Datasets:

electricsheepasia
/

asia-operational-presence-philippines-who-does-what-where-and-when

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
  - cyclones-hurricanes-typhoons
  - operational-presence
  - shelter
  - who-is-doing-what-and-where-3w-4w-5w
  - phl
pretty_name: Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco
dataset_info:
  splits:
    - name: train
      num_examples: 4981
    - name: test
      num_examples: 1245

Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco

Publisher: Global Shelter Cluster (inactive) · Source: HDX · License: cc-by · Updated: 2025-03-07

Abstract

Shelter Cluster 4W report (Who does What, Where, and When) for typhoon Goni (Rolly) and Vamco (Ulysses) in the Philippines

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-03-07. Geographic scope: PHL.

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

Dataset Characteristics


Domain	Humanitarian and development data
Unit of observation	Tabular records
Rows (total)	6,227
Columns	2 (0 numeric, 2 categorical, 0 datetime)
Train split	4,981 rows
Test split	1,245 rows
Geographic scope	PHL
Publisher	Global Shelter Cluster (inactive)
HDX last updated	2025-03-07

Variables

Identifier / Metadata — esa_source (HDX), esa_processed (2026-05-04).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-operational-presence-all")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Column	Type	Null %	Range / Sample Values
`esa_source`	object	0.0%	HDX
`esa_processed`	object	0.0%	2026-05-04

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. 38 column(s) with >80% missing values were removed: unnamed_0, unnamed_1, unnamed_2, unnamed_3, unnamed_4, unnamed_5.... 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 Global Shelter Cluster (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_asia_operational_presence_all,
  title     = {Philippines - Who does What, Where, and When (4W) typhoon Goni and Vamco},
  author    = {Global Shelter Cluster (inactive)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/philippines-who-does-what-where-and-when-4w-for-typhoon-goni-and-vamco-01-december-2020},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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