electricsheepafrica/africa-somalia-2018-tropical-cyclone-sagar-path-47111786

2018 Tropical Cyclone Sagar Path | Africa (IGAD Climate Prediction and Applications Center (ICPAC))

19 rows - 1 Africa country/area - 2018 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 19 rows from IGAD Climate Prediction and Applications Center (ICPAC), covering 2018 Tropical Cyclone Sagar Path. 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: CSV file. This layer shows the movement path of 2018 Tropical Cyclone Sagar. Cyclone Sagar made landfall in north-western Somaliland on 19 May, 2018. It was a very rare cyclone in the Gulf of Aden. The storm moved with wind gusts of up to 120 km/hour that delivered a year’s worth of rain to some areas, that is between 150 and 200mm in some parts of the north.

How To Read This Dataset

• One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	19
Countries/areas	1
First period	2018
Last period	2018
Indicators	0
Columns	45
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SOM	19	2018	2018	Somalia

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	76353f25-af7e-408d-adff-fdb59801bde7:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	SOM
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Somalia
year	int64	Observation year.	2018
fid	string	Source column from the original resource.	a__2018_TC_Sagar0.1
fid_2	int64	Source column from the original resource.	1
the_geom	string	Source column from the original resource.	POINT (48.1 13)
basin	string	Source column from the original resource.	IO
cy	int64	Source column from the original resource.	1
yyyymmddhh	int64	Source column from the original resource.	2018051712
tech	string	Source column from the original resource.	BEST
tau	int64	Source column from the original resource.	0
lat	double	Source column from the original resource.	13.0
long	double	Source column from the original resource.	48.1
vmax	int64	Source column from the original resource.	50
mslp	int64	Source column from the original resource.	985
ty	string	Source column from the original resource.	TS
rad	int64	Source column from the original resource.	0
windcode	string	Source column from the original resource.	NEQ
rad1	int64	Source column from the original resource.	45
rad2	int64	Source column from the original resource.	40
rad3	int64	Source column from the original resource.	50
rad4	int64	Source column from the original resource.	75
radp	int64	Source column from the original resource.	1007
rrp	int64	Source column from the original resource.	150
mrd	int64	Source column from the original resource.	25
gusts	int64	Source column from the original resource.	0
eye	int64	Source column from the original resource.	0
subregn	string	Source column from the original resource.	A
maxseas	int64	Source column from the original resource.	0
dir	int64	Source column from the original resource.	0
speed	int64	Source column from the original resource.	0
stormname	string	Source column from the original resource.	SAGAR
depth	string	Source column from the original resource.	M
source_period_start_year	int64	Start year inferred from source metadata.	2018
source_period_end_year	int64	End year inferred from source metadata.	2018
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2018
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	IGAD Climate Prediction and Applications Center (ICPAC)
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	2018 Tropical Cyclone Sagar Path
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	2018 Tropical Cyclone Sagar Path CSV
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	f40c6491-187c-4016-9f1a-719ef37cd416
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	76353f25-af7e-408d-adff-fdb59801bde7
source_url	dictionary<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_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T14:51:11Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-somalia-2018-tropical-cyclone-sagar-path-47111786")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

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

Time-Series Pattern

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

Pivot For Analysis

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

• Source: IGAD Climate Prediction and Applications Center (ICPAC)
• Publisher: IGAD Climate Prediction and Applications Center (ICPAC)
• Portal: https://data.humdata.org
• Resource: 2018 Tropical Cyclone Sagar Path CSV
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T14:51:17Z
• Hugging Face repo: electricsheepafrica/africa-somalia-2018-tropical-cyclone-sagar-path-47111786

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
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_somalia_2018_tropical_cyclone_sagar_path_47111786_2018,
  title        = {2018 Tropical Cyclone Sagar Path | Africa (IGAD Climate Prediction and Applications Center (ICPAC))},
  author       = {IGAD Climate Prediction and Applications Center (ICPAC)},
  year         = {2018},
  url          = {https://data.humdata.org/dataset/icpac-geonode-2018-tropical-cyclone-sagar-path},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-somalia-2018-tropical-cyclone-sagar-path-47111786}}
}

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.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/icpac-geonode-2018-tropical-cyclone-sagar-path