Datasets:
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-regression
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- economics
- food-security
- indicators
- markets
- tcd
pretty_name: Chad Weekly FEWS NET Staple Food Price Data
dataset_info:
splits:
- name: train
num_examples: 55088
- name: test
num_examples: 13772
Chad Weekly FEWS NET Staple Food Price Data
Publisher: FEWS NET · Source: HDX · License: cc-by · Updated: 2026-04-01
Abstract
Chad Weekly staple food price data collected by FEWS NET since 2002.
Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the period_date column(s). Geographic scope: TCD.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Food security and nutrition |
| Unit of observation | Country-level aggregates |
| Rows (total) | 68,861 |
| Columns | 18 (3 numeric, 14 categorical, 1 datetime) |
| Train split | 55,088 rows |
| Test split | 13,772 rows |
| Geographic scope | TCD |
| Publisher | FEWS NET |
| HDX last updated | 2026-04-01 |
Variables
Geographic — country (Chad), admin_1 (Kanem, N'Djamena, Ouaddai), longitude (range 14.7148–20.9267), latitude (range 8.5596–17.9287), price_type (Retail) and 2 others.
Temporal — period_date.
Outcome / Measurement — value (range 25.5–367968.0).
Identifier / Metadata — fnid (TD0000M010, TD0000M001, TD0000M004), source_document (Famine Early Warning Systems Network (FEWS NET), Chad, Price (weekly)), product_source (Local, Import), esa_source, esa_processed.
Other — market (N'Djamena, Abeche, Bongor), cpcv2 (R01182AD, R01142AC, R01709AE), product (Millet (Pearl), Sorghum (Red), Cowpeas (Mixed)), unit (kg, ea, L).
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-chad-weekly-124")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
country |
object | 0.0% | Chad |
fnid |
object | 0.0% | TD0000M010, TD0000M001, TD0000M004 |
market |
object | 0.0% | N'Djamena, Abeche, Bongor |
admin_1 |
object | 0.0% | Kanem, N'Djamena, Ouaddai |
longitude |
float64 | 0.0% | 14.7148 – 20.9267 (mean 17.2839) |
latitude |
float64 | 0.0% | 8.5596 – 17.9287 (mean 12.1065) |
cpcv2 |
object | 0.0% | R01182AD, R01142AC, R01709AE |
product |
object | 0.0% | Millet (Pearl), Sorghum (Red), Cowpeas (Mixed) |
source_document |
object | 0.0% | Famine Early Warning Systems Network (FEWS NET), Chad, Price (weekly) |
period_date |
datetime64[ns] | 0.0% | |
price_type |
object | 0.0% | Retail |
product_source |
object | 0.0% | Local, Import |
unit |
object | 0.0% | kg, ea, L |
unit_type |
object | 0.0% | |
currency |
object | 0.0% | |
value |
float64 | 5.8% | 25.5 – 367968.0 (mean 12892.3008) |
esa_source |
object | 0.0% | |
esa_processed |
object | 0.0% |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
longitude |
14.7148 | 20.9267 | 17.2839 | 16.493 |
latitude |
8.5596 | 17.9287 | 12.1065 | 12.1867 |
value |
25.5 | 367968.0 | 12892.3008 | 512.28 |
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) 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.
Limitations
- Data originates from FEWS NET 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.
Citation
@dataset{hdx_africa_fewsnet_staple_food_price_data_for_chad_weekly_124,
title = {Chad Weekly FEWS NET Staple Food Price Data},
author = {FEWS NET},
year = {2026},
url = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_chad_weekly_124},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.