CoolFace
Datasetpublic

electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters

Kenya - Tally of Internaly displaced persons resulting from natural disasters | Africa (original) Size category: 1K<n<10K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa TL;DR This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context. What This Dataset Covers Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters.

sourceHugging Faceotherupdated 2mo agoView on Hugging Face
0likes12downloads
Dataset Card

Kenya - Tally of Internaly displaced persons resulting from natural disasters | Africa (original)

Size category: 1K<n<10K - Formats: parquet - Sector: health - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Health datasets help researchers examine disease burden, service delivery, risk factors, outcomes, and public-health program performance.

Dataset context from the existing Hugging Face card: Kenya - Tally of Internaly displaced persons resulting from natural disasters Publisher: Kenya Open Data Initiative (inactive) · Source: HDX · License: other-pd-nr · Updated: 2023-03-03 Abstract This data-set shows the Number of people affected by Disasters in Kenya. It is based on the National Disaster inventory which is a record of Natural Disasters including floods, thunderstorms, forest fires, mudslides and disease outbreaks. Each row in this dataset represents… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters.

Dataset Profile

FieldValue
Hugging Face repo`electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters`
Sectorhealth
Topic tagshumanitarian, hdx, electric-sheep-africa, affected-population, geodata, governance-and-civil-society, natural-disasters, ken
Modalitiestabular, text
Formatsparquet
Size category1K<n<10K
CountriesKenya
ISO3 coverageKEN
Last modified on HF2026-04-15 02:02:14+00:00
Inventory snapshot2026-07-16T16:00:34Z

How To Read This Dataset

  • —Start from the repository files and the dataset viewer when available.
  • —Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • —Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • —Preserve missing values until you have a defensible imputation rule.

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

python
from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • —This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • —Exact schema, row counts, and source files should be inspected in the repository data files.
  • —Metadata gaps from the inventory: upstream_publisher.
  • —Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • —Inspect schema and missingness before modeling.
  • —Profile variables by geography, time, and subgroup columns where present.
  • —Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • —Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

bibtex
@misc{electric_sheep_africa_africa_1999_2013_tally_of_internaly_displaced_persons_resulting_from_natural_dis_2026,
  title        = {Kenya - Tally of Internaly displaced persons resulting from natural disasters | Africa (original)},
  author       = {original},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-1999-2013-tally-of-internaly-displaced-persons-resulting-from-natural-disasters}}
}

License

Released under Source-specific or other license.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

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


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.