electricsheepafrica/africa-comoros-comoros-cyclone-tropical-storm-may-2024-749b30f0

Comoros: Cyclone - Tropical storm - May 2024 | Africa (Comoros official open data)

39 rows - 1 Africa country - 2024 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Comoros as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• —Source: Comoros: Cyclone - Tropical storm - May 2024
• —Publisher: WFP Automated Disaster Analysis & Mapping
• —Resource: 1001060-15-adam-ts-1001060-15-pop-estimation.csv
• —Format: CSV
• —License: CC BY-SA
• —Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Indicators or Resource Contents

• —This source file is packaged as a normalized tabular resource.

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-comoros-comoros-cyclone-tropical-storm-may-2024-749b30f0")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "COM"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_comoros_comoros_cyclone_tropical_storm_may_2024_749b30f0_2024,
  title        = {Comoros: Cyclone - Tropical storm - May 2024 | Africa (Comoros official open data)},
  author       = {WFP Automated Disaster Analysis & Mapping},
  year         = {2024},
  url          = {https://data.humdata.org/dataset/comoros-cyclone-1001060},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-comoros-comoros-cyclone-tropical-storm-may-2024-749b30f0}}
}

License

Released under CC BY-SA.

Original data (c) WFP Automated Disaster Analysis & Mapping. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

Provenance: ingested 2026-08-25 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/3c283ec8-dc26-43cb-a25c-139a80b69daa/resource/9dc3a875-1714-4bba-a74e-9afe7252a4b7/download/1001060-15-adam-ts-1001060-15-pop-estimation.csv