electricsheepasia/asia-climate-hdx-hapi-sri-lanka

HDX HAPI Data for Sri Lanka

Publisher: HDX Humanitarian API Data · Source: HDX · License: hdx-other · Updated: 2026-02-18

Abstract

This dataset contains data obtained from the HDX Humanitarian API (HDX HAPI), which provides standardized humanitarian indicators designed for seamless interoperability from multiple sources. The data facilitates automated workflows and visualizations to support humanitarian decision making. For more information, please see the HDX HAPI landing page and documentation.

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

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

Dataset Characteristics

Variables

Geographic — location_code (LKA), provider_admin1_name (Northern, Sabaragamuwa, Central), provider_admin2_name (Ratnapura, Matale, Kandy), admin1_code (LK4, LK9, LK2), admin1_name (Northern, Sabaragamuwa, Central) and 5 others.

Temporal — reference_period_start, reference_period_end.

Identifier / Metadata — esa_source (HDX), esa_processed.

Other — has_hrp, in_gho, operation (Tropical Cyclone Ditwah, Sri Lanka Floods (2017)), reporting_round (range 1.0–4.0).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-climate-hdx-hapi-sri-lanka")
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. 2 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 HDX Humanitarian API Data 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: provider_admin2_name, admin2_code, admin2_name.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_climate_hdx_hapi_sri_lanka,
  title     = {HDX HAPI Data for Sri Lanka},
  author    = {HDX Humanitarian API Data},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/hdx-hapi-lka},
  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.