electricsheepafrica/africa-bilans-alimentaires-du-senegal-en-2016

Bilans alimentaires du Sénégal en 2016

Publisher: Food and Agriculture Organization (FAO) · Source: OpenAfrica · License: cc-by · Updated: 2021-03-22

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Abstract

alimentaires produites au Sénégal ajoutée à la quantité totale importée et ajustée à toute variation des stocks survenue depuis le début de la période de référence donne l'approvisionnement disponible pendant cette période. Du côté de l'utilisation, une distinction est faite entre les quantités exportées, nourries au bétail, utilisées pour les semences, mises en fabrication à des fins alimentaires et non alimentaires, les pertes pendant le stockage et le transport, et les approvisionnements alimentaires disponibles pour la consommation humaine.

Each row in this dataset represents time-series observations. Data was last updated on OpenAfrica on 2021-03-22. Geographic scope: Africa (multiple countries).

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	Time-series observations
Rows (total)	1,167
Columns	16 (6 numeric, 10 categorical, 0 datetime)
Train split	933 rows
Test split	233 rows
Geographic scope	Africa (multiple countries)
Publisher	Food and Agriculture Organization (FAO)
OpenAfrica last updated	2021-03-22

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Variables

Geographic — year_code (range 2016.0–2016.0), year (range 2016.0–2016.0).

Outcome / Measurement — value (range -133.0–14994.0).

Identifier / Metadata — domain_code (FBS), area_code (range 195.0–195.0), element_code (range 511.0–5911.0), item_code (range 2501.0–2899.0), esa_source (HDX) and 1 others.

Other — domain (New Food Balances), area (Senegal), element (Domestic supply quantity, Import Quantity, Fat supply quantity (g/capita/day)), item (Rice and products, Maize and products, Millet and products), unit (1000 tonnes, g/capita/day, kg) and 2 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-bilans-alimentaires-du-senegal-en-2016")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
domain_code	object	0.0%	FBS
domain	object	0.0%	New Food Balances
area_code	int64	0.0%	195.0 – 195.0 (mean 195.0)
area	object	0.0%	Senegal
element_code	int64	0.0%	511.0 – 5911.0 (mean 3853.6555)
element	object	0.0%	Domestic supply quantity, Import Quantity, Fat supply quantity (g/capita/day)
item_code	int64	0.0%	2501.0 – 2899.0 (mean 2624.1662)
item	object	0.0%	Rice and products, Maize and products, Millet and products
year_code	int64	0.0%	2016.0 – 2016.0 (mean 2016.0)
year	int64	0.0%	2016.0 – 2016.0 (mean 2016.0)
unit	object	0.0%	1000 tonnes, g/capita/day, kg
value	float64	0.0%	-133.0 – 14994.0 (mean 40.0838)
flag	object	0.0%	Im, Fc, S
flag_description	object	0.0%	FAO data based on imputation methodology, Calculated data, Standardized data
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-29

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Numeric Summary

Column	Min	Max	Mean	Median
area_code	195.0	195.0	195.0	195.0
element_code	511.0	5911.0	3853.6555	5142.0
item_code	2501.0	2899.0	2624.1662	2602.0
year_code	2016.0	2016.0	2016.0	2016.0
year	2016.0	2016.0	2016.0	2016.0
value	-133.0	14994.0	40.0838	0.0

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Curation

Raw data was downloaded from OpenAfrica via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from Food and Agriculture Organization (FAO) and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{openafrica_africa_bilans_alimentaires_du_senegal_en_2016,
  title     = {Bilans alimentaires du Sénégal en 2016},
  author    = {Food and Agriculture Organization (FAO)},
  year      = {2021},
  url       = {https://open.africa/dataset/bilans-alimentaires-du-senegal-en-2016},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.