electricsheepafrica/africa-food-for-education-ffe-supported-schools-sudan

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- education
- education-facilities-schools
- food-security
- geodata
- sdn
pretty_name: "Sudan - Food for Education (FFE) Supported Schools"
dataset_info:
splits:
- name: train
num_examples: 1072
- name: test
num_examples: 268
---

# Sudan - Food for Education (FFE) Supported Schools

**Publisher:** OCHA Sudan · **Source:** [HDX](https://data.humdata.org/dataset/food-for-education-ffe-supported-schools-sudan) · **License:** `cc-by` · **Updated:** 2024-09-13

---

## Abstract

WFP Food for Education (FFE) Supported Schools in Sudan. The Microsoft Excel spread sheet contains consolidated record of FFE in in the states of Kassala, Gadaref, Gazeira, North Kordofan, Red Sea, Sennar and South Kordofan. It includes state names, locality names, locations, school names, XY coordinates (in Decimal Degrees) and education by type.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2024-09-13. Geographic scope: **SDN**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Food security and nutrition |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 1,341 |
| **Columns** | 9 (2 numeric, 7 categorical, 0 datetime) |
| **Train split** | 1,072 rows |
| **Test split** | 268 rows |
| **Geographic scope** | SDN |
| **Publisher** | OCHA Sudan |
| **HDX last updated** | 2024-09-13 |

---

## Variables

**Geographic** — `state` (North Kordofan, South Kordofan, Red Sea), `locality` (Bara, Um Rowaba, El Nehoud), `location` (Um Dam, EL Nehoud, Abu Zabad), `lon` (range 27.2342–38.4303), `lat` (range 10.0581–21.9663) and 1 others.

**Identifier / Metadata** — `name_of_school` (Alhumeira, Gabret El Sheikh, Um El Gura ), `esa_source` (HDX), `esa_processed` (2026-04-18).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-food-for-education-ffe-supported-schools-sudan")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `state` | object | 0.0% | North Kordofan, South Kordofan, Red Sea |
| `locality` | object | 0.0% | Bara, Um Rowaba, El Nehoud |
| `location` | object | 13.0% | Um Dam, EL Nehoud, Abu Zabad |
| `name_of_school` | object | 0.0% | Alhumeira, Gabret El Sheikh, Um El Gura |
| `lon` | float64 | 0.0% | 27.2342 – 38.4303 (mean 31.4878) |
| `lat` | float64 | 0.0% | 10.0581 – 21.9663 (mean 14.2035) |
| `type_of_education` | object | 37.4% | Primary, Nomads, Secondary |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-18 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `lon` | 27.2342 | 38.4303 | 31.4878 | 30.546 |
| `lat` | 10.0581 | 21.9663 | 14.2035 | 13.7341 |

---

## 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`. 2 column(s) with >80% missing values were removed: `cp`, `composite`. 26 exact duplicate rows were removed. 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 OCHA Sudan 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: `type_of_education`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/food-for-education-ffe-supported-schools-sudan) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_food_for_education_ffe_supported_schools_sudan,
title = {Sudan - Food for Education (FFE) Supported Schools},
author = {OCHA Sudan},
year = {2024},
url = {https://data.humdata.org/dataset/food-for-education-ffe-supported-schools-sudan},
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.*