electricsheepafrica/africa-senegal-biomasse-a5485a6e

Biomasse | Africa (CSE)

1,008 rows - 1 Africa country/area - 2000-2024 - 1 indicator - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 1,008 rows from CSE, covering Biomasse. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: La biomasse totale représente la somme de la phytomasse herbacée et ligneuse obtenue à la fin de la saison des pluies (octobre). La méthode de calcul du CSE, basée sur la corrélation entre l’indice de végétation et la quantité de matière sèche collectée dans les 28 sites de contrôle au sol (SCS) permet d’estimer la biomasse totale ou biomasse disponible à la fin de la saison des pluies.

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	1,008
Countries/areas	1
First period	2000
Last period	2024
Indicators	1
Columns	21
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SEN	1,008	2000	2024	Senegal

Indicators, Variables, Or Resource Contents

• biomasse-a5485a6e - Biomasse(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	biomasse-a5485a6e
indicator_name	string	Human-readable indicator name.	Biomasse
country_iso3	string	ISO3 country or area code.	SEN
source_sheet	string	Source column from the original resource.	Calcul_Biomasse_kg,MS par ha
country_name	string	Country or area name.	Senegal
year	int64	Observation year.	2000
value	double	Numeric observation value.	2731.57
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_departement	string	Source dimension retained during long-form normalization.	Bakel
dimension_superficie_pastorale_ha	string	Source dimension retained during long-form normalization.	6723
source_period_start_year	int64	Start year inferred from source metadata.	2000
source_period_end_year	int64	End year inferred from source metadata.	2024
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2000-2024
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	CSE
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Biomasse
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Biomasse ligneuse de 2000 et de 2024
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	58df7321-2446-4298-b24e-7a3269da97f8
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	23aeaa39-1837-4428-80a1-c54993dc3de1
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://agridata.ansd.sn/dataset/58df7321-2446-4298-b24e-7a3269da97f8...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-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-biomasse-a5485a6e")
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: CSE
• Publisher: CSE
• Portal: https://agridata.ansd.sn
• Resource: Biomasse ligneuse de 2000 et de 2024
• License: CC BY 4.0
• Retrieved/generated: 2026-07-27T11:04:48Z
• Hugging Face repo: electricsheepafrica/africa-senegal-biomasse-a5485a6e

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

• Profile the distribution of values
• Compare categories or geographies
• Join with complementary public datasets
• 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_biomasse_a5485a6e_2024,
  title        = {Biomasse | Africa (CSE)},
  author       = {CSE},
  year         = {2024},
  url          = {https://agridata.ansd.sn/dataset/biomasse},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-biomasse-a5485a6e}}
}

License

Released under CC BY 4.0.

Original data is published by CSE. 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/biomasse