electricsheepafrica/africa-ocha-ethiopia-3w-november-2018

---
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
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- hxl
- who-is-doing-what-and-where-3w-4w-5w
- eth
pretty_name: "Ethiopia - 3W Operational Presence November 2018"
dataset_info:
splits:
- name: train
num_examples: 6940
- name: test
num_examples: 1735
---

# Ethiopia - 3W Operational Presence November 2018

**Publisher:** OCHA Ethiopia · **Source:** [HDX](https://data.humdata.org/dataset/ocha-ethiopia-3w-november-2018) · **License:** `cc-by` · **Updated:** 2025-04-25

---

## Abstract

OCHA Ethiopia 3W dataset 2018

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-04-25. Geographic scope: **ETH**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Subnational administrative unit observations |
| **Rows (total)** | 8,676 |
| **Columns** | 12 (0 numeric, 12 categorical, 0 datetime) |
| **Train split** | 6,940 rows |
| **Test split** | 1,735 rows |
| **Geographic scope** | ETH |
| **Publisher** | OCHA Ethiopia |
| **HDX last updated** | 2025-04-25 |

---

## Variables

**Geographic** — `organization_type` (UN Agency, International NGO, Government), `region` (Oromia, Somali, SNNP), `zone` (Gedeo, East Hararge, Borena ), `woreda` (Kochere Gedeb, Kochere, Yirgachefe), `activity_type` (SAM treatment and screening, VitA supplementation, Deworming, IYCF, GMP, Nutritional surveillance, screening, IYCF, coordination, treatment, provision of equipment and commodities , Hygiene kit distribution (all kits including, bathing and laundry soap, sanitary pads, buckets or jerry cans, nappies and potties)) and 1 others.

**Identifier / Metadata** — `pcode` (0, ET070506, ET070502), `esa_source`, `esa_processed`.

**Other** — `programme_organization` (UNICEF, WFP, Government), `sector` (WASH, Nutrition, Education), `project_status` (Ongoing, Completed, Planned).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-ocha-ethiopia-3w-november-2018")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `programme_organization` | object | 9.2% | UNICEF, WFP, Government |
| `organization_type` | object | 9.1% | UN Agency, International NGO, Government |
| `region` | object | 0.0% | Oromia, Somali, SNNP |
| `zone` | object | 0.3% | Gedeo, East Hararge, Borena |
| `woreda` | object | 1.5% | Kochere Gedeb, Kochere, Yirgachefe |
| `pcode` | object | 2.1% | 0, ET070506, ET070502 |
| `sector` | object | 0.0% | WASH, Nutrition, Education |
| `activity_type` | object | 8.6% | SAM treatment and screening, VitA supplementation, Deworming, IYCF, GMP, Nutritional surveillance, screening, IYCF, coordination, treatment, provision of equipment and commodities , Hygiene kit distribution (all kits including, bathing and laundry soap, sanitary pads, buckets or jerry cans, nappies and potties) |
| `project_status` | object | 0.0% | Ongoing, Completed, Planned |
| `implementing_agency` | object | 0.1% | Government, RWB, UNICEF |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
_No numeric columns._

---

## 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`. 6,222 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 Ethiopia 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/ocha-ethiopia-3w-november-2018) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_ocha_ethiopia_3w_november_2018,
title = {Ethiopia - 3W Operational Presence November 2018},
author = {OCHA Ethiopia},
year = {2025},
url = {https://data.humdata.org/dataset/ocha-ethiopia-3w-november-2018},
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.*