Datasets:
disease_name stringclasses 8
values | 2009 int64 387k 9.83M | 2010 int64 419k 11.4M | 2011 int64 375k 11.2M | 2012 int64 358k 12.2M | 2013 int64 350k 14.8M | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-07 00:00:00 2026-04-07 00:00:00 |
|---|---|---|---|---|---|---|---|
Urinary Tract Infections | 507,910 | 638,758 | 778,433 | 912,646 | 1,091,371 | HDX | 2026-04-07 |
Diarrhoea Diseases | 1,639,945 | 1,818,078 | 2,024,812 | 2,081,487 | 2,226,107 | HDX | 2026-04-07 |
All Other Diseases | 6,755,308 | 8,441,917 | 6,701,348 | 7,781,869 | 8,618,536 | HDX | 2026-04-07 |
Pneumonia | 1,018,151 | 1,081,317 | 1,100,997 | 1,135,046 | 1,282,996 | HDX | 2026-04-07 |
Diseases of the Skin (Incl. Ulcers) | 2,109,416 | 2,718,570 | 2,882,050 | 3,051,026 | 3,648,361 | HDX | 2026-04-07 |
Malaria | 9,833,701 | 11,371,889 | 11,150,223 | 9,445,107 | 8,808,471 | HDX | 2026-04-07 |
Disease of the Respiratory System | 8,017,565 | 9,760,371 | 11,098,928 | 12,215,993 | 14,823,864 | HDX | 2026-04-07 |
Intestinal Worms | 387,066 | 419,298 | 374,886 | 357,844 | 349,632 | HDX | 2026-04-07 |
National Top 10 Incidences of Diseases: 2009 to 2013
Publisher: Kenya National Bureau of Statistics (inactive) · Source: HDX · License: other-pd-nr · Updated: 2025-02-06
Abstract
This dataset shows the National Top 10 Incidences of Diseases in kenya for the period of : 2009 to 2013 as reported by the Kenya National Bureau of statistics
Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-02-06. Geographic scope: KEN.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Public health |
| Unit of observation | Tabular records |
| Rows (total) | 11 |
| Columns | 8 (5 numeric, 3 categorical, 0 datetime) |
| Train split | 8 rows |
| Test split | 2 rows |
| Geographic scope | KEN |
| Publisher | Kenya National Bureau of Statistics (inactive) |
| HDX last updated | 2025-02-06 |
Variables
Identifier / Metadata — disease_name (Accidents (incl. fractures, burns etc), All Other Diseases, Diarrhoea Diseases), esa_source (HDX), esa_processed (2026-04-07).
Other — 2009 (range 387066.0–9833701.0), 2010 (range 419298.0–11371889.0), 2011 (range 374886.0–11150223.0), 2012 (range 357844.0–12215993.0), 2013 (range 349632.0–14823864.0).
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-national-top-10-incidences-of-diseases-2009-to-2013")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
disease_name |
object | 0.0% | Accidents (incl. fractures, burns etc), All Other Diseases, Diarrhoea Diseases |
2009 |
int64 | 0.0% | 387066.0 – 9833701.0 (mean 2905534.2727) |
2010 |
int64 | 0.0% | 419298.0 – 11371889.0 (mean 3478372.4545) |
2011 |
int64 | 0.0% | 374886.0 – 11150223.0 (mean 3484770.6364) |
2012 |
int64 | 0.0% | 357844.0 – 12215993.0 (mean 3580971.3636) |
2013 |
int64 | 0.0% | 349632.0 – 14823864.0 (mean 3966956.0909) |
esa_source |
object | 0.0% | HDX |
esa_processed |
object | 0.0% | 2026-04-07 |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
2009 |
387066.0 | 9833701.0 | 2905534.2727 | 1018151.0 |
2010 |
419298.0 | 11371889.0 | 3478372.4545 | 1081317.0 |
2011 |
374886.0 | 11150223.0 | 3484770.6364 | 1100997.0 |
2012 |
357844.0 | 12215993.0 | 3580971.3636 | 1135046.0 |
2013 |
349632.0 | 14823864.0 | 3966956.0909 | 1282996.0 |
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. 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 Kenya National Bureau of Statistics (inactive) 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
@dataset{hdx_africa_national_top_10_incidences_of_diseases_2009_to_2013,
title = {National Top 10 Incidences of Diseases: 2009 to 2013},
author = {Kenya National Bureau of Statistics (inactive)},
year = {2025},
url = {https://data.humdata.org/dataset/national-top-10-incidences-of-diseases-2009-to-2013},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.
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