electricsheepafrica/africa-ethiopia-3w-operational-presence-september-2019

---
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 September 2019"
dataset_info:
splits:
- name: train
num_examples: 4361
- name: test
num_examples: 1090
---

# Ethiopia 3W Operational Presence September 2019

**Publisher:** OCHA Ethiopia · **Source:** [HDX](https://data.humdata.org/dataset/ethiopia-3w-operational-presence-september-2019) · **License:** `cc-by` · **Updated:** 2025-04-29

---

## Abstract

Operational presence of partners who does what where by woreda as September 2019

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2025-04-29. 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)** | 5,452 |
| **Columns** | 17 (0 numeric, 17 categorical, 0 datetime) |
| **Train split** | 4,361 rows |
| **Test split** | 1,090 rows |
| **Geographic scope** | ETH |
| **Publisher** | OCHA Ethiopia |
| **HDX last updated** | 2025-04-29 |

---

## Variables

**Geographic** — `organization_type` (UN Agency, International NGO, Government), `implementing_agency` (RWB, NDRMC, IOM), `implementing_agencytype` (International NGO, Government, UN Agency), `region` (Oromia, Somali, SNNP), `zone` (West Guji, Gedeo, East Hararge) and 2 others.

**Temporal** — `start_date` (7/15/2019, 4/1/2019, 1/1/2019), `end_date` (12/31/2019, 3/31/2019, 4/30/2019).

**Identifier / Metadata** — `esa_source`, `esa_processed`.

**Other** — `project_status` (On-going, Completed, Planned), `donor` (ECHO, UN AgencyOCHA - EHF, USAID / OFDA), `programme_organization` (UNICEF, NDRMC, IOM), `sector`, `clusteractivities` and 1 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-ethiopia-3w-operational-presence-september-2019")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `project_status` | object | 0.0% | On-going, Completed, Planned |
| `start_date` | object | 27.1% | 7/15/2019, 4/1/2019, 1/1/2019 |
| `end_date` | object | 28.7% | 12/31/2019, 3/31/2019, 4/30/2019 |
| `donor` | object | 25.9% | ECHO, UN AgencyOCHA - EHF, USAID / OFDA |
| `programme_organization` | object | 0.0% | UNICEF, NDRMC, IOM |
| `organization_type` | object | 0.0% | UN Agency, International NGO, Government |
| `implementing_agency` | object | 0.3% | RWB, NDRMC, IOM |
| `implementing_agencytype` | object | 0.2% | International NGO, Government, UN Agency |
| `region` | object | 0.0% | Oromia, Somali, SNNP |
| `zone` | object | 0.1% | West Guji, Gedeo, East Hararge |
| `woreda` | object | 0.4% | |
| `woreda_pcode` | object | 0.8% | |
| `sector` | object | 0.0% | |
| `clusteractivities` | object | 7.1% | |
| `cluster_objective` | object | 4.2% | |
| `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`. 3,560 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.
- The following columns have >20% missing values and should be treated with caution in modelling: `start_date`, `end_date`, `donor`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ethiopia-3w-operational-presence-september-2019) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_ethiopia_3w_operational_presence_september_2019,
title = {Ethiopia 3W Operational Presence September 2019},
author = {OCHA Ethiopia},
year = {2025},
url = {https://data.humdata.org/dataset/ethiopia-3w-operational-presence-september-2019},
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.*