Min	Max	Mean	Median
`longitude`	27.3979	33.9249	31.3085	31.5547
`latitude`	4.0928	9.8874	7.1659	7.457
`value`	1.0	1120000.0	24287.4641	3920.0

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.
The following columns have >20% missing values and should be treated with caution in modelling: value.
Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_africa_fewsnet_staple_food_price_data_for_south_sudan_weekly_6857,
  title     = {South Sudan Weekly FEWS NET Staple Food Price Data},
  author    = {FEWS NET},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_south_sudan_weekly_6857},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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