electricsheepafrica/africa-mauritius-mauritius-exchange-rates-5c8ceb86

Mauritius Exchange Rates | Africa (MDPA)

11 rows - 1 Africa country/area - 2006-2023 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 11 rows from MDPA, covering Mauritius Exchange Rates. 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: Mauritius Exchange Rates (Average buying + selling) from National_Accounts 2006-2023

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	11
Countries/areas	1
First period	2006
Last period	2023
Indicators	0
Columns	57
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
MU	11	2006	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.	4ac6da1c-97ab-4807-940a-14f65466367d: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
australian_dollar	string	Source column from the original resource.	Great Britain Pound
d_10_71	double	Source column from the original resource.	17.86
d_12_3	double	Source column from the original resource.	18.47
d_10_92	double	Source column from the original resource.	20.03
d_9_19	double	Source column from the original resource.	19.87
d_9_18	double	Source column from the original resource.	21.2
d_10_73	double	Source column from the original resource.	24.07
d_12_26	double	Source column from the original resource.	25.16
d_11_57	double	Source column from the original resource.	26.46
d_12_17	double	Source column from the original resource.	27.63
d_11_4	double	Source column from the original resource.	27.44
d_11_94	double	Source column from the original resource.	26.51
d_13_1	double	Source column from the original resource.	27.61
d_13_09	double	Source column from the original resource.	28.1
d_15_32	double	Source column from the original resource.	30.81
d_15_51	double	Source column from the original resource.	34.51
d_14_96	double	Source column from the original resource.	39.75
d_16_12	double	Source column from the original resource.	40.7
d_15_15	double	Source column from the original resource.	39.81
d_14_94	double	Source column from the original resource.	41.92
d_16_19	double	Source column from the original resource.	45.06
d_18_35	double	Source column from the original resource.	46.35
d_20_25	double	Source column from the original resource.	50.97
d_22_36	double	Source column from the original resource.	53.14
d_23_73	double	Source column from the original resource.	57.83
d_26_356	double	Source column from the original resource.	62.855
d_24_079	double	Source column from the original resource.	52.729
d_25_328	double	Source column from the original resource.	50.069
d_28_47	double	Source column from the original resource.	47.72
d_29_74	double	Source column from the original resource.	46.09
d_31_094916666666663	double	Source column from the original resource.	47.44275
d_29_489	double	Source column from the original resource.	47.823
d_27_37	double	Source column from the original resource.	50.253
d_26_27	double	Source column from the original resource.	53.729
d_26_583985750360753	double	Source column from the original resource.	48.59790602453103
d_26_71134219455239	double	Source column from the original resource.	44.776530828009726
d_25_598364477649113	double	Source column from the original resource.	45.501564109415696
d_24_781470415856283	double	Source column from the original resource.	45.304348738419385
d_27_127572897989374	double	Source column from the original resource.	50.157423204131874
d_31_185716943874837	double	Source column from the original resource.	56.88174551435407
d_30_61981233766234	double	Source column from the original resource.	54.189753753191255
d_30_312980624636722	double	Source column from the original resource.	56.08619238386831
source_period_start_year	int64	Start year inferred from source metadata.	2006
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.	2006-2023
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.	Mauritius Exchange Rates
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	table21.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	990f5574-e5b1-40ff-895d-ee56da0fc7ca
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	4ac6da1c-97ab-4807-940a-14f65466367d
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.govmu.org/dataset/990f5574-e5b1-40ff-895d-ee56da0fc7ca/r...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	CC-BY-SA-4.0
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-mauritius-exchange-rates-5c8ceb86")
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: table21.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-08T17:05:58Z
• Hugging Face repo: electricsheepafrica/africa-mauritius-mauritius-exchange-rates-5c8ceb86

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_mauritius_exchange_rates_5c8ceb86_2023,
  title        = {Mauritius Exchange Rates | Africa (MDPA)},
  author       = {MDPA},
  year         = {2023},
  url          = {https://data.govmu.org/dataset/mauritius-exchange-rates},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-mauritius-exchange-rates-5c8ceb86}}
}

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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/mauritius-exchange-rates