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electricsheepafrica/africa-uganda-proportion-of-the-poor-persons-before-and-during-covid19-323f391e

Proportion of the Poor Persons Before and During Covid19 | Africa (Uganda Bureau of Statistics) 15 rows - 1 Africa country/area - 2021 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 15 rows from Uganda Bureau of Statistics, covering Proportion of the Poor Persons Before and During Covid19. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-uganda-proportion-of-the-poor-persons-before-and-during-covid19-323f391e.

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Proportion of the Poor Persons Before and During Covid19 | Africa (Uganda Bureau of Statistics)

15 rows - 1 Africa country/area - 2021 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 15 rows from Uganda Bureau of Statistics, covering Proportion of the Poor Persons Before and During Covid19. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.

Source-provided context: Proportion of the poor persons before and during COVID19 (%) - Last Updated on 12th August 2021

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

DimensionValue
Rows15
Countries/areas1
First period2021
Last period2021
Indicators0
Columns19
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
UGA1520212021Uganda

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-cab3d09defdf61:sheet1:0
country_iso3stringISO3 country or area code.UGA
country_namestringCountry or area name.Uganda
source_sheetstringSource column from the original resource.Sheet1
yearint64Observation year.2021
regionsstringSource column from the original resource.Acholi
before_20th_march_before_covid_19doubleSource column from the original resource.68.0
during_covid_19_after_lock_downdoubleSource column from the original resource.67.4
source_period_start_yearint64Start year inferred from source metadata.2021
source_period_end_yearint64End year inferred from source metadata.2021
source_period_labelstringSource column from the original resource.2021
source_providerstringPublishing organization.Uganda Bureau of Statistics
source_datasetstringSource dataset or package title.Proportion of the poor persons before and during COVID19 (%)
source_resourcestringSource resource title, table name, or file name.Proportion of the poor persons before and during COVID19 (%)
source_package_idstringSource package identifier.proportion-of-the-poor-persons-before-and-during-covid19-ubos-stat-ca...
source_resource_idstringSource resource identifier.ubos-stat-cab3d09defdf61
source_urlstringOriginal source URL or download URL.https://www.ubos.org/wp-content/uploads/statistics/Proportion_of_the_...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-21T22:20:38Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-uganda-proportion-of-the-poor-persons-before-and-during-covid19-323f391e")
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

  • —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

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

  • —Track mobility over time
  • —Compare routes or geographies
  • —Join with economic and population 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_uganda_proportion_of_the_poor_persons_before_and_during_covid19_323f391e_2021,
  title        = {Proportion of the Poor Persons Before and During Covid19 | Africa (Uganda Bureau of Statistics)},
  author       = {Uganda Bureau of Statistics},
  year         = {2021},
  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-proportion-of-the-poor-persons-before-and-during-covid19-323f391e}}
}

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/