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electricsheepafrica/africa-senegal-pourcentage-de-la-superficie-forestiere-soumise-a-une-gest-b82babc7

Pourcentage De La Superficie Forestiere Soumise a Une Gest | Africa (DPVE) 2 rows - 1 Africa country/area - 2015 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 2 rows from DPVE, covering Pourcentage De La Superficie Forestiere Soumise a Une Gest. 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-senegal-pourcentage-de-la-superficie-forestiere-soumise-a-une-gest-b82babc7.

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Pourcentage De La Superficie Forestiere Soumise a Une Gest | Africa (DPVE)

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

rows countries period indicators license

TL;DR

This dataset contains 2 rows from DPVE, covering Pourcentage De La Superficie Forestiere Soumise a Une Gest. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Agriculture datasets help analysts examine production, prices, inputs, land use, food systems, and rural economic activity.

Source-provided context: META DATA sur l'indicateur de pourcentage de la superficie forestière soumise à une gestion à long terme

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

Coverage

DimensionValue
Rows2
Countries/areas1
First period2015
Last period2015
Indicators0
Columns31
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
SEN220152015Senegal

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.b41099f9-1e4e-44b7-91e4-7ab05a0e91f8:pourcentage-de-la-superficie-fo:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.SEN
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.Senegal
source_sheetstringSource column from the original resource.Pourcentage de la superficie fo
valeurdelasituationdereferedoubleSource column from the original resource.49.53
datesdrint64Source column from the original resource.2015
vi2015doubleSource column from the original resource.49.53
vi2016doubleSource column from the original resource.63.18
vi2017doubleSource column from the original resource.63.18
vi2018doubleSource column from the original resource.63.18
vi2019int64Source column from the original resource.2020
modedecalcultauxproportiostringSource column from the original resource.taux
frequencedeproductionirregulstringSource column from the original resource.quinquennale
delaidediffusionstringSource column from the original resource.quinquennale
lindicateurestildiffuseprestringSource column from the original resource.non
niveaudedesagregationagesestringSource column from the original resource.région
statutdelindicateurdefinitistringSource column from the original resource.Définitif
uniteechellemilliermistringSource column from the original resource.%
sourcestringSource column from the original resource.comité FRA
methodedaccesstringSource column from the original resource.Rapport de performance du METE
source_period_start_yearint64Start year inferred from source metadata.``
source_period_end_yearint64End year inferred from source metadata.``
source_period_labelstringSource column from the original resource.``
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.DPVE
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Pourcentage de la superficie forestière soumise à une gestion à long ...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.META DONNEES
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.0c9fe760-fd86-4da9-be35-65b5bdccf139
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.b41099f9-1e4e-44b7-91e4-7ab05a0e91f8
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://agridata.ansd.sn/dataset/0c9fe760-fd86-4da9-be35-65b5bdccf139...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-27T11:04:43Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-senegal-pourcentage-de-la-superficie-forestiere-soumise-a-une-gest-b82babc7")
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"] == "SEN"]

Time-Series Pattern

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

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

  • —Canonical time field: datesdr.
  • —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

  • —Track production or price movements
  • —Compare regions or commodities
  • —Join with climate and trade data
  • —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

bibtex
@misc{electric_sheep_africa_africa_senegal_pourcentage_de_la_superficie_forestiere_soumise_a_une_gest_b82bab_2015,
  title        = {Pourcentage De La Superficie Forestiere Soumise a Une Gest | Africa (DPVE)},
  author       = {DPVE},
  year         = {2015},
  url          = {https://agridata.ansd.sn/dataset/pourcentagesuperficieforestieregestionlongterme},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-senegal-pourcentage-de-la-superficie-forestiere-soumise-a-une-gest-b82babc7}}
}

License

Released under CC BY 4.0.

Original data is published by DPVE. 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/pourcentagesuperficieforestieregestionlongterme