electricsheepafrica/africa-fewsnet-staple-food-price-data-for-kenya-monthly-125
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---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-regression
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- eastern-africa
- economics
- food-security
- indicators
- markets
- ken
pretty_name: "Kenya Monthly FEWS NET Staple Food Price Data"
dataset_info:
splits:
- name: train
num_examples: 1156
- name: test
num_examples: 289
---
# Kenya Monthly FEWS NET Staple Food Price Data
**Publisher:** FEWS NET · **Source:** [HDX](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_kenya_monthly_125) · **License:** `cc-by` · **Updated:** 2026-04-07
---
## Abstract
Kenya Monthly staple food price data collected by FEWS NET since 2005.
Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `period_date` column(s). Geographic scope: **KEN**.
*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
---
## Dataset Characteristics
| | |
|---|---|
| **Domain** | Food security and nutrition |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 1,446 |
| **Columns** | 18 (3 numeric, 14 categorical, 1 datetime) |
| **Train split** | 1,156 rows |
| **Test split** | 289 rows |
| **Geographic scope** | KEN |
| **Publisher** | FEWS NET |
| **HDX last updated** | 2026-04-07 |
---
## Variables
**Geographic** — `country` (Kenya), `admin_1` (Nairobi), `longitude` (range 36.8317–36.8317), `latitude` (range -1.2826–-1.2826), `price_type` (Retail) and 2 others.
**Temporal** — `period_date`.
**Outcome / Measurement** — `value` (range 20.0–622.0).
**Identifier / Metadata** — `fnid` (KE0000M012), `source_document` (Famine Early Warning Systems Network (FEWS NET), Kenya, Price), `product_source` (Local), `esa_source`, `esa_processed`.
**Other** — `market` (Nairobi), `cpcv2` (P23490AA, P22110AA, P33360AA), `product` (Bread, Cow's Milk (Fresh, Pasteurized), Diesel), `unit` (L, 500_g, 500_ml).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-kenya-monthly-125")
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% | Kenya |
| `fnid` | object | 0.0% | KE0000M012 |
| `market` | object | 0.0% | Nairobi |
| `admin_1` | object | 0.0% | Nairobi |
| `longitude` | float64 | 0.0% | 36.8317 – 36.8317 (mean 36.8317) |
| `latitude` | float64 | 0.0% | -1.2826 – -1.2826 (mean -1.2826) |
| `cpcv2` | object | 0.0% | P23490AA, P22110AA, P33360AA |
| `product` | object | 0.0% | Bread, Cow's Milk (Fresh, Pasteurized), Diesel |
| `source_document` | object | 0.0% | Famine Early Warning Systems Network (FEWS NET), Kenya, Price |
| `period_date` | datetime64[ns] | 0.0% | |
| `price_type` | object | 0.0% | Retail |
| `product_source` | object | 0.0% | Local |
| `unit` | object | 0.0% | L, 500_g, 500_ml |
| `unit_type` | object | 0.0% | |
| `currency` | object | 0.0% | |
| `value` | float64 | 0.6% | 20.0 – 622.0 (mean 115.6194) |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `longitude` | 36.8317 | 36.8317 | 36.8317 | 36.8317 |
| `latitude` | -1.2826 | -1.2826 | -1.2826 | -1.2826 |
| `value` | 20.0 | 622.0 | 115.6194 | 90.0 |
---
## 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](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_kenya_monthly_125) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_fewsnet_staple_food_price_data_for_kenya_monthly_125,
title = {Kenya Monthly FEWS NET Staple Food Price Data},
author = {FEWS NET},
year = {2026},
url = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_kenya_monthly_125},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```
---
*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*
提供机构:
electricsheepafrica



