electricsheepafrica/africa-mauritius-shopping-mall-05d760c8
Shopping Mall | Africa (MDPA) 30 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 30 rows from MDPA, covering Shopping Mall. 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-shopping-mall-05d760c8.
Shopping Mall | Africa (MDPA)
30 rows - 1 Africa country/area - detected - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
TL;DR
This dataset contains 30 rows from MDPA, covering Shopping Mall. 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: List of shopping malls over the island. Their respective website is also uploaded.
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:
source_period_start_year. - Time coverage basis: sourceperiodstart_year.
- Recommended join keys:
country_iso3where available plus source-specific keys.
Coverage
Geographic Coverage
Top areas shown below, sorted by row count when available:
Indicators, Variables, Or Resource Contents
- This repo preserves one source tabular resource with its usable columns kept together.
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mauritius-shopping-mall-05d760c8")
df = ds["train"].to_pandas()
print(df.head())Inspect Columns
print(df.info())
print(df.head())Filter By Geography
if "country_iso3" in df.columns:
sample = df[df["country_iso3"] == "MU"]Time-Series Pattern
if "value" in df.columns and "source_period_start_year" in df.columns:
trend = df.sort_values("source_period_start_year")Pivot For Analysis
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:
source_period_start_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: MDPA
- Publisher: MDPA
- Portal: https://data.govmu.org
- Resource: shoppingmall.csv
- License: CC BY-SA 4.0
- Retrieved/generated:
2026-08-08T17:15:05Z - Hugging Face repo: electricsheepafrica/africa-mauritius-shopping-mall-05d760c8
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
- Check missingness before modeling
- Use
country_iso3as the safest geography join key when present
Citation
@misc{electric_sheep_africa_africa_mauritius_shopping_mall_05d760c8_2026,
title = {Shopping Mall | Africa (MDPA)},
author = {MDPA},
year = {2026},
url = {https://data.govmu.org/dataset/shopping-mall},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-shopping-mall-05d760c8}}
}License
Released under CC BY-SA 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/shopping-mall
