CoolFace
Datasetpublic

electricsheepafrica/africa-mauritius-gfcf-in-the-manufacturing-sector-buildings-and-other-const-d0461e0b

Gfcf in the Manufacturing Sector Buildings and Other Const | Africa (MDPA) 51 rows - 1 Africa country/area - 2006-2022 - 1 indicator - Engineered by Electric Sheep Africa TL;DR This dataset contains 51 rows from MDPA, covering Gfcf in the Manufacturing Sector Buildings and Other Const. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-gfcf-in-the-manufacturing-sector-buildings-and-other-const-d0461e0b.

sourceHugging Facecc-by-4.0updated 2mo agoView on Hugging Face
0likes19downloads
Dataset Card

Gfcf in the Manufacturing Sector Buildings and Other Const | Africa (MDPA)

51 rows - 1 Africa country/area - 2006-2022 - 1 indicator - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 51 rows from MDPA, covering Gfcf in the Manufacturing Sector Buildings and Other Const. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

Source-provided context: Dataset shows GFCF in the manufacturing sector - Buildings and other Construction Works, 2006 - 2022

How To Read This Dataset

  • —One row means: one indicator observation for one geography, time period, and optional source dimensions.
  • —Primary geography column: country_iso3.
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3, year, indicator_id.

Coverage

DimensionValue
Rows51
Countries/areas1
First period2006
Last period2022
Indicators1
Columns19
Source formatCSV

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU5120062022Mauritius

Indicators, Variables, Or Resource Contents

  • —gfcf-in-the-manufacturing-sector-buildings-and-other-construction-works-d0461e0b - GFCF in the manufacturing sector - Buildings and other Construction Works, 2006 - 2022(sourceunitsunspecified)

Schema

ColumnTypeDescriptionExample
indicator_idstringStable source or Electric Sheep Africa indicator identifier.gfcf-in-the-manufacturing-sector-buildings-and-other-construction-wor...
indicator_namestringHuman-readable indicator name.GFCF in the manufacturing sector - Buildings and other Construction W...
country_iso3stringISO3 country or area code.MU
country_namestringCountry or area name.Mauritius
yearint64Observation year.2006
valuedoubleNumeric observation value.5.0
unitstringMeasurement unit, when supplied by the source.source_units_unspecified
dimension_yearstringSource dimension retained during long-form normalization.SUGAR
source_period_start_yearint64Start year inferred from source metadata.2006
source_period_end_yearint64End year inferred from source metadata.2022
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2006-2022
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.GFCF in the manufacturing sector - Buildings and other Construction W...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.CSV File
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.104e4663-cbfa-4e57-b7c3-516cbb9c30b2
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.f38cc585-ec6c-4664-bfff-40f6d7a26db4
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/104e4663-cbfa-4e57-b7c3-516cbb9c30b2/r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-08T16:26:20Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-gfcf-in-the-manufacturing-sector-buildings-and-other-const-d0461e0b")
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"] == "MU"]

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

  • —Build time-series dashboards
  • —Compare economic indicators
  • —Join with population or sector data
  • —Build time-series views and period-over-period comparisons
  • —Pivot to geography x period or indicator x period matrices
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_mauritius_gfcf_in_the_manufacturing_sector_buildings_and_other_const_d046_2022,
  title        = {Gfcf in the Manufacturing Sector Buildings and Other Const | Africa (MDPA)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/gfcf-in-the-manufacturing-sector-buildings-and-other-construction-works-2006-2022},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-gfcf-in-the-manufacturing-sector-buildings-and-other-const-d0461e0b}}
}

License

Released under CC BY 4.0.

Original data is published by MDPA. 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.govmu.org/dataset/gfcf-in-the-manufacturing-sector-buildings-and-other-construction-works-2006-2022