electricsheepasia/asia-displacement-philippines-humanitarian-profile

Philippines - DROMIC data on municipalities within 50km radius of typhoon Haiyan

Publisher: OCHA Philippines · Source: HDX · License: hdx-other · Updated: 2023-03-02

Abstract

DROMIC data by DSWD on municipalities within the 50km radius of the typhoon Haiyan/Yolanda track as of 27 January 2014. Historic COD used during response to Typhoon Haiyan, November 2013.

Each row in this dataset represents tabular records. Data was last updated on HDX on 2023-03-02. Geographic scope: PHL.

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

Dataset Characteristics

Variables

Identifier / Metadata — unnamed_2 (range 1.0–38.0), unnamed_3 (San Remegio , Pilar, Sta. Fe ), unnamed_4 (range 1325.0–1472248.0), unnamed_5 (range 6228.0–7110958.0), unnamed_6 (range 0.0–918261.0) and 6 others.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-displacement-philippines-humanitarian-profile")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Numeric Summary

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`. 2 column(s) with >80% missing values were removed: `republicofthephilippines, unnamed_1`. 5 exact duplicate rows were removed. 8 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 Philippines 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_displacement_philippines_humanitarian_profile,
  title     = {Philippines - DROMIC data on municipalities within 50km radius of  typhoon Haiyan},
  author    = {OCHA Philippines},
  year      = {2023},
  url       = {https://data.humdata.org/dataset/philippines-humanitarian-profile},
  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.