electricsheepafrica/africa-wfp-food-prices-for-cote-divoire

Cote d'Ivoire - Food Prices

Publisher: WFP - World Food Programme · Source: HDX · License: cc-by-igo · Updated: 2024-09-13

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Abstract

This dataset contains Food Prices data for Cote d'Ivoire. Food prices data comes from the World Food Programme and covers foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the date column(s). Geographic scope: CIV.

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

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Dataset Characteristics

Domain	Food security and nutrition
Unit of observation	Country-level aggregates
Rows (total)	5,127
Columns	18 (7 numeric, 10 categorical, 1 datetime)
Train split	4,101 rows
Test split	1,025 rows
Geographic scope	CIV
Publisher	WFP - World Food Programme
HDX last updated	2024-09-13

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Variables

Geographic — category (cereals and tubers, meat, fish and eggs, pulses and nuts), currency (XOF, #currency), country (Cote d'Ivoire, #country+name).

Temporal — date.

Outcome / Measurement — price (range 35.0–3550.0).

Identifier / Metadata — cmname (Maize - Retail, Rice (denikassia, imported) - Retail, Rice (local) - Retail), admname (Montagnes, Vallee Du Bandama, Denguele), adm1id (range 1041.0–40692.0), mktname (Man, Guiglo, Bouake), mktid (range 125.0–1807.0) and 6 others.

Other — unit (KG, L, #item+unit), sn (127_51_15_5, 127_70_15_5, 127_71_15_5).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-wfp-food-prices-for-cote-divoire")
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
date	datetime64[ns]	0.0%
cmname	object	0.0%	Maize - Retail, Rice (denikassia, imported) - Retail, Rice (local) - Retail
unit	object	0.0%	KG, L, #item+unit
category	object	0.0%	cereals and tubers, meat, fish and eggs, pulses and nuts
price	float64	0.0%	35.0 – 3550.0 (mean 708.7705)
currency	object	0.0%	XOF, #currency
country	object	0.0%	Cote d'Ivoire, #country+name
admname	object	16.6%	Montagnes, Vallee Du Bandama, Denguele
adm1id	float64	0.0%	1041.0 – 40692.0 (mean 20650.8701)
mktname	object	0.0%	Man, Guiglo, Bouake
mktid	float64	0.0%	125.0 – 1807.0 (mean 473.2444)
cmid	float64	0.0%	51.0 – 488.0 (mean 125.8625)
ptid	float64	0.0%	15.0 – 15.0 (mean 15.0)
umid	float64	0.0%	5.0 – 15.0 (mean 5.6184)
catid	float64	0.0%	1.0 – 8.0 (mean 2.1137)
sn	object	0.0%	127_51_15_5, 127_70_15_5, 127_71_15_5
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-07

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Numeric Summary

Column	Min	Max	Mean	Median
price	35.0	3550.0	708.7705	363.0
adm1id	1041.0	40692.0	20650.8701	16843.0
mktid	125.0	1807.0	473.2444	127.0
cmid	51.0	488.0	125.8625	72.0
ptid	15.0	15.0	15.0	15.0
umid	5.0	15.0	5.6184	5.0
catid	1.0	8.0	2.1137	1.0

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Curation

Raw data was downloaded from HDX 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. 1 column(s) with >80% missing values were removed: default. 5 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 WFP - World Food Programme 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{hdx_africa_wfp_food_prices_for_cote_divoire,
  title     = {Cote d'Ivoire - Food Prices},
  author    = {WFP - World Food Programme},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/wfp-food-prices-for-cote-divoire},
  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.