electricsheepafrica/africa-senegal-anomalies-de-temperature-max-e2b66cff

Anomalies De Temperature Max | Africa (ANACIM)

1 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 1 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: META DATA de l'indicateur sur les anomalies des températures MAX ANACIM

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: source_period_start_year.
• Time coverage basis: source_period_start_year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	1
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	25
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SEN	1	detected	detected	Senegal

Indicators, Variables, Or Resource Contents

• This repo preserves one source tabular resource with its usable columns kept together.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	502721f3-708d-43e7-874c-c0d805cf8b9e:metadata:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	SEN
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Senegal
source_sheet	string	Source column from the original resource.	METADATA
methode_de_collecte	string	Source column from the original resource.	Données d'observation
mode_de_calcul	string	Source column from the original resource.	Différence
frequence_de_production	string	Source column from the original resource.	annuelle
delai_de_diffusion	string	Source column from the original resource.	mensuel
indicateur_diffuse	string	Source column from the original resource.	non
niveau_de_desagregation	string	Source column from the original resource.	station
statut_de_l_indicateur	string	Source column from the original resource.	définitif
unite_echelle	string	Source column from the original resource.	degrès celsius
source	string	Source column from the original resource.	ANACIM
methode_de_acces	string	Source column from the original resource.	sur demande
source_period_start_year	int64	Start year inferred from source metadata.	``
source_period_end_year	int64	End year inferred from source metadata.	``
source_period_label	string	Source column from the original resource.	``
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.	META DONNEES
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.	502721f3-708d-43e7-874c-c0d805cf8b9e
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-e2b66cff")
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 "source_period_start_year" in df.columns:
    trend = df.sort_values("source_period_start_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: source_period_start_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: META DONNEES
• License: Open Data Commons Attribution License
• Retrieved/generated: 2026-07-27T11:05:06Z
• Hugging Face repo: electricsheepafrica/africa-senegal-anomalies-de-temperature-max-e2b66cff

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
• 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_e2b66cff_2026,
  title        = {Anomalies De Temperature Max | Africa (ANACIM)},
  author       = {ANACIM},
  year         = {2026},
  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-e2b66cff}}
}

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.

---

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