electricsheepafrica/africa-senegal-anomalies-de-temperature-max-739842d7

Anomalies De Temperature Max | Africa (ANACIM)

1,186 rows - 1 Africa country/area - 1991-2023 - 36 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 1,186 rows from ANACIM, covering Anomalies De Temperature Max. 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: Anomalies des températures maximales à Dakar [2023]

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	1,186
Countries/areas	1
First period	1991
Last period	2023
Indicators	36
Columns	19
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SEN	1,186	1991	2023	Senegal

Indicators, Variables, Or Resource Contents

• anomalies-de-temperature-max-moy-janv-8e4180ab - Anomalies de température _Max - moy janv(source_units_unspecified)
• anomalies-de-temperature-max-normale-janv-1d0ed8b8 - Anomalies de température _Max - normale janv(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-janv-109210d4 - Anomalies de température _Max - anomalies janv(source_units_unspecified)
• anomalies-de-temperature-max-moy-fev-c2e18554 - Anomalies de température _Max - moy fev(source_units_unspecified)
• anomalies-de-temperature-max-normale-fev-2ad2e991 - Anomalies de température _Max - normale fev(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-fev-b331d71a - Anomalies de température _Max - anomalies fev(source_units_unspecified)
• anomalies-de-temperature-max-moy-mar-a7f9ad78 - Anomalies de température _Max - moy mar(source_units_unspecified)
• anomalies-de-temperature-max-normale-mar-2b7c86be - Anomalies de température _Max - normale mar(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-mar-f65d01a3 - Anomalies de température _Max - anomalies mar(source_units_unspecified)
• anomalies-de-temperature-max-moy-avr-bbb7c02a - Anomalies de température _Max - moy avr(source_units_unspecified)
• anomalies-de-temperature-max-normale-avr-6478b305 - Anomalies de température _Max - normale avr(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-avr-fcb4011b - Anomalies de température _Max - anomalies avr(source_units_unspecified)
• anomalies-de-temperature-max-moy-mai-a835d216 - Anomalies de température _Max - moy mai(source_units_unspecified)
• anomalies-de-temperature-max-normale-mai-0b570275 - Anomalies de température _Max - normale mai(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-mai-169385d9 - Anomalies de température _Max - anomalies mai(source_units_unspecified)
• anomalies-de-temperature-max-moy-juin-1be22209 - Anomalies de température _Max - moy juin(source_units_unspecified)
• anomalies-de-temperature-max-normale-juin-7c0509e3 - Anomalies de température _Max - normale juin(source_units_unspecified)
• anomalies-de-temperature-max-anomalies-juin-d8d569c6 - Anomalies de température _Max - anomalies juin(source_units_unspecified)
• anomalies-de-temperature-max-moy-juil-a056b59b - Anomalies de température _Max - moy juil(source_units_unspecified)
• anomalies-de-temperature-max-normale-juil-c4ff32c3 - Anomalies de température _Max - normale juil(source_units_unspecified)
• ... 16 more indicators

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	anomalies-de-temperature-max-moy-janv-8e4180ab
indicator_name	string	Human-readable indicator name.	Anomalies de température _Max - moy janv
country_iso3	string	ISO3 country or area code.	SEN
source_sheet	string	Source column from the original resource.	Dakar Tmax
country_name	string	Country or area name.	Senegal
year	int64	Observation year.	1991
value	double	Numeric observation value.	24.5838709622622
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
source_period_start_year	int64	Start year inferred from source metadata.	2023
source_period_end_year	int64	End year inferred from source metadata.	2023
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2023
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	ANACIM
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Anomalies de température _Max
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Anomalies Dakar Tmax 2023
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	8bc963da-c116-415c-bf21-5b6ac6ad4671
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	0db71c3a-d6bf-411b-b169-024d27a5d2fe
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://agridata.ansd.sn/dataset/8bc963da-c116-415c-bf21-5b6ac6ad4671...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	odc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-27T11:04:43Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-senegal-anomalies-de-temperature-max-739842d7")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "SEN"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

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

• Source: ANACIM
• Publisher: ANACIM
• Portal: https://agridata.ansd.sn
• Resource: Anomalies Dakar Tmax 2023
• License: Open Data Commons Attribution License
• Retrieved/generated: 2026-07-27T11:05:07Z
• Hugging Face repo: electricsheepafrica/africa-senegal-anomalies-de-temperature-max-739842d7

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
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_senegal_anomalies_de_temperature_max_739842d7_2023,
  title        = {Anomalies De Temperature Max | Africa (ANACIM)},
  author       = {ANACIM},
  year         = {2023},
  url          = {https://agridata.ansd.sn/dataset/anomalietemperaturemax},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-anomalies-de-temperature-max-739842d7}}
}

License

Released under Open Data Commons Attribution License.

Original data is published by ANACIM. 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.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://agridata.ansd.sn/dataset/anomalietemperaturemax