electricsheepafrica/africa-mauritius-area-harvested-production-yield-and-interline-of-food-crop-1cfd7212

Area Harvested Production Yield and Interline of Food Crop | Africa (MDPA)

47 rows - 1 Africa country/area - 2023 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 47 rows from MDPA, covering Area Harvested Production Yield and Interline of Food Crop. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Agriculture datasets help analysts examine production, prices, inputs, land use, food systems, and rural economic activity.

Source-provided context: Production of Fruits and Vegetables by Area Harvested and Amount Yield in Mauritius for the Year 2023

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

Dimension	Value
Rows	47
Countries/areas	1
First period	2023
Last period	2023
Indicators	0
Columns	37
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	47	2023	2023	Mauritius

Indicators, Variables, Or Resource Contents

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

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	60af4c08-3190-497b-a8a7-85a0f515f5e6:table-28:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	MU
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Mauritius
source_sheet	string	Source column from the original resource.	Table 28
year	int64	Observation year.	2023
bittergourd	string	Source column from the original resource.	Brinjal
d_185	double	Source column from the original resource.	277.0
d_1778	double	Source column from the original resource.	3387.0
d_9_6	double	Source column from the original resource.	12.2
d_189_8	double	Source column from the original resource.	289.8
d_1664	double	Source column from the original resource.	3496.0
d_8_8	double	Source column from the original resource.	12.1
d_216	double	Source column from the original resource.	291.9
1977	double	Source column from the original resource.	3093.0
d_9_2	double	Source column from the original resource.	10.6
d_210_8	double	Source column from the original resource.	278.7
d_1540	double	Source column from the original resource.	3165.0
d_7_3	double	Source column from the original resource.	11.4
d_214_2	double	Source column from the original resource.	360.4
d_1652	double	Source column from the original resource.	4769.0
d_7_7	double	Source column from the original resource.	13.2
column	double	Source column from the original resource.	1.3
d_0_5	double	Source column from the original resource.	90.5
d_10_7	double	Source column from the original resource.	69.5
d_214_3	double	Source column from the original resource.	361.7
d_1653	double	Source column from the original resource.	4860.0
source_period_start_year	int64	Start year inferred from source metadata.	2023
source_period_end_year	int64	End year inferred from source metadata.	2023
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2023
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	MDPA
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Area Harvested, Production, Yield and Interline of Food Crops for Mau...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source File 2023.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	418af393-03a3-49ba-9a28-835f8476f4a8
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	60af4c08-3190-497b-a8a7-85a0f515f5e6
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/418af393-03a3-49ba-9a28-835f8476f4a8/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-08T16:26:20Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-area-harvested-production-yield-and-interline-of-food-crop-1cfd7212")
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 "year" in df.columns:
    trend = df.sort_values("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: 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: Source File 2023.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-08T16:56:00Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-area-harvested-production-yield-and-interline-of-food-crop-1cfd7212

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 production or price movements
• Compare regions or commodities
• Join with climate and trade 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

@misc{electric_sheep_africa_africa_mauritius_area_harvested_production_yield_and_interline_of_food_crop_1cfd_2023,
  title        = {Area Harvested Production Yield and Interline of Food Crop | Africa (MDPA)},
  author       = {MDPA},
  year         = {2023},
  url          = {https://data.govmu.org/dataset/area-harvested-production-yield-and-interline-of-food-crops-for-mauritius-for-year-2023},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-area-harvested-production-yield-and-interline-of-food-crop-1cfd7212}}
}

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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/area-harvested-production-yield-and-interline-of-food-crops-for-mauritius-for-year-2023