Datasetpublic

electricsheepafrica/africa-chad-cholera-outbreaks-in-central-and-west-africa-2012-regional-dd8dac89

Cholera Outbreaks in Central and West Africa 2012 Regional | Africa (Regional Cholera Platform in West and Central Africa (inactive)) 19 rows - 1 Africa country/area - 2012 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 19 rows from Regional Cholera Platform in West and Central Africa (inactive), covering Cholera Outbreaks in Central and West Africa 2012 Regional. It is published as ML-ready Parquet with consistent Hugging… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-chad-cholera-outbreaks-in-central-and-west-africa-2012-regional-dd8dac89.

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Dataset Card

Cholera Outbreaks in Central and West Africa 2012 Regional | Africa (Regional Cholera Platform in West and Central Africa (inactive))

19 rows - 1 Africa country/area - 2012 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 19 rows from Regional Cholera Platform in West and Central Africa (inactive), covering Cholera Outbreaks in Central and West Africa 2012 Regional. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Health datasets help analysts monitor disease burden, service delivery, population health outcomes, and public-health program performance.

Source-provided context: The number of reported Cholera Cases by country & epi week in Western and Central Africa, in 2012.

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	2012
Last period	2012
Indicators	0
Columns	70
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
`TCD`	19	2012	2012	`Chad`

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.	`aca6aa56-5ecd-4926-9c03-42c3d94ee6ef:2012:0`
`country_iso3`	`dictionary<values=string, indices=int8, ordered=0>`	ISO3 country or area code.	`TCD`
`country_name`	`dictionary<values=string, indices=int8, ordered=0>`	Country or area name.	`Chad`
`source_sheet`	`int64`	Source column from the original resource.	`2012`
`year`	`int64`	Observation year.	`2012`
`iso3`	`string`	Source column from the original resource.	`#country+code`
`country`	`string`	Source column from the original resource.	`#country+name`
`w1`	`double`	Source column from the original resource.	``
`w2`	`double`	Source column from the original resource.	``
`w3`	`double`	Source column from the original resource.	``
`w4`	`double`	Source column from the original resource.	``
`w5`	`double`	Source column from the original resource.	``
`w6`	`double`	Source column from the original resource.	``
`w7`	`double`	Source column from the original resource.	``
`w8`	`double`	Source column from the original resource.	``
`w9`	`double`	Source column from the original resource.	``
`w10`	`double`	Source column from the original resource.	``
`w11`	`double`	Source column from the original resource.	``
`w12`	`double`	Source column from the original resource.	``
`w13`	`double`	Source column from the original resource.	``
`w14`	`double`	Source column from the original resource.	``
`w15`	`double`	Source column from the original resource.	``
`w16`	`double`	Source column from the original resource.	``
`w17`	`double`	Source column from the original resource.	``
`w18`	`double`	Source column from the original resource.	``
`w19`	`double`	Source column from the original resource.	``
`w20`	`double`	Source column from the original resource.	``
`w21`	`double`	Source column from the original resource.	``
`w22`	`double`	Source column from the original resource.	``
`w23`	`double`	Source column from the original resource.	``
`w24`	`double`	Source column from the original resource.	``
`w25`	`double`	Source column from the original resource.	``
`w26`	`double`	Source column from the original resource.	``
`w27`	`double`	Source column from the original resource.	``
`w28`	`double`	Source column from the original resource.	``
`w29`	`double`	Source column from the original resource.	``
`w30`	`double`	Source column from the original resource.	``
`w31`	`double`	Source column from the original resource.	``
`w32`	`double`	Source column from the original resource.	``
`w33`	`double`	Source column from the original resource.	``
`w34`	`double`	Source column from the original resource.	``
`w35`	`double`	Source column from the original resource.	``
`w36`	`double`	Source column from the original resource.	``
`w37`	`double`	Source column from the original resource.	``
`w38`	`double`	Source column from the original resource.	``
`w39`	`double`	Source column from the original resource.	``
`w40`	`double`	Source column from the original resource.	``
`w41`	`double`	Source column from the original resource.	``
`w42`	`double`	Source column from the original resource.	``
`w43`	`double`	Source column from the original resource.	``
`w44`	`double`	Source column from the original resource.	``
`w45`	`double`	Source column from the original resource.	``
`w46`	`double`	Source column from the original resource.	``
`w47`	`double`	Source column from the original resource.	``
`w48`	`string`	Source column from the original resource.	`#affected+date+w48`
`w49`	`string`	Source column from the original resource.	`#affected+date+w49`
`w50`	`string`	Source column from the original resource.	`#affected+date+w50`
`w51`	`string`	Source column from the original resource.	`#affected+date+w51`
`w52`	`string`	Source column from the original resource.	`#affected+date+w52`
`source_period_start_year`	`int64`	Start year inferred from source metadata.	`2012`
`source_period_end_year`	`int64`	End year inferred from source metadata.	`2012`
`source_period_label`	`dictionary<values=string, indices=int8, ordered=0>`	Source column from the original resource.	`2012`
`source_provider`	`dictionary<values=string, indices=int8, ordered=0>`	Publishing organization.	`Regional Cholera Platform in West and Central Africa (inactive)`
`source_dataset`	`dictionary<values=string, indices=int8, ordered=0>`	Source dataset or package title.	`Cholera Outbreaks in Central and West Africa : 2012 Regional Update`
`source_resource`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource title, table name, or file name.	`wca_Cases2012_RegCholeraPlatformWCA.xlsx`
`source_package_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source package identifier.	`97759b41-ba38-4051-954a-f651cb1ad8d4`
`source_resource_id`	`dictionary<values=string, indices=int8, ordered=0>`	Source resource identifier.	`aca6aa56-5ecd-4926-9c03-42c3d94ee6ef`
`source_url`	`dictionary<values=string, indices=int8, ordered=0>`	Original source URL or download URL.	`https://data.humdata.org/dataset/97759b41-ba38-4051-954a-f651cb1ad8d4...`
`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.	`2026-08-10T22:51:43Z`

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-chad-cholera-outbreaks-in-central-and-west-africa-2012-regional-dd8dac89")
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"] == "TCD"]

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

—Source: Regional Cholera Platform in West and Central Africa (inactive)
—Publisher: Regional Cholera Platform in West and Central Africa (inactive)
—Portal: https://data.humdata.org
—Resource: wca_Cases2012_RegCholeraPlatformWCA.xlsx
—License: CC BY 4.0
—Retrieved/generated: 2026-08-11T01:29:22Z
—Hugging Face repo: electricsheepafrica/africa-chad-cholera-outbreaks-in-central-and-west-africa-2012-regional-dd8dac89

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

—Compare health outcomes across geographies
—Track changes over time
—Join with population or facility data
—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

bibtex

@misc{electric_sheep_africa_africa_chad_cholera_outbreaks_in_central_and_west_africa_2012_regional_dd8dac89_2012,
  title        = {Cholera Outbreaks in Central and West Africa 2012 Regional | Africa (Regional Cholera Platform in West and Central Africa (inactive))},
  author       = {Regional Cholera Platform in West and Central Africa (inactive)},
  year         = {2012},
  url          = {https://data.humdata.org/dataset/cholera-outbreaks-in-central-and-west-africa-2012-regional-update},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-chad-cholera-outbreaks-in-central-and-west-africa-2012-regional-dd8dac89}}
}

License

Released under CC BY 4.0.

Original data is published by Regional Cholera Platform in West and Central Africa (inactive). 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 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/cholera-outbreaks-in-central-and-west-africa-2012-regional-update