electricsheepafrica/africa-rcce-activities-mapping

RCCE activities mapping

Publisher: UNICEF West and Central Africa (WCARO) (inactive) · Source: HDX · License: cc-by · Updated: 2024-04-12

---

Abstract

Data about who does what where (C4D & RCCE) in North-Kivu and Ituri

Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-04-12. Geographic scope: COD.

Curated into ML-ready Parquet format by Electric Sheep Africa.

---

Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	Tabular records
Rows (total)	229
Columns	9 (3 numeric, 6 categorical, 0 datetime)
Train split	183 rows
Test split	45 rows
Geographic scope	COD
Publisher	UNICEF West and Central Africa (WCARO) (inactive)
HDX last updated	2024-04-12

---

Variables

Identifier / Metadata — code (range 1.0–23.0), esa_source (HDX), esa_processed (2026-04-18).

Other — n (range 1.0–229.0), zs (BENI, KATWA, OICHA), zs_min (Beni, Katwa, Oicha), activité (Community dialogue, Mass / media communication, Advocacy), partenaires (range 1.0–7.0) and 1 others.

---

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-rcce-activities-mapping")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

---

Schema

Column	Type	Null %	Range / Sample Values
n	int64	0.0%	1.0 – 229.0 (mean 115.0)
zs	object	0.0%	BENI, KATWA, OICHA
code	int64	0.0%	1.0 – 23.0 (mean 11.5677)
zs_min	object	0.0%	Beni, Katwa, Oicha
activité	object	0.0%	Community dialogue, Mass / media communication, Advocacy
partenaires	int64	0.0%	1.0 – 7.0 (mean 2.6725)
partenaires_1	object	0.0%	UNICEF, WHO, MOH, UNICEF, WHO, UNICEF, SFCG, CARITAS, WHO, Internews
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-18

---

Numeric Summary

Column	Min	Max	Mean	Median
n	1.0	229.0	115.0	115.0
code	1.0	23.0	11.5677	11.0
partenaires	1.0	7.0	2.6725	2.0

---

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. 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 UNICEF West and Central Africa (WCARO) (inactive) 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 for the publisher's own methodology notes and caveats.

---

Citation

@dataset{hdx_africa_rcce_activities_mapping,
  title     = {RCCE activities mapping},
  author    = {UNICEF West and Central Africa (WCARO) (inactive)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/rcce-activities-mapping},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.