electricsheepafrica/africa-fewsnet-staple-food-price-data-for-zimbabwe-monthly-4566

---
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
- economics
- food-security
- indicators
- markets
- zwe
pretty_name: "Zimbabwe Monthly FEWS NET Staple Food Price Data"
dataset_info:
splits:
- name: train
num_examples: 3902
- name: test
num_examples: 975
---

# Zimbabwe Monthly FEWS NET Staple Food Price Data

**Publisher:** FEWS NET · **Source:** [HDX](https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_zimbabwe_monthly_4566) · **License:** `cc-by` · **Updated:** 2026-01-28

---

## Abstract

Zimbabwe Monthly staple food price data collected by FEWS NET since 2004.

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

*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)** | 4,878 |
| **Columns** | 17 (3 numeric, 13 categorical, 1 datetime) |
| **Train split** | 3,902 rows |
| **Test split** | 975 rows |
| **Geographic scope** | ZWE |
| **Publisher** | FEWS NET |
| **HDX last updated** | 2026-01-28 |

---

## Variables

**Geographic** — `country` (Zimbabwe), `admin_1` (Harare, Bulawayo, Midlands), `longitude` (range 28.5734–32.6556), `latitude` (range -20.1471–-17.868), `price_type` (Retail) and 2 others.

**Temporal** — `period_date`.

**Outcome / Measurement** — `value` (range 0.0005–1849.0).

**Identifier / Metadata** — `source_document` (Famine Early Warning Systems Network (FEWS NET), Zimbabwe, Price (ZWL), Famine Early Warning Systems Network (FEWS NET), Zimbabwe, Price (USD)), `product_source` (Local, Import), `esa_source`, `esa_processed`.

**Other** — `market` (Harare, Mbare, Bulawayo, Renkini, Gweru, Kombayi), `cpcv2` (P33360AA, P33310AA, P23490AA), `product` (Diesel, Gasoline, Bread), `unit` (L, kg, 700_g).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-fewsnet-staple-food-price-data-for-zimbabwe-monthly-4566")
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% | Zimbabwe |
| `market` | object | 0.0% | Harare, Mbare, Bulawayo, Renkini, Gweru, Kombayi |
| `admin_1` | object | 0.0% | Harare, Bulawayo, Midlands |
| `longitude` | float64 | 0.0% | 28.5734 – 32.6556 (mean 30.7957) |
| `latitude` | float64 | 0.0% | -20.1471 – -17.868 (mean -18.6158) |
| `cpcv2` | object | 0.0% | P33360AA, P33310AA, P23490AA |
| `product` | object | 0.0% | Diesel, Gasoline, Bread |
| `source_document` | object | 0.0% | Famine Early Warning Systems Network (FEWS NET), Zimbabwe, Price (ZWL), Famine Early Warning Systems Network (FEWS NET), Zimbabwe, Price (USD) |
| `period_date` | datetime64[ns] | 0.0% | |
| `price_type` | object | 0.0% | Retail |
| `product_source` | object | 0.0% | Local, Import |
| `unit` | object | 0.0% | L, kg, 700_g |
| `unit_type` | object | 0.0% | Volume, Weight, Item |
| `currency` | object | 0.0% | |
| `value` | float64 | 9.1% | 0.0005 – 1849.0 (mean 17.8414) |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `longitude` | 28.5734 | 32.6556 | 30.7957 | 31.0312 |
| `latitude` | -20.1471 | -17.868 | -18.6158 | -17.868 |
| `value` | 0.0005 | 1849.0 | 17.8414 | 1.34 |

---

## 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_zimbabwe_monthly_4566) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_fewsnet_staple_food_price_data_for_zimbabwe_monthly_4566,
title = {Zimbabwe Monthly FEWS NET Staple Food Price Data},
author = {FEWS NET},
year = {2026},
url = {https://data.humdata.org/dataset/fewsnet_staple_food_price_data_for_zimbabwe_monthly_4566},
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.*