---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- humanitarian-response-plan-hrp
- who-is-doing-what-and-where-3w-4w-5w
- rwa
pretty_name: "Rwanda: Response Plan projects"
dataset_info:
  splits:
    - name: train
      num_examples: 330
    - name: test
      num_examples: 82
---

# Rwanda: Response Plan projects

**Publisher:** OCHA Humanitarian Programme Cycle Tools (HPC Tools) · **Source:** [HDX](https://data.humdata.org/dataset/hrp-projects-rwa) · **License:** `cc-by-igo` · **Updated:** 2026-03-30

---

## Abstract

Projects proposed, in progress, or completed as part of the annual Rwanda Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools

**Important:** some projects in Rwanda might be missing, and others might not apply specifically to Rwanda. See _Caveats_ under the _Additional information_ tab.

Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `startdate`, `enddate` column(s). Geographic scope: **RWA**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Time-series observations |
| **Rows (total)** | 413 |
| **Columns** | 13 (1 numeric, 10 categorical, 2 datetime) |
| **Train split** | 330 rows |
| **Test split** | 82 rows |
| **Geographic scope** | RWA |
| **Publisher** | OCHA Humanitarian Programme Cycle Tools (HPC Tools) |
| **HDX last updated** | 2026-03-30 |

---

## Variables

**Geographic** — `locations` (UGA, RWA, TZA).

**Temporal** — `startdate`, `enddate`.

**Identifier / Metadata** — `name` (Zambia: United Nations High Commissioner for Refugees (Basic Needs response), Uganda: HelpAge International (Protection response), Rwanda: International Organization for Migration (Protection response)), `versioncode` (RDRC_RRP24-BSC-213740-1, RDRC_RRP24-PRO-213533-1, RDRC_RRP24-PRO-213560-1), `response_plan_code` (RDRC_RRP24), `esa_source` (HDX), `esa_processed` (2026-04-04).

**Other** — `currentrequestedfunds` (range 700.0–38119944.0), `objective` (United Nations High Commissioner for Refugees: Basic Needs response for DRC Regional Plan in Zambia, HelpAge International: Protection response for DRC Regional Plan in Uganda, International Organization for Migration: Protection response for DRC Regional Plan in Rwanda), `globalclusters` (Early Recovery, Education, Health), `organizations` (United Nations High Commissioner for Refugees, United Nations Children's Fund, World Vision International), `plans` (Democratic Republic of the Congo Regional Refugee Response Plan 2024).

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-hrp-projects-rwa")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `name` | object | 0.0% | Zambia: United Nations High Commissioner for Refugees (Basic Needs response), Uganda: HelpAge International (Protection response), Rwanda: International Organization for Migration (Protection response) |
| `versioncode` | object | 0.0% | RDRC_RRP24-BSC-213740-1, RDRC_RRP24-PRO-213533-1, RDRC_RRP24-PRO-213560-1 |
| `currentrequestedfunds` | int64 | 0.0% | 700.0 – 38119944.0 (mean 1618104.9467) |
| `objective` | object | 0.0% | United Nations High Commissioner for Refugees: Basic Needs response for DRC Regional Plan in Zambia, HelpAge International: Protection response for DRC Regional Plan in Uganda, International Organization for Migration: Protection response for DRC Regional Plan in Rwanda |
| `startdate` | datetime64[ns] | 0.0% |  |
| `enddate` | datetime64[ns] | 0.0% |  |
| `globalclusters` | object | 0.0% | Early Recovery, Education, Health |
| `locations` | object | 0.0% | UGA, RWA, TZA |
| `organizations` | object | 0.0% | United Nations High Commissioner for Refugees, United Nations Children's Fund, World Vision International |
| `plans` | object | 0.0% | Democratic Republic of the Congo Regional Refugee Response Plan 2024 |
| `response_plan_code` | object | 0.0% | RDRC_RRP24 |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-04 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `currentrequestedfunds` | 700.0 | 38119944.0 | 1618104.9467 | 500000.0 |

---

## 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`. 1 column(s) with >80% missing values were removed: `partners`. 2 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 Humanitarian Programme Cycle Tools (HPC Tools) 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/hrp-projects-rwa) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_hrp_projects_rwa,
  title     = {Rwanda: Response Plan projects},
  author    = {OCHA Humanitarian Programme Cycle Tools (HPC Tools)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/hrp-projects-rwa},
  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.*