electricsheepasia/asia-4w-central-sulawesi-earthquake-and-tsunami-2018

Indonesia - 4W Central Sulawesi Earthquake and Tsunami

Publisher: OCHA Indonesia (inactive) · Source: HDX · License: cc-by · Updated: 2025-11-05

Abstract

Central Sulawesi Earthquake and Tsunami 2018 Who does What Where (3W) matrix

Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the start_date, end_date column(s). Geographic scope: IDN.

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

Dataset Characteristics

Variables

Geographic — implementing_agency (BNPB/BPBD/BAPPEDA, IBI/PHO, UNICEF), org_type (National NGOs, Government, UN Agencies), district (Palu, Sigi, Donggala), admin_level_5 (RH tent, RH Tent, ), activity_details and 2 others.

Temporal — reporting_period (27 Nov - 07 Dec 2018), start_date, end_date.

Demographic — village (Petobo, Balaroa, Lolu).

Identifier / Metadata — material_provided, esa_source, esa_processed.

Other — lead_organization (UNFPA, UNDP, MoSA/Dinsos), sub_dstrict (Sigi Biromaru, Palu Barat, Sirenja), sector_cluster (Health, Protection, WASH), sub_sector (Psychosocial support, Ruang Belajar Sementara | Temporary Learning Space , Air | Water), status.

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-4w-central-sulawesi-earthquake-and-tsunami-2018")
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`. 3 column(s) with >80% missing values were removed: `totalbeneficiariesreachedhousehold, totalbeneficiariesplannedhousehold`, `activitydescription`. 119 exact duplicate rows were removed. 3 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 Indonesia (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.
• —The following columns have >20% missing values and should be treated with caution in modelling: admin_level_5, end_date, of_primary_beneficiaries, material_provided.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_4w_central_sulawesi_earthquake_and_tsunami_2018,
  title     = {Indonesia - 4W Central Sulawesi Earthquake and Tsunami},
  author    = {OCHA Indonesia (inactive)},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/4w-central-sulawesi-earthquake-and-tsunami-2018},
  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.