electricsheepafrica/africa-mauritius-eoe-imports-by-country-of-origin-2020-2023-ba359f58

Eoe Imports by Country of Origin 2020 2023 | Africa (MDPA)

44 rows - 1 Africa country/area - 2020-2023 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 44 rows from MDPA, covering Eoe Imports by Country of Origin 2020 2023. 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 the Export Oriented Enterprise Sector imports by country of origin Quarterwise 2020 - 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: not detected.
• Time coverage basis: source metadata.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	44
Countries/areas	1
First period	2020
Last period	2023
Indicators	0
Columns	36
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	44	2020	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.	6669fca8-6030-4285-bd8d-3f5a0c1b4ebd:sheet1:0
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.	Sheet1
total_eoe_imports_c_i_f_r_million	string	Source column from the original resource.	Europe
d_4812	double	Source column from the original resource.	2339.0
d_3580	double	Source column from the original resource.	1240.0
d_5305	double	Source column from the original resource.	2696.0
d_5933	double	Source column from the original resource.	2672.0
d_19629	double	Source column from the original resource.	8947.0
d_5368	double	Source column from the original resource.	2117.0
d_5849	double	Source column from the original resource.	2711.0
d_6689	double	Source column from the original resource.	2880.0
d_7767	double	Source column from the original resource.	3501.0
d_25673	double	Source column from the original resource.	11210.0
d_7478	double	Source column from the original resource.	3348.0
d_8226	double	Source column from the original resource.	3697.0
d_8793	double	Source column from the original resource.	4084.0
d_8968	double	Source column from the original resource.	3878.0
d_33466	double	Source column from the original resource.	15006.0
d_6809	double	Source column from the original resource.	2950.0
d_7346	double	Source column from the original resource.	3525.0
d_6273	double	Source column from the original resource.	2746.0
d_6353	double	Source column from the original resource.	2546.0
d_26781	double	Source column from the original resource.	11767.0
source_period_start_year	int64	Start year inferred from source metadata.	2020
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.	2020-2023
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.	EOE imports by country of origin 2020 - 2023
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Source File: EOE imports by country of origin, 2020 - 2023.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	ff00cf60-3924-4c63-8711-b2f1746d4447
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	6669fca8-6030-4285-bd8d-3f5a0c1b4ebd
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/ff00cf60-3924-4c63-8711-b2f1746d4447/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-eoe-imports-by-country-of-origin-2020-2023-ba359f58")
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

• No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• 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: EOE imports by country of origin, 2020 - 2023.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-08T16:52:41Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-eoe-imports-by-country-of-origin-2020-2023-ba359f58

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
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_mauritius_eoe_imports_by_country_of_origin_2020_2023_ba359f58_2023,
  title        = {Eoe Imports by Country of Origin 2020 2023 | Africa (MDPA)},
  author       = {MDPA},
  year         = {2023},
  url          = {https://data.govmu.org/dataset/eoe-imports-by-country-of-origin-2020-2023},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-eoe-imports-by-country-of-origin-2020-2023-ba359f58}}
}

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/eoe-imports-by-country-of-origin-2020-2023