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

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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-operational-presence-philippines-who-does-what-where-and-when.

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Dataset Card

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](https://huggingface.co/electricsheepafrica).


Dataset Characteristics

DomainHumanitarian and development data
Unit of observationTabular records
Rows (total)6,227
Columns2 (0 numeric, 2 categorical, 0 datetime)
Train split4,981 rows
Test split1,245 rows
Geographic scopePHL
PublisherGlobal Shelter Cluster (inactive)
HDX last updated2025-03-07

Variables

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


Quick Start

python
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

ColumnTypeNull %Range / Sample Values
esa_sourceobject0.0%HDX
esa_processedobject0.0%2026-05-04

Numeric Summary

ColumnMinMaxMeanMedian

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 snakecase. 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: `unnamed0, unnamed1`, `unnamed2, unnamed3`, `unnamed4, 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

bibtex
@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](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.