electricsheepasia/asia-flooding-cambodia-4w-flood-response

Cambodia - 4W Flood Response

Publisher: OCHA Regional Office for Asia and the Pacific (ROAP) · Source: HDX · License: cc-by · Updated: 2024-05-17

Abstract

4W Flood response for Cambodia

Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-05-17. Geographic scope: KHM.

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

Dataset Characteristics

Variables

Identifier / Metadata — unnamed_1 (UNICEF, WVI, DCA ), unnamed_2 (UN Agency, International NGO, Type of organization), unnamed_3 (Food Security and Nutrition, WASH, Education), unnamed_4 (Provision of first aid kits primary schools, Cash assistance to the flood affected and vulnerable households, WASH NFIs), unnamed_5 (In-kind, Cash, Other) and 9 others.

Other — 4w_floods_cambodia (UNICEF, World Vision International, DanChurchAid).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-flooding-cambodia-4w-flood-response")
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 snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 1 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 Regional Office for Asia and the Pacific (ROAP) 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: unnamed_10.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_flooding_cambodia_4w_flood_response,
  title     = {Cambodia - 4W Flood Response},
  author    = {OCHA Regional Office for Asia and the Pacific (ROAP)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/cambodia-4w-flood-response},
  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.