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electricsheepafrica/africa-mauritius-percentage-water-level-by-year-month-and-reservoir-de3b50ad

Percentage Water Level by Year Month and Reservoir | Africa (MDPA) 20 rows - 1 Africa country/area - 2021-2022 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 20 rows from MDPA, covering Percentage Water Level by Year Month and Reservoir. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Climate and… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-percentage-water-level-by-year-month-and-reservoir-de3b50ad.

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Dataset Card

Percentage Water Level by Year Month and Reservoir | Africa (MDPA)

20 rows - 1 Africa country/area - 2021-2022 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 20 rows from MDPA, covering Percentage Water Level by Year Month and Reservoir. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Climate and environment datasets help analysts study exposure, resource conditions, environmental pressure, and climate-related trends.

Source-provided context: the data shows percentage water level by year, by month and by reservoir for the year 2021 and 2022.

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
Rows20
Countries/areas1
First period2021
Last period2022
Indicators0
Columns70
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU2020212022Mauritius

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.eab8ad8c-5b0a-4005-a4de-da0fbb19f7c6:tab14:0
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.TAB14
janstringSource column from the original resource.Feb
d_59_3859502753212doubleSource column from the original resource.62.549846348517725
d_54_34924078091106doubleSource column from the original resource.61.71691973969632
d_62_55965292841649doubleSource column from the original resource.63.28633405639913
d_70_58046115529847doubleSource column from the original resource.92.79779307743092
d_63_579175704989154doubleSource column from the original resource.74.90238611713666
d_75_96529284164858doubleSource column from the original resource.95.88937093275489
d_60doubleSource column from the original resource.65.0
d_70_72674332234008doubleSource column from the original resource.67.57805458993175
d_68_17303978370026doubleSource column from the original resource.63.31788335264581
d_73_34878331402085doubleSource column from the original resource.70.33603707995366
d_69_36898273321603doubleSource column from the original resource.97.29457403395637
d_63_15179606025493doubleSource column from the original resource.72.53765932792584
d_74_43028196214755doubleSource column from the original resource.100.0
d_23doubleSource column from the original resource.30.0
d_29_7943376068376doubleSource column from the original resource.37.37340856481481
d_22_048611111111114doubleSource column from the original resource.36.28472222222222
d_35_24305555555555doubleSource column from the original resource.38.54166666666667
d_53_433641975308646doubleSource column from the original resource.65.40232487922707
d_52_864583333333336doubleSource column from the original resource.52.951388888888886
d_54_25347222222222doubleSource column from the original resource.71.875
d_32doubleSource column from the original resource.48.0
d_79_92405683488487doubleSource column from the original resource.79.4984076433121
d_75_79617834394904doubleSource column from the original resource.77.54777070063695
d_82_16560509554141doubleSource column from the original resource.80.4140127388535
d_76_75748997405046doubleSource column from the original resource.98.137635004154
d_72_45222929936304doubleSource column from the original resource.80.09554140127389
d_81_21019108280254doubleSource column from the original resource.100.0
source_period_start_yearint64Start year inferred from source metadata.2021
source_period_end_yearint64End year inferred from source metadata.2022
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2021-2022
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Percentage water level by year, month and reservoir
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Energy_Water_Yr22_060623_Source_file.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.c1537c98-cc38-44b3-9d8d-bb9b0f7a05f1
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.eab8ad8c-5b0a-4005-a4de-da0fbb19f7c6
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/c1537c98-cc38-44b3-9d8d-bb9b0f7a05f1/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
sepstringSource column from the original resource.``
d_89doubleSource column from the original resource.``
d_88_03548795944232doubleSource column from the original resource.``
d_80_60836501901142doubleSource column from the original resource.``
d_93_15589353612168doubleSource column from the original resource.``
d_60_67807351077311doubleSource column from the original resource.``
d_54_94296577946769doubleSource column from the original resource.``
d_70_15209125475286doubleSource column from the original resource.``
d_81doubleSource column from the original resource.``
d_98_6236171854901doubleSource column from the original resource.``
d_96_98996655518394doubleSource column from the original resource.``
d_99_66555183946487doubleSource column from the original resource.``
d_85_84567606306737doubleSource column from the original resource.``
d_82_94314381270902doubleSource column from the original resource.``
d_89_29765886287625doubleSource column from the original resource.``
d_99_12217194570134doubleSource column from the original resource.``
d_98_78431372549021doubleSource column from the original resource.``
d_99_68627450980392doubleSource column from the original resource.``
d_93_79971988795519doubleSource column from the original resource.``
d_90_0392156862745doubleSource column from the original resource.``
d_97_05882352941177doubleSource column from the original resource.``
d_99_24692516155929doubleSource column from the original resource.``
d_98_03523035230353doubleSource column from the original resource.``
d_100doubleSource column from the original resource.``
d_83_57046070460704doubleSource column from the original resource.``
d_78_5230352303523doubleSource column from the original resource.``
d_88_6178861788618doubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-percentage-water-level-by-year-month-and-reservoir-de3b50ad")
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

  • —Analyze seasonal or annual patterns
  • —Join with agriculture or health data
  • —Map geographic exposure
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_mauritius_percentage_water_level_by_year_month_and_reservoir_de3b50ad_2022,
  title        = {Percentage Water Level by Year Month and Reservoir | Africa (MDPA)},
  author       = {MDPA},
  year         = {2022},
  url          = {https://data.govmu.org/dataset/percentage-water-level-year-month-and-reservoir},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-percentage-water-level-by-year-month-and-reservoir-de3b50ad}}
}

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/percentage-water-level-year-month-and-reservoir