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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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-mauritius-exchange-rates-5c8ceb86.

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

Mauritius Exchange Rates | Africa (MDPA)

11 rows - 1 Africa country/area - 2006-2023 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

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

DimensionValue
Rows11
Countries/areas1
First period2006
Last period2023
Indicators0
Columns57
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU1120062023Mauritius

Indicators, Variables, Or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.4ac6da1c-97ab-4807-940a-14f65466367d:sheet1:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.MU
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.Mauritius
source_sheetstringSource column from the original resource.Sheet1
australian_dollarstringSource column from the original resource.Great Britain Pound
d_10_71doubleSource column from the original resource.17.86
d_12_3doubleSource column from the original resource.18.47
d_10_92doubleSource column from the original resource.20.03
d_9_19doubleSource column from the original resource.19.87
d_9_18doubleSource column from the original resource.21.2
d_10_73doubleSource column from the original resource.24.07
d_12_26doubleSource column from the original resource.25.16
d_11_57doubleSource column from the original resource.26.46
d_12_17doubleSource column from the original resource.27.63
d_11_4doubleSource column from the original resource.27.44
d_11_94doubleSource column from the original resource.26.51
d_13_1doubleSource column from the original resource.27.61
d_13_09doubleSource column from the original resource.28.1
d_15_32doubleSource column from the original resource.30.81
d_15_51doubleSource column from the original resource.34.51
d_14_96doubleSource column from the original resource.39.75
d_16_12doubleSource column from the original resource.40.7
d_15_15doubleSource column from the original resource.39.81
d_14_94doubleSource column from the original resource.41.92
d_16_19doubleSource column from the original resource.45.06
d_18_35doubleSource column from the original resource.46.35
d_20_25doubleSource column from the original resource.50.97
d_22_36doubleSource column from the original resource.53.14
d_23_73doubleSource column from the original resource.57.83
d_26_356doubleSource column from the original resource.62.855
d_24_079doubleSource column from the original resource.52.729
d_25_328doubleSource column from the original resource.50.069
d_28_47doubleSource column from the original resource.47.72
d_29_74doubleSource column from the original resource.46.09
d_31_094916666666663doubleSource column from the original resource.47.44275
d_29_489doubleSource column from the original resource.47.823
d_27_37doubleSource column from the original resource.50.253
d_26_27doubleSource column from the original resource.53.729
d_26_583985750360753doubleSource column from the original resource.48.59790602453103
d_26_71134219455239doubleSource column from the original resource.44.776530828009726
d_25_598364477649113doubleSource column from the original resource.45.501564109415696
d_24_781470415856283doubleSource column from the original resource.45.304348738419385
d_27_127572897989374doubleSource column from the original resource.50.157423204131874
d_31_185716943874837doubleSource column from the original resource.56.88174551435407
d_30_61981233766234doubleSource column from the original resource.54.189753753191255
d_30_312980624636722doubleSource column from the original resource.56.08619238386831
source_period_start_yearint64Start year inferred from source metadata.2006
source_period_end_yearint64End year inferred from source metadata.2023
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2006-2023
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Mauritius Exchange Rates
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.table21.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.990f5574-e5b1-40ff-895d-ee56da0fc7ca
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.4ac6da1c-97ab-4807-940a-14f65466367d
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/990f5574-e5b1-40ff-895d-ee56da0fc7ca/r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.CC-BY-SA-4.0
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-mauritius-exchange-rates-5c8ceb86")
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

  • —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

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

bibtex
@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.


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