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electricsheepafrica/africa-somalia-somalia-districts-hit-by-2015-tropical-cyclone-chapala-a94005b3

Somalia Districts Hit by 2015 Tropical Cyclone Chapala | Africa (IGAD Climate Prediction and Applications Center (ICPAC)) 6 rows - 1 Africa country/area - 2017 - 6 indicators - Engineered by Electric Sheep Africa TL;DR This dataset contains 6 rows from IGAD Climate Prediction and Applications Center (ICPAC), covering Somalia Districts Hit by 2015 Tropical Cyclone Chapala. It is published as ML-ready Parquet with consistent Hugging Face metadata, source… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-somalia-somalia-districts-hit-by-2015-tropical-cyclone-chapala-a94005b3.

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Dataset Card

Somalia Districts Hit by 2015 Tropical Cyclone Chapala | Africa (IGAD Climate Prediction and Applications Center (ICPAC))

6 rows - 1 Africa country/area - 2017 - 6 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 6 rows from IGAD Climate Prediction and Applications Center (ICPAC), covering Somalia Districts Hit by 2015 Tropical Cyclone Chapala. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Excel file. This layer show two Somalia Districts struck by 2015 Tropical Cyclone Chapala, Berbera and Bossaso Districts. On November 2, 2015 TC Chapala entered the Gulf of Aden in Somalia as the strongest tropical cyclone on record. 2015 TC Chapala prduced maximum wind speeds of 130knots. It brought rainfall in Northern Bari Region in Bossaso Districts. The villages struck within the recorded districts include, Baargaal, Bander, Bareeda, Butiyaal, Caluula, Murcanyo, Qandalla, Xaabo, Biycad, Bulahar, Ceelsheik, Shacable, Xaafun.

How To Read This Dataset

  • —One row means: one indicator observation for one geography, time period, and optional source dimensions.
  • —Primary geography column: country_iso3.
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3, year, indicator_id.

Coverage

DimensionValue
Rows6
Countries/areas1
First period2017
Last period2017
Indicators6
Columns36
Source formatXLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
SOM620172017Somalia

Indicators, Variables, Or Resource Contents

  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-fid-2-a7f8596e - Somalia Districts hit by 2015 Tropical Cyclone Chapala - fid 2(sourceunitsunspecified)
  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-objectid-1-7ca0b41d - Somalia Districts hit by 2015 Tropical Cyclone Chapala - objectid 1(sourceunitsunspecified)
  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-shape-leng-082b8b8e - Somalia Districts hit by 2015 Tropical Cyclone Chapala - shape leng(sourceunitsunspecified)
  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-shape-area-3239c894 - Somalia Districts hit by 2015 Tropical Cyclone Chapala - shape area(sourceunitsunspecified)
  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-objectid-2-f1db243d - Somalia Districts hit by 2015 Tropical Cyclone Chapala - objectid 2(sourceunitsunspecified)
  • —somalia-districts-hit-by-2015-tropical-cyclone-chapala-d-2015chapa-83b4eb7c - Somalia Districts hit by 2015 Tropical Cyclone Chapala - d 2015chapa(sourceunitsunspecified)

Schema

ColumnTypeDescriptionExample
indicator_idstringStable source or Electric Sheep Africa indicator identifier.somalia-districts-hit-by-2015-tropical-cyclone-chapala-fid-2-a7f8596e
indicator_namestringHuman-readable indicator name.Somalia Districts hit by 2015 Tropical Cyclone Chapala - fid 2
country_iso3stringISO3 country or area code.SOM
source_sheetstringSource column from the original resource.a__2015_TCChapal
country_namestringCountry or area name.Somalia
yearint64Observation year.2017
valuedoubleNumeric observation value.1.0
unitstringMeasurement unit, when supplied by the source.source_units_unspecified
dimension_fidstringSource dimension retained during long-form normalization.a__2015_TCChapal.1
dimension_the_geomstringSource dimension retained during long-form normalization.MULTIPOLYGON (((45.862251282000045 10.819958687000053, 45.86577606200...
dimension_admin2namestringSource dimension retained during long-form normalization.Berbera
dimension_admin2pcodstringSource dimension retained during long-form normalization.SO1202
dimension_admin2refnstringSource dimension retained during long-form normalization.Berbera
dimension_admin2altnstringSource dimension retained during long-form normalization.``
dimension_admin1namestringSource dimension retained during long-form normalization.Woqooyi Galbeed
dimension_admin1pcodstringSource dimension retained during long-form normalization.SO12
dimension_admin0namestringSource dimension retained during long-form normalization.Somalia
dimension_admin0pcodstringSource dimension retained during long-form normalization.SO
dimension_datestringSource dimension retained during long-form normalization.2014-06-06 00:00:00
dimension_adm1pcodestringSource dimension retained during long-form normalization.SO12
dimension_adm1_namestringSource dimension retained during long-form normalization.Woqooyi Galbeed
dimension_admin2pc_1stringSource dimension retained during long-form normalization.SO1202
dimension_adm2_namestringSource dimension retained during long-form normalization.Berbera
dimension_adm2_ochastringSource dimension retained during long-form normalization.Berbera
dimension_adm2_finstringSource dimension retained during long-form normalization.Berbera
source_period_start_yearint64Start year inferred from source metadata.2015
source_period_end_yearint64End year inferred from source metadata.2015
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2015
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.IGAD Climate Prediction and Applications Center (ICPAC)
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Somalia Districts hit by 2015 Tropical Cyclone Chapala
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Somalia Districts hit by 2015 Tropical Cyclone Chapala Excel
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.6aa6b58a-2426-47dc-bc6f-96a3b6b1f5e0
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.82d47210-c44a-411d-9042-011778857205
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://geoportal.icpac.net/geoserver/ows?service=WFS&version=1.0.0&r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-10T14:51:11Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-somalia-somalia-districts-hit-by-2015-tropical-cyclone-chapala-a94005b3")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "SOM"]

Time-Series Pattern

python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

  • —Canonical time field: year.
  • —Missing values are preserved rather than silently imputed.
  • —Column names are standardized for machine use; source meanings are preserved where known.
  • —Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

Transformations Applied

  • —Converted the source table to Parquet for efficient analytics and ML workflows.
  • —Added or preserved source provenance columns where available.
  • —Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
  • —Preserved source-reported values without analytical imputation.

Suggested Analyses

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —Build time-series views and period-over-period comparisons
  • —Pivot to geography x period or indicator x period matrices
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_somalia_somalia_districts_hit_by_2015_tropical_cyclone_chapala_a94005b3_2017,
  title        = {Somalia Districts Hit by 2015 Tropical Cyclone Chapala | Africa (IGAD Climate Prediction and Applications Center (ICPAC))},
  author       = {IGAD Climate Prediction and Applications Center (ICPAC)},
  year         = {2017},
  url          = {https://data.humdata.org/dataset/icpac-geonode-somalia-districts-hit-by-2015-tropical-cyclone-chapala},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-somalia-somalia-districts-hit-by-2015-tropical-cyclone-chapala-a94005b3}}
}

License

Released under CC BY 4.0.

Original data is published by IGAD Climate Prediction and Applications Center (ICPAC). Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/icpac-geonode-somalia-districts-hit-by-2015-tropical-cyclone-chapala