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electricsheepafrica/africa-mauritius-physical-and-chemical-characteristics-of-coastal-water-by-a80309aa

Physical and Chemical Characteristics of Coastal Water by | Africa (MDPA) 100 rows - 1 Africa country/area - 2015-2021 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 100 rows from MDPA, covering Physical and Chemical Characteristics of Coastal Water by. 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-physical-and-chemical-characteristics-of-coastal-water-by-a80309aa.

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Physical and Chemical Characteristics of Coastal Water by | Africa (MDPA)

100 rows - 1 Africa country/area - 2015-2021 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 100 rows from MDPA, covering Physical and Chemical Characteristics of Coastal Water by. 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: Dataset shows the Physical and Chemical Characteristics of Coastal Water by Level and Monitoring Site in Mauritius for the Year 2015 to 2021.

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
Rows100
Countries/areas1
First period2015
Last period2021
Indicators0
Columns38
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
MU10020152021Mauritius

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.79f9a030-1064-446b-ab31-03e971af0ce5:table-33:0
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.Table 33
mon_choisystringSource column from the original resource.Blue Bay
d_7_9_8_4stringSource column from the original resource.7.9 - 8.5
d_25_0_29_3stringSource column from the original resource.24.5 - 31.0
d_29_2_32_5stringSource column from the original resource.9.1 - 33.1
d_8_2_8_4stringSource column from the original resource.8.1 - 8.4
d_23_5_31_0stringSource column from the original resource.24.6 - 29.1
d_32_7_36_6stringSource column from the original resource.17.5 - 36.5
d_8_1_8_4stringSource column from the original resource.8.0 - 8.4
d_23_8_29_5stringSource column from the original resource.24.7 - 31.1
d_33_5_36_3stringSource column from the original resource.8.9 - 35.8
d_8_0_8_4stringSource column from the original resource.8.0 - 8.4
d_25_4_31_5stringSource column from the original resource.24.5 - 30.4
d_33_0_36_1stringSource column from the original resource.20.4 - 36.3
d_8_1_8_5stringSource column from the original resource.8.0 - 8.5
d_25_4_30_4stringSource column from the original resource.25.7 - 32.7
d_29_2_35_6stringSource column from the original resource.31.8 - 35.8
d_8_06_8_24stringSource column from the original resource.7.74 - 8.20
d_24_7_32_6stringSource column from the original resource.22.7 - 29.7
d_34_3_35_6stringSource column from the original resource.31.9 - 36.1
d_7_9_8_3stringSource column from the original resource.7.9 - 8.5
d_25_8_30_2stringSource column from the original resource.25.8 - 30.3
d_30_8_35_1stringSource column from the original resource.30.1 - 34.5
source_period_start_yearint64Start year inferred from source metadata.2015
source_period_end_yearint64End year inferred from source metadata.2021
source_period_labeldictionary<values=string, indices=int8, ordered=0>Source column from the original resource.2015-2021
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.MDPA
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Physical and Chemical Characteristics of Coastal Water by Level and M...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Source-File_7.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.c5b4e3b7-dcff-4c87-9cee-e73e5264d778
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.79f9a030-1064-446b-ab31-03e971af0ce5
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.govmu.org/dataset/c5b4e3b7-dcff-4c87-9cee-e73e5264d778/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
back_to_table_of_contentstringSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-physical-and-chemical-characteristics-of-coastal-water-by-a80309aa")
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_physical_and_chemical_characteristics_of_coastal_water_by_a8030_2021,
  title        = {Physical and Chemical Characteristics of Coastal Water by | Africa (MDPA)},
  author       = {MDPA},
  year         = {2021},
  url          = {https://data.govmu.org/dataset/physical-and-chemical-characteristics-coastal-water-level-and-monitoring-site-mauritius},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-physical-and-chemical-characteristics-of-coastal-water-by-a80309aa}}
}

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/physical-and-chemical-characteristics-coastal-water-level-and-monitoring-site-mauritius