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electricsheepafrica/africa-uganda-construction-sector-indices-excel-tables-march-2022-12aed319

Construction Sector Indices Excel Tables March 2022 | Africa (Uganda Bureau of Statistics) 58 rows - 1 Africa country/area - 2022 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 58 rows from Uganda Bureau of Statistics, covering Construction Sector Indices Excel Tables March 2022. 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-construction-sector-indices-excel-tables-march-2022-12aed319.

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Construction Sector Indices Excel Tables March 2022 | Africa (Uganda Bureau of Statistics)

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

rows countries period indicators license

TL;DR

This dataset contains 58 rows from Uganda Bureau of Statistics, covering Construction Sector Indices Excel Tables March 2022. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Construction Sector Indices Excel Tables March 2022 - Last Updated on 25th 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: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows58
Countries/areas1
First period2022
Last period2022
Indicators0
Columns64
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
UGA5820222022Uganda

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-978f1760b3277a:csi-indices:0
country_iso3stringISO3 country or area code.UGA
country_namestringCountry or area name.Uganda
source_sheetstringSource column from the original resource.CSI Indices
yearint64Observation year.2022
q1stringSource column from the original resource.Q2
d_243_63275134059154doubleSource column from the original resource.246.47254414550144
d_249_2244553761027doubleSource column from the original resource.0.0
d_240_36553916574974doubleSource column from the original resource.243.02193418035415
d_244_99126403349433doubleSource column from the original resource.0.0
d_219_25000989964028doubleSource column from the original resource.221.85633901214385
d_224_4264319195353doubleSource column from the original resource.0.0
d_253_23997862008108doubleSource column from the original resource.256.8161484439817
d_257_99778011270456doubleSource column from the original resource.0.0
d_185_72187935646159doubleSource column from the original resource.187.50892777726423
d_191_01472715782788doubleSource column from the original resource.0.0
q1_2stringSource column from the original resource.Q2
d_283_0209600412681doubleSource column from the original resource.286.0949937236408
d_295_31709477075907doubleSource column from the original resource.0.0
d_209_95737070409845doubleSource column from the original resource.209.95737070409845
d_210_25610287103493doubleSource column from the original resource.0.0
d_167_71108675968273doubleSource column from the original resource.167.71108675968273
d_161_65028296922446doubleSource column from the original resource.0.0
d_142_51859184819475doubleSource column from the original resource.142.42880765003764
d_151_55177146899936doubleSource column from the original resource.0.0
d_257_7160142108533doubleSource column from the original resource.257.7160142108533
d_262_7173335230946doubleSource column from the original resource.0.0
q1_3stringSource column from the original resource.Q2
d_186_7960465813536doubleSource column from the original resource.188.49619514268136
d_189_67214238988802doubleSource column from the original resource.0.0
d_152_09093647698387doubleSource column from the original resource.152.09093647698387
d_153_68799683491648doubleSource column from the original resource.0.0
d_235_8854651306639doubleSource column from the original resource.235.9356704385767
d_229_00257230042038doubleSource column from the original resource.0.0
d_208_64972799689826doubleSource column from the original resource.217.52383608947235
d_254_44237359578588doubleSource column from the original resource.0.0
d_154_1012797776099doubleSource column from the original resource.153.6775031056858
d_154_02388772957062doubleSource column from the original resource.0.0
source_period_start_yearint64Start year inferred from source metadata.2022
source_period_end_yearint64End year inferred from source metadata.2022
source_period_labelstringSource column from the original resource.2022
source_providerstringPublishing organization.Uganda Bureau of Statistics
source_datasetstringSource dataset or package title.Construction Sector Indices Excel Tables March 2022
source_resourcestringSource resource title, table name, or file name.Construction Sector Indices Excel Tables March 2022
source_package_idstringSource package identifier.construction-sector-indices-excel-tables-march-2022-ubos-stat-978f176...
source_resource_idstringSource resource identifier.ubos-stat-978f1760b3277a
source_urlstringOriginal source URL or download URL.https://www.ubos.org/wp-content/uploads/statistics/Construction_Secto...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-21T21:37:51Z
sectorstringSource column from the original resource.``
weightsdoubleSource column from the original resource.``
2021doubleSource column from the original resource.``
2021_2doubleSource column from the original resource.``
2021_3doubleSource column from the original resource.``
2021_4doubleSource column from the original resource.``
2021_5doubleSource column from the original resource.``
2021_6doubleSource column from the original resource.``
2021_7doubleSource column from the original resource.``
2021_8doubleSource column from the original resource.``
2021_9doubleSource column from the original resource.``
2021_10doubleSource column from the original resource.``
2022doubleSource column from the original resource.``
2022_2doubleSource column from the original resource.``
2022_3doubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-uganda-construction-sector-indices-excel-tables-march-2022-12aed319")
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

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —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_construction_sector_indices_excel_tables_march_2022_12aed319_2022,
  title        = {Construction Sector Indices Excel Tables March 2022 | 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-construction-sector-indices-excel-tables-march-2022-12aed319}}
}

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/