electricsheepasia/asia-displacement-philippines-displacement-data-mindanao-e

Philippines Displacement - IDPs -Mindanao Earthquake - Site Assessment [IOM DTM]

Publisher: International Organization for Migration (IOM) · Source: HDX · License: hdx-other · Updated: 2025-04-29

Abstract

The dataset contains number of IDPs, families and their needs at sub national level with site coordinates.

Each row in this dataset represents facility or site records. Temporal coverage is indicated by the date_of_current_survey, opening_date_date_when_first_occupied_by_idps column(s). Geographic scope: PHL.

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

Dataset Characteristics

Variables

Geographic — survey_round (MatDTM01, MatDTM02), date_of_current_survey, region (Region XI, #adm1+name), region_pcode (PH110000000, #adm1+code), province (Davao del Sur, Davao Del Sur, #adm2+name) and 20 others.

Demographic — management, no_of_persons (range 34.0–3061.0).

Identifier / Metadata — site_id (2019PhMinEQ0124, 2019PhMinEQ0125, 2019PhMinEQ0126), name_of_site (#meta+site+name, Kapoc 2, Bangkal), esa_source, esa_processed.

Other — designation (Brgy. Secretary, Brgy. Chairman, Camp Manager ), no_of_families (range 8.0–774.0), 1st_most_urgent_need, 2nd_most_urgent_need, 3rd_most_urgent_need and 3 others.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-displacement-philippines-displacement-data-mindanao-e")
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`. 5 column(s) with >80% missing values were removed: `returnorrelocationprospects, protracteddisplacement`, `shelternfidetails`, `foodsecuritylivelihooddetails, safetysecuritydetails`. 5 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 International Organization for Migration (IOM) and has not been independently validated by ESA.
• —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• —The following columns have >20% missing values and should be treated with caution in modelling: management, wash_details, health_details.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_displacement_philippines_displacement_data_mindanao_e,
  title     = {Philippines Displacement - IDPs -Mindanao Earthquake - Site Assessment [IOM DTM]},
  author    = {International Organization for Migration (IOM)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/philippines-displacement-data-mindanao-earthquake-site-assessment-iom-dtm},
  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.