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electricsheepafrica/africa-uganda-selected-health-sector-performance-indicators-2016-17-2019-7da59f4a

Selected Health Sector Performance Indicators 2016 17 2019 | Africa (Uganda Bureau of Statistics) 410 rows - 1 Africa country/area - 2016-2022 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 410 rows from Uganda Bureau of Statistics, covering Selected Health Sector Performance Indicators 2016 17 2019. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-uganda-selected-health-sector-performance-indicators-2016-17-2019-7da59f4a.

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Selected Health Sector Performance Indicators 2016 17 2019 | Africa (Uganda Bureau of Statistics)

410 rows - 1 Africa country/area - 2016-2022 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 410 rows from Uganda Bureau of Statistics, covering Selected Health Sector Performance Indicators 2016 17 2019. 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: Selected health sector performance indicators, 2016/17- 2019/20 - Last Updated on 26th April 2022

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: not detected.
  • —Time coverage basis: source metadata.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows410
Countries/areas1
First period2016
Last period2022
Indicators0
Columns52
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
UGA41020162022Uganda

Indicators, Variables, Or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.ubos-stat-c6743e2e9951c2:sheet1:0
country_iso3stringISO3 country or area code.UGA
country_namestringCountry or area name.Uganda
source_sheetstringSource column from the original resource.Sheet1
mulago_sw_national_hospitalstringSource column from the original resource.Kiruddu National Referral Hospital
columnstringSource column from the original resource.-
column_2doubleSource column from the original resource.``
column_3doubleSource column from the original resource.``
column_4doubleSource column from the original resource.``
column_5stringSource column from the original resource.-
column_6stringSource column from the original resource.-
d_887doubleSource column from the original resource.829.0
d_299doubleSource column from the original resource.244.0
d_34doubleSource column from the original resource.29.0
source_period_start_yearint64Start year inferred from source metadata.2016
source_period_end_yearint64End year inferred from source metadata.2022
source_period_labelstringSource column from the original resource.2016-2022
source_providerstringPublishing organization.Uganda Bureau of Statistics
source_datasetstringSource dataset or package title.Selected health sector performance indicators, 2016/17- 2019/20
source_resourcestringSource resource title, table name, or file name.Selected health sector performance indicators, 2016/17- 2019/20
source_package_idstringSource package identifier.selected-health-sector-performance-indicators-2016-17-2019-20-ubos-st...
source_resource_idstringSource resource identifier.ubos-stat-c6743e2e9951c2
source_urlstringOriginal source URL or download URL.https://www.ubos.org/wp-content/uploads/statistics/Selected_health_se...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-21T21:37:51Z
kassandastringSource column from the original resource.``
d_10_2doubleSource column from the original resource.``
d_12doubleSource column from the original resource.``
d_61_1doubleSource column from the original resource.``
d_67_8doubleSource column from the original resource.``
column_9doubleSource column from the original resource.``
d_64doubleSource column from the original resource.``
d_32_3doubleSource column from the original resource.``
d_34_7doubleSource column from the original resource.``
kapelebyongstringSource column from the original resource.``
d_6_8doubleSource column from the original resource.``
d_5doubleSource column from the original resource.``
d_82_1doubleSource column from the original resource.``
d_86_7doubleSource column from the original resource.``
d_67doubleSource column from the original resource.``
d_29_8doubleSource column from the original resource.``
d_26_9doubleSource column from the original resource.``
d_28doubleSource column from the original resource.``
nabilatukstringSource column from the original resource.``
d_8_8doubleSource column from the original resource.``
d_9doubleSource column from the original resource.``
d_69_9doubleSource column from the original resource.``
d_73_6doubleSource column from the original resource.``
d_62doubleSource column from the original resource.``
d_53_4doubleSource column from the original resource.``
d_61_5doubleSource column from the original resource.``
d_43doubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-uganda-selected-health-sector-performance-indicators-2016-17-2019-7da59f4a")
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"] == "UGA"]

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

  • —No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
  • —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

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

Citation

bibtex
@misc{electric_sheep_africa_africa_uganda_selected_health_sector_performance_indicators_2016_17_2019_7da59f4_2022,
  title        = {Selected Health Sector Performance Indicators 2016 17 2019 | Africa (Uganda Bureau of Statistics)},
  author       = {Uganda Bureau of Statistics},
  year         = {2022},
  url          = {https://www.ubos.org/explore-statistics/0/},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-uganda-selected-health-sector-performance-indicators-2016-17-2019-7da59f4a}}
}

License

Released under other-open.

Original data is published by Uganda Bureau of Statistics. 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 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://www.ubos.org/explore-statistics/0/