electricsheepafrica/africa-faostat-food-prices-for-morocco
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---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- food-security
- indicators
- mar
pretty_name: "Morocco - Food Prices"
dataset_info:
splits:
- name: train
num_examples: 350
- name: test
num_examples: 87
---
# Morocco - Food Prices
**Publisher:** Food and Agriculture Organization (FAO) of the United Nations · **Source:** [HDX](https://data.humdata.org/dataset/faostat-food-prices-for-morocco) · **License:** `cc-by-igo` · **Updated:** 2026-04-06
---
## Abstract
Food Prices for Morocco.
Contains data from the FAOSTAT [bulk data service](https://fenixservices.fao.org/faostat/static/bulkdownloads/datasets_E.json) covering the following categories: Consumer Price Indices, Deflators, Exchange rates, Producer Prices
Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `startdate`, `enddate` column(s). Geographic scope: **MAR**.
*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)** | 438 |
| **Columns** | 17 (6 numeric, 9 categorical, 2 datetime) |
| **Train split** | 350 rows |
| **Test split** | 87 rows |
| **Geographic scope** | MAR |
| **Publisher** | Food and Agriculture Organization (FAO) of the United Nations |
| **HDX last updated** | 2026-04-06 |
---
## Variables
**Geographic** — `iso3` (MAR), `year_code` (range 1970.0–2024.0), `year` (range 1970.0–2024.0).
**Temporal** — `startdate`, `enddate`.
**Outcome / Measurement** — `value` (range 12.0352–130.9913).
**Identifier / Metadata** — `area_code` (range 143.0–143.0), `area_code_m49` ('504), `item_code` (range 22024.0–22028.0), `element_code` (range 6179.0–62250.0), `esa_source` (HDX) and 1 others.
**Other** — `area` (Morocco), `item` (GDP Deflator, Gross Fixed Capital Formation Deflator, Value Added Deflator (Agriculture, forestry and fishery)), `element` (Value Standard Local Currency, 2015 prices, Value US$, 2015 prices), `unit` (SLC, USD), `flag` (X, E).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-faostat-food-prices-for-morocco")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
```
---
## Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `iso3` | object | 0.0% | MAR |
| `startdate` | datetime64[ns] | 0.0% | |
| `enddate` | datetime64[ns] | 0.0% | |
| `area_code` | int64 | 0.0% | 143.0 – 143.0 (mean 143.0) |
| `area_code_m49` | object | 0.0% | '504 |
| `area` | object | 0.0% | Morocco |
| `item_code` | int64 | 0.0% | 22024.0 – 22028.0 (mean 22025.7397) |
| `item` | object | 0.0% | GDP Deflator, Gross Fixed Capital Formation Deflator, Value Added Deflator (Agriculture, forestry and fishery) |
| `element_code` | int64 | 0.0% | 6179.0 – 62250.0 (mean 34214.5) |
| `element` | object | 0.0% | Value Standard Local Currency, 2015 prices, Value US$, 2015 prices |
| `year_code` | int64 | 0.0% | 1970.0 – 2024.0 (mean 1996.8767) |
| `year` | int64 | 0.0% | 1970.0 – 2024.0 (mean 1996.8767) |
| `unit` | object | 0.0% | SLC, USD |
| `value` | float64 | 0.0% | 12.0352 – 130.9913 (mean 78.7328) |
| `flag` | object | 0.0% | X, E |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-06 |
---
## Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `area_code` | 143.0 | 143.0 | 143.0 | 143.0 |
| `item_code` | 22024.0 | 22028.0 | 22025.7397 | 22025.0 |
| `element_code` | 6179.0 | 62250.0 | 34214.5 | 34214.5 |
| `year_code` | 1970.0 | 2024.0 | 1996.8767 | 1997.0 |
| `year` | 1970.0 | 2024.0 | 1996.8767 | 1997.0 |
| `value` | 12.0352 | 130.9913 | 78.7328 | 87.6819 |
---
## 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`. 2 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 Food and Agriculture Organization (FAO) of the United Nations 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/faostat-food-prices-for-morocco) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_faostat_food_prices_for_morocco,
title = {Morocco - Food Prices},
author = {Food and Agriculture Organization (FAO) of the United Nations},
year = {2026},
url = {https://data.humdata.org/dataset/faostat-food-prices-for-morocco},
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



