electricsheepafrica/africa-srf-2014

---
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:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- education
- health
- humanitarian-needs-overview-hno
- nutrition
- population
- shelter
- water-sanitation-and-hygiene-wash
- som
pretty_name: "Somalia beneficiary figures (targeted and reached) by month, Jan - Dec 2014"
dataset_info:
splits:
- name: train
num_examples: 1880
- name: test
num_examples: 470
---

# Somalia beneficiary figures (targeted and reached) by month, Jan - Dec 2014

**Publisher:** OCHA Somalia · **Source:** [HDX](https://data.humdata.org/dataset/srf-2014) · **License:** `cc-by-igo` · **Updated:** 2023-11-15

---

## Abstract

2014 response data for Somalia. (Single Reporting Format) The data shows targets and response by cluster per month. The data is sourced from the humanitarian clusters in Somalia.

Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **SOM**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 2,350 |
| **Columns** | 14 (3 numeric, 10 categorical, 1 datetime) |
| **Train split** | 1,880 rows |
| **Test split** | 470 rows |
| **Geographic scope** | SOM |
| **Publisher** | OCHA Somalia |
| **HDX last updated** | 2023-11-15 |

---

## Variables

**Geographic** — `region` (Awdal, Lower Juba, Nugaal), `category` (FSC, Wash, Education), `end_year_target` (550, 6,000, 0), `cumulative_reached_to_date` (0, 600, 3,265), `cumulative_reached_num_to_date` (range 0.0–1427330.0).

**Temporal** — `date`, `month_num` (range 1.0–12.0), `month` (December, April, May), `current_target_to_date` (0, 3,000, 1,500), `percent_current_target_reached_to_date` (0%, 6%, 4%) and 1 others.

**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-08).

**Other** — `metric` (Number of people receiving primary and/or basic secondary health care services, Number of people targeted through interventions geared towards improving access to food and safety nets, Number of people targeted through livelihood investment and assets activities).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-srf-2014")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `region` | object | 0.0% | Awdal, Lower Juba, Nugaal |
| `date` | datetime64[ns] | 0.0% | |
| `month_num` | int64 | 0.0% | 1.0 – 12.0 (mean 6.9677) |
| `month` | object | 0.0% | December, April, May |
| `category` | object | 0.0% | FSC, Wash, Education |
| `metric` | object | 0.0% | Number of people receiving primary and/or basic secondary health care services, Number of people targeted through interventions geared towards improving access to food and safety nets, Number of people targeted through livelihood investment and assets activities |
| `end_year_target` | object | 0.0% | 550, 6,000, 0 |
| `current_target_to_date` | object | 0.0% | 0, 3,000, 1,500 |
| `cumulative_reached_to_date` | object | 25.5% | 0, 600, 3,265 |
| `cumulative_reached_num_to_date` | float64 | 0.0% | 0.0 – 1427330.0 (mean 45403.4732) |
| `percent_current_target_reached_to_date` | object | 0.0% | 0%, 6%, 4% |
| `ratio_of_current_target_reached_to_date` | float64 | 0.0% | 0.0 – 13.89 (mean 0.6117) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-08 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `month_num` | 1.0 | 12.0 | 6.9677 | 7.0 |
| `cumulative_reached_num_to_date` | 0.0 | 1427330.0 | 45403.4732 | 1948.0 |
| `ratio_of_current_target_reached_to_date` | 0.0 | 13.89 | 0.6117 | 0.25 |

---

## 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 OCHA Somalia 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: `cumulative_reached_to_date`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/srf-2014) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_srf_2014,
title = {Somalia beneficiary figures (targeted and reached) by month, Jan - Dec 2014},
author = {OCHA Somalia},
year = {2023},
url = {https://data.humdata.org/dataset/srf-2014},
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.*