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electricsheepafrica/africa-mauritius-mobile-banking-and-mobile-payments-0e3b0ca0

Mobile Banking and Mobile Payments | Africa (MDPA) 30 rows - 1 Africa country/area - 2020 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 30 rows from MDPA, covering Mobile Banking and Mobile Payments. 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-mobile-banking-and-mobile-payments-0e3b0ca0.

sourceHugging Facecc-by-sa-4.0updated 2mo agoView on Hugging Face
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Mobile Banking and Mobile Payments | Africa (MDPA)

30 rows - 1 Africa country/area - 2020 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 30 rows from MDPA, covering Mobile Banking and Mobile Payments. 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: The data shows number of monthly Mobile Banking and Mobile Payments from year 2019 to August 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

DimensionValue
Rows30
Countries/areas1
First period2020
Last period2020
Indicators0
Columns112
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU3020202020Mauritius

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.8bc180ce-feff-4736-a5b1-a3ef435deefb:39-40-41:0
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.39-40-41
yearint64Observation year.2020
number_of_transactions_4stringSource column from the original resource.Value of Transactions (Rs million) 2 & 4
d_4736872stringSource column from the original resource.9717.931
d_4319467stringSource column from the original resource.8695.531
d_4841422stringSource column from the original resource.9537
d_4758541stringSource column from the original resource.9328.38
d_4845776stringSource column from the original resource.9365.379
d_4496701stringSource column from the original resource.8566.686
d_4733299stringSource column from the original resource.9187.151
d_4753864stringSource column from the original resource.9327.463
d_4589854stringSource column from the original resource.8899.062
d_5016549stringSource column from the original resource.10019.85
d_4831238stringSource column from the original resource.9953.074
d_6407067stringSource column from the original resource.14412.458
d_4875444stringSource column from the original resource.10301.35
d_4576070stringSource column from the original resource.9300.485
d_5159362stringSource column from the original resource.10679.24
d_5247975stringSource column from the original resource.11267.70279
d_4677566stringSource column from the original resource.9276.966
d_5215652stringSource column from the original resource.10612.598168220002
d_5146740stringSource column from the original resource.10549.572
d_4946438stringSource column from the original resource.9942
d_5139787stringSource column from the original resource.10729.645
d_5093468stringSource column from the original resource.10840.106
d_6796552stringSource column from the original resource.15747.024
d_5089885stringSource column from the original resource.11116.937
d_4795824stringSource column from the original resource.12597.385472539
d_5439117stringSource column from the original resource.11425
d_5556138stringSource column from the original resource.11616.533
d_5635041stringSource column from the original resource.11411.8463010512
d_5320280stringSource column from the original resource.10729.509122245256
d_5507836stringSource column from the original resource.11263.0062579179
d_5233474stringSource column from the original resource.10996.251
d_5283765stringSource column from the original resource.10655
d_5542287stringSource column from the original resource.11325.604
d_5430649stringSource column from the original resource.11628.968
d_7185702stringSource column from the original resource.17038.289164287296
d_5576038stringSource column from the original resource.11990.63
d_5217581stringSource column from the original resource.11039
d_5980306stringSource column from the original resource.12689.2040794632
d_5385116stringSource column from the original resource.11416
d_5476327stringSource column from the original resource.11568.88887716
d_5381144stringSource column from the original resource.11032.510691
d_5583771stringSource column from the original resource.11767
d_5722712stringSource column from the original resource.12212
d_5278224stringSource column from the original resource.10979.01516
d_5641964stringSource column from the original resource.12170
d_5639078stringSource column from the original resource.12319
d_7340347stringSource column from the original resource.17686.962684089995
d_5541738stringSource column from the original resource.12299.68105725
d_5436047stringSource column from the original resource.11863
d_5734387stringSource column from the original resource.12300
d_5520603stringSource column from the original resource.12047
d_6001113stringSource column from the original resource.12894.22292939
d_5408488stringSource column from the original resource.11442
d_5762671stringSource column from the original resource.12705.69796049
d_6034651stringSource column from the original resource.13047
d_5574065stringSource column from the original resource.11945
d_6189540stringSource column from the original resource.13772.597299
d_5990000stringSource column from the original resource.13412
d_8031505stringSource column from the original resource.19581.84666339
d_6197949stringSource column from the original resource.13905
d_5467258stringSource column from the original resource.12044.143946
d_6180864stringSource column from the original resource.13521
d_5874355stringSource column from the original resource.12691.390219
d_6477234stringSource column from the original resource.13828
d_5857453stringSource column from the original resource.12433.66978
d_6305140stringSource column from the original resource.13739
d_6378216stringSource column from the original resource.13832
d_6056687stringSource column from the original resource.12928
d_6754415stringSource column from the original resource.14819
d_6368444stringSource column from the original resource.14337
d_8181811stringSource column from the original resource.19660
d_6383125stringSource column from the original resource.14085
d_6109633stringSource column from the original resource.13453
d_6979691stringSource column from the original resource.15346
d_6781194stringSource column from the original resource.``
d_7170154stringSource column from the original resource.``
d_6256345stringSource column from the original resource.``
d_7092455stringSource column from the original resource.``
d_6979838stringSource column from the original resource.``
d_6511710stringSource column from the original resource.``
d_7300253stringSource column from the original resource.``
d_6950183stringSource column from the original resource.``
d_8741586stringSource column from the original resource.``
d_6933706stringSource column from the original resource.``
d_6547750stringSource column from the original resource.``
d_7382070stringSource column from the original resource.``
d_7541784stringSource column from the original resource.``
d_7489177stringSource column from the original resource.``
d_6826339stringSource column from the original resource.``
d_7573108stringSource column from the original resource.``
d_7493801stringSource column from the original resource.``
d_7230248stringSource column from the original resource.``
d_7884889stringSource column from the original resource.``
d_7291162stringSource column from the original resource.``
d_9844856stringSource column from the original resource.``
source_period_start_yearint64Start year inferred from source metadata.``
source_period_end_yearint64End year inferred from source metadata.``
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.``
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.``
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.``
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.``
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.``
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.``
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.``
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.``
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-mobile-banking-and-mobile-payments-0e3b0ca0")
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

  • —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

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
  • —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

bibtex
@misc{electric_sheep_africa_africa_mauritius_mobile_banking_and_mobile_payments_0e3b0ca0_2020,
  title        = {Mobile Banking and Mobile Payments | Africa (MDPA)},
  author       = {MDPA},
  year         = {2020},
  url          = {https://data.govmu.org/dataset/mobile-banking-and-mobile-payments},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-mobile-banking-and-mobile-payments-0e3b0ca0}}
}

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/mobile-banking-and-mobile-payments