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electricsheepasia/asia-indonesia-dengue-fever-cases-by-province-2015-2017

Indonesia Dengue Fever cases by province, 2015-2017 Publisher: International Federation of Red Cross and Red Crescent Societies (IFRC) · Source: HDX · License: other-pd-nr · Updated: 2024-05-16 Abstract This dataset contains the number of Dengue Fever cases, incidence rape per 100,000 population, people death and case fatality rate (CFR) by province (admin 1), 2015-2017. The data was extracted from the Indonesia Health Profile publications (2015-2017) published… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-indonesia-dengue-fever-cases-by-province-2015-2017.

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Dataset Card

Indonesia Dengue Fever cases by province, 2015-2017

Publisher: International Federation of Red Cross and Red Crescent Societies (IFRC) · Source: HDX · License: other-pd-nr · Updated: 2024-05-16

Abstract

This dataset contains the number of Dengue Fever cases, incidence rape per 100,000 population, people death and case fatality rate (CFR) by province (admin 1), 2015-2017. The data was extracted from the Indonesia Health Profile publications (2015-2017) published by the Ministry of Health. The publication is available in PDF format: http://www.pusdatin.kemkes.go.id/folder/view/01/structure-publikasi-pusdatin-profil-kesehatan.html

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2024-05-16. Geographic scope: IDN.

Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).

Dataset Characteristics

DomainPublic health
Unit of observationFirst-level administrative unit observations
Rows (total)38
Columns17 (14 numeric, 3 categorical, 0 datetime)
Train split30 rows
Test split7 rows
Geographic scopeIDN
PublisherInternational Federation of Red Cross and Red Crescent Societies (IFRC)
HDX last updated2024-05-16

Variables

Geographic — number_of_dengue_fever_cases_incidence_rape_per_100_000_population_people_death_and_case_fatality_rate_cfr_by_province_2015_2017 (range 1.0–34.0).

Identifier / Metadata — unnamed_1 (range 11.0–94.0), unnamed_2 (Provinsi/ Province, Aceh, Sumatera Utara), unnamed_3 (range 66.0–129650.0), unnamed_4 (range 4.63–257.75), unnamed_5 (range 0.0–1071.0) and 11 others.

Quick Start

python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-indonesia-dengue-fever-cases-by-province-2015-2017")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

ColumnTypeNull %Range / Sample Values
number_of_dengue_fever_cases_incidence_rape_per_100_000_population_people_death_and_case_fatality_rate_cfr_by_province_2015_2017float6410.5%1.0 – 34.0 (mean 17.5)
unnamed_1float6410.5%11.0 – 94.0 (mean 47.5588)
unnamed_2object5.3%Provinsi/ Province, Aceh, Sumatera Utara
unnamed_3float647.9%66.0 – 129650.0 (mean 7408.5714)
unnamed_4float647.9%4.63 – 257.75 (mean 55.1089)
unnamed_5float647.9%0.0 – 1071.0 (mean 61.2)
unnamed_6float647.9%0.0 – 7.69 (mean 1.2749)
unnamed_7float647.9%105.0 – 204171.0 (mean 11666.9143)
unnamed_8float647.9%11.75 – 515.9 (mean 89.454)
unnamed_9float647.9%0.0 – 1598.0 (mean 91.3143)
unnamed_10float647.9%0.0 – 5.79 (mean 1.0383)
unnamed_11float647.9%37.0 – 59047.0 (mean 3374.1143)
unnamed_12float647.9%2.87 – 105.95 (mean 26.3066)
unnamed_13float647.9%0.0 – 444.0 (mean 25.3714)
unnamed_14float647.9%0.0 – 2.53 (mean 0.7271)
esa_sourceobject0.0%HDX
esa_processedobject0.0%2026-05-04

Numeric Summary

ColumnMinMaxMeanMedian
number_of_dengue_fever_cases_incidence_rape_per_100_000_population_people_death_and_case_fatality_rate_cfr_by_province_2015_20171.034.017.517.5
unnamed_111.094.047.558851.5
unnamed_366.0129650.07408.57141571.0
unnamed_44.63257.7555.108945.47
unnamed_50.01071.061.215.0
unnamed_60.07.691.27490.83
unnamed_7105.0204171.011666.91432651.0
unnamed_811.75515.989.45464.83
unnamed_90.01598.091.314322.0
unnamed_100.05.791.03830.9
unnamed_1137.059047.03374.1143918.0
unnamed_122.87105.9526.306625.68
unnamed_130.0444.025.37147.0
unnamed_140.02.530.72710.54

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. 14 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

Limitations

  • —Data originates from International Federation of Red Cross and Red Crescent Societies (IFRC) and has not been independently validated by ESA.
  • —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
  • —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

bibtex
@dataset{hdx_asia_indonesia_dengue_fever_cases_by_province_2015_2017,
  title     = {Indonesia Dengue Fever cases by province, 2015-2017},
  author    = {International Federation of Red Cross and Red Crescent Societies (IFRC)},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/indonesia-dengue-fever-cases-by-province-2015-2017},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.