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electricsheepafrica/africa-mauritius-exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencie-d89317ae

Exchange Rate of the Mur Vis a Vis Selected Hard Currencie | Africa (MDPA) 5 rows - 1 Africa country/area - 2018-2024 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 5 rows from MDPA, covering Exchange Rate of the Mur Vis a Vis Selected Hard Currencie. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencie-d89317ae.

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Dataset Card

Exchange Rate of the Mur Vis a Vis Selected Hard Currencie | Africa (MDPA)

5 rows - 1 Africa country/area - 2018-2024 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 5 rows from MDPA, covering Exchange Rate of the Mur Vis a Vis Selected Hard Currencie. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Dataset shows Exchange rate of the MUR vis-a-vis selected hard currencies, FY 2018/19 – FY 2023/24

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
Rows5
Countries/areas1
First period2018
Last period2024
Indicators0
Columns22
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU520182024Mauritius

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.9814a1b6-7f90-4b01-aa7e-2734e1e82eef: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
currenciesstringSource column from the original resource.US Dollars
fy2018_19int64Source column from the original resource.35122
fy2019_20int64Source column from the original resource.37914
fy2021_22int64Source column from the original resource.43674
fy2021_22_2int64Source column from the original resource.43674
fy2022_23int64Source column from the original resource.45420
fy2023_24int64Source column from the original resource.45732
source_period_start_yearint64Start year inferred from source metadata.2018
source_period_end_yearint64End year inferred from source metadata.2024
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2018-2024
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Exchange rate of the MUR vis-a-vis selected hard currencies, FY 2018/...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Source File
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.be5ceb27-e30d-415f-9aea-ab149c5296e3
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.9814a1b6-7f90-4b01-aa7e-2734e1e82eef
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/be5ceb27-e30d-415f-9aea-ab149c5296e3/r...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
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-exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencie-d89317ae")
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

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_mauritius_exchange_rate_of_the_mur_vis_a_vis_selected_hard_currencie_d893_2024,
  title        = {Exchange Rate of the Mur Vis a Vis Selected Hard Currencie | Africa (MDPA)},
  author       = {MDPA},
  year         = {2024},
  url          = {https://data.govmu.org/dataset/exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencies-fy-2018-19-fy-2023-24},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencie-d89317ae}}
}

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.


Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/exchange-rate-of-the-mur-vis-a-vis-selected-hard-currencies-fy-2018-19-fy-2023-24