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electricsheepafrica/africa-madagascar-madagascar-cyclone-tropical-storm-jan-2024-277fccfc

Madagascar: Cyclone - Tropical storm - Jan 2024 | Africa (Madagascar official open data) 39 rows - 1 Africa country - 2024 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from Madagascar 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: Madagascar: Cyclone - Tropical storm -… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-madagascar-madagascar-cyclone-tropical-storm-jan-2024-277fccfc.

sourceHugging Facecc-by-sa-4.0updated 29d agoView on Hugging Face
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Dataset Card

Madagascar: Cyclone - Tropical storm - Jan 2024 | Africa (Madagascar official open data)

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

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Madagascar 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

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
MDG3920242024Madagascar

Indicators or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.c340199e-0d49-42d5-a3e4-e2188e1fe3d8:0
country_iso3categoryISO3 country code.MDG
country_namecategoryCountry name.Madagascar
yearInt64Observation year.2024
unnamed_0int64Source column.0
adm0_namestringSource column.Bassas da India
adm1_namestringSource column.---
adm2_namestringSource column.---
pop_60_kmhint64Source column.0
pop_90_kmhint64Source column.0
source_period_start_yearInt64First year inferred from source resource metadata.2024
source_period_end_yearInt64Last year inferred from source resource metadata.2024
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2024
source_providercategoryPublishing organization.WFP Automated Disaster Analysis & Mapping
source_datasetcategorySource package title.Madagascar: Cyclone - Tropical storm - Jan 2024
source_resourcecategorySource resource title.1001040-13-adam-ts-1001040-13-pop-estimation.csv
source_package_idcategoryCKAN package UUID.b2b4c3eb-da43-4e84-a596-28b0b6dd0aa0
source_resource_idcategoryCKAN resource UUID.c340199e-0d49-42d5-a3e4-e2188e1fe3d8
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/b2b4c3eb-da43-4e84-a596-28b0b6dd0aa0/re
license_idcategorySource license identifier.cc-by-sa
retrieved_atcategoryUTC retrieval timestamp.2026-08-30T05:38:32Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-madagascar-madagascar-cyclone-tropical-storm-jan-2024-277fccfc")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
sample_country = df[df["country_iso3"] == "MDG"]

Work with indicators

python
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

bibtex
@misc{electric_sheep_africa_africa_madagascar_madagascar_cyclone_tropical_storm_jan_2024_277fccfc_2024,
  title        = {Madagascar: Cyclone - Tropical storm - Jan 2024 | Africa (Madagascar official open data)},
  author       = {WFP Automated Disaster Analysis & Mapping},
  year         = {2024},
  url          = {https://data.humdata.org/dataset/madagascar-cyclone-1001040},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-madagascar-madagascar-cyclone-tropical-storm-jan-2024-277fccfc}}
}

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 2026-08-30 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/b2b4c3eb-da43-4e84-a596-28b0b6dd0aa0/resource/c340199e-0d49-42d5-a3e4-e2188e1fe3d8/download/1001040-13-adam-ts-1001040-13-pop-estimation.csv