electricsheepafrica/africa-drc-3-w-national-june-2015

---
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
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- education
- who-is-doing-what-and-where-3w-4w-5w
- cod
pretty_name: "DRC - 3 W National - June 2015"
dataset_info:
splits:
- name: train
num_examples: 1480
- name: test
num_examples: 370
---

# DRC - 3 W National - June 2015

**Publisher:** OCHA Democratic Republic of the Congo (DRC) · **Source:** [HDX](https://data.humdata.org/dataset/drc-3-w-national-june-2015) · **License:** `cc-by-igo` · **Updated:** 2024-08-08

---

## Abstract

3W of operational projects DRC

Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2024-08-08. Geographic scope: **COD**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Subnational administrative unit observations |
| **Rows (total)** | 1,851 |
| **Columns** | 26 (6 numeric, 20 categorical, 0 datetime) |
| **Train split** | 1,480 rows |
| **Test split** | 370 rows |
| **Geographic scope** | COD |
| **Publisher** | OCHA Democratic Republic of the Congo (DRC) |
| **HDX last updated** | 2024-08-08 |

---

## Variables

**Geographic** — `agency_acronym` (PAM, IEDA Relief, UNHCR), `province` (Sud-Kivu, Katanga, Nord-Kivu), `district` (Sud-Kivu, Nord-Kivu, Maniema), `territory` (Rutshuru, Kalehe, Walikale), `location` (Toutes, toutes les structures, toutes les localités) and 2 others.

**Temporal** — `start_date`, `end_date`.

**Demographic** — `household` (range 1.0–5000000.0).

**Identifier / Metadata** — `adm1pcode` (range 50.0–70.0), `adm2pcode` (range 501.0–707.0), `adm3pcode` (range 5010.0–7076.0), `esa_source`, `esa_processed`.

**Other** — `health_division` (Toutes, Pweto, Dungu), `titre_de_projet` (Suivi et Evaluation des Activités relevant du Mandat du HCR/Monitoring de Protection, Gouvernance pour la protection des enfants, Nutrition), `cluster` (Protection, Santé, Nutrition), `cluster_cleaned` (Protection, Securite Alimentaire, Santé), `project` and 6 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-drc-3-w-national-june-2015")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `agency_acronym` | object | 0.2% | PAM, IEDA Relief, UNHCR |
| `province` | object | 0.0% | Sud-Kivu, Katanga, Nord-Kivu |
| `adm1pcode` | int64 | 0.0% | 50.0 – 70.0 (mean 61.8622) |
| `district` | object | 0.0% | Sud-Kivu, Nord-Kivu, Maniema |
| `adm2pcode` | int64 | 0.0% | 501.0 – 707.0 (mean 618.3798) |
| `territory` | object | 0.0% | Rutshuru, Kalehe, Walikale |
| `adm3pcode` | float64 | 0.5% | 5010.0 – 7076.0 (mean 6193.3286) |
| `health_division` | object | 18.4% | Toutes, Pweto, Dungu |
| `location` | object | 27.4% | Toutes, toutes les structures, toutes les localités |
| `titre_de_projet` | object | 15.1% | Suivi et Evaluation des Activités relevant du Mandat du HCR/Monitoring de Protection, Gouvernance pour la protection des enfants, Nutrition |
| `cluster` | object | 0.3% | Protection, Santé, Nutrition |
| `cluster_cleaned` | object | 0.0% | Protection, Securite Alimentaire, Santé |
| `activity_description` | object | 44.5% | Monitoring de protection, Réhabilitation nutritionnelle, Distribution alimentaire |
| `project` | object | 18.1% | |
| `project_description` | object | 23.6% | |
| `donors` | object | 21.1% | |
| `household` | float64 | 40.3% | 1.0 – 5000000.0 (mean 214793.5644) |
| `women` | float64 | 71.0% | 2.0 – 642852.0 (mean 113061.825) |
| `men` | float64 | 75.8% | 1.0 – 484205.0 (mean 100668.808) |
| `type_of_beneficiary` | object | 19.1% | |
| `implenting_partners` | object | 46.7% | |
| `start_date` | object | 8.8% | |
| `end_date` | object | 11.3% | |
| `notes` | object | 68.2% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `adm1pcode` | 50.0 | 70.0 | 61.8622 | 62.0 |
| `adm2pcode` | 501.0 | 707.0 | 618.3798 | 622.0 |
| `adm3pcode` | 5010.0 | 7076.0 | 6193.3286 | 6224.0 |
| `household` | 1.0 | 5000000.0 | 214793.5644 | 5737.0 |
| `women` | 2.0 | 642852.0 | 113061.825 | 1923.0 |
| `men` | 1.0 | 484205.0 | 100668.808 | 2000.0 |

---

## 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`. 2 column(s) with >80% missing values were removed: `sub_cluster`, `sub_type_project`. 4 exact duplicate rows were removed. 3 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 Democratic Republic of the Congo (DRC) 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: `location`, `activity_description`, `project_description`, `donors`, `household`, `women`, `men`, `implenting_partners`....
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/drc-3-w-national-june-2015) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_drc_3_w_national_june_2015,
title = {DRC - 3 W National - June 2015},
author = {OCHA Democratic Republic of the Congo (DRC)},
year = {2024},
url = {https://data.humdata.org/dataset/drc-3-w-national-june-2015},
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.*