---
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
- tgo
pretty_name: "Togo - Food Prices"
dataset_info:
  splits:
    - name: train
      num_examples: 350
    - name: test
      num_examples: 87
---

# Togo - Food Prices

**Publisher:** Food and Agriculture Organization (FAO) of the United Nations · **Source:** [HDX](https://data.humdata.org/dataset/faostat-food-prices-for-togo) · **License:** `cc-by-igo` · **Updated:** 2026-03-30

---

## Abstract

Food Prices for Togo.

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: **TGO**.

*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** | TGO |
| **Publisher** | Food and Agriculture Organization (FAO) of the United Nations |
| **HDX last updated** | 2026-03-30 |

---

## Variables

**Geographic** — `iso3` (TGO), `year_code` (range 1970.0–2024.0), `year` (range 1970.0–2024.0).

**Temporal** — `startdate`, `enddate`.

**Outcome / Measurement** — `value` (range 5.1618–174.9819).

**Identifier / Metadata** — `area_code` (range 217.0–217.0), `area_code_m49` ('768), `item_code` (range 22024.0–22028.0), `element_code` (range 6179.0–62250.0), `esa_source` (HDX) and 1 others.

**Other** — `area` (Togo), `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-togo")
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% | TGO |
| `startdate` | datetime64[ns] | 0.0% |  |
| `enddate` | datetime64[ns] | 0.0% |  |
| `area_code` | int64 | 0.0% | 217.0 – 217.0 (mean 217.0) |
| `area_code_m49` | object | 0.0% | '768 |
| `area` | object | 0.0% | Togo |
| `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% | 5.1618 – 174.9819 (mean 71.14) |
| `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` | 217.0 | 217.0 | 217.0 | 217.0 |
| `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` | 5.1618 | 174.9819 | 71.14 | 72.3837 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_faostat_food_prices_for_togo,
  title     = {Togo - Food Prices},
  author    = {Food and Agriculture Organization (FAO) of the United Nations},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/faostat-food-prices-for-togo},
  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.*