README.md

---
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](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_south_sudan_weekly_6857) · **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](https://huggingface.co/electricsheepafrica).*

---

## 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

```python
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](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_south_sudan_weekly_6857) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@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](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*