electricsheepafrica/africa-afdb-market-trends-2015

---
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-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- economics
- markets
- services
- dza
- ago
- ben
- bwa
- bfa
pretty_name: "AFDB Market Trends, 2015"
dataset_info:
splits:
- name: train
num_examples: 26992
- name: test
num_examples: 6748
---

# AFDB Market Trends, 2015

**Publisher:** African Development Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/afdb-market-trends-2015) · **License:** `cc-by` · **Updated:** 2023-03-02

---

## Abstract

AFDB Market Trends, January 2011 - July 2015

Each row in this dataset represents time-series observations. Temporal coverage is indicated by the `date` column(s). Geographic scope: **DZA, AGO, BEN, BWA, BFA, BDI, CPV, CMR, and 50 others**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Market and price monitoring |
| **Unit of observation** | Time-series observations |
| **Rows (total)** | 33,740 |
| **Columns** | 8 (2 numeric, 5 categorical, 1 datetime) |
| **Train split** | 26,992 rows |
| **Test split** | 6,748 rows |
| **Geographic scope** | DZA, AGO, BEN, BWA, BFA, BDI, CPV, CMR, and 50 others |
| **Publisher** | African Development Bank Group |
| **HDX last updated** | 2023-03-02 |

---

## Variables

**Geographic** — `frequency` (D).

**Temporal** — `date`.

**Outcome / Measurement** — `value` (range 0.6743–55188.34).

**Identifier / Metadata** — `indicatorname` (Tunisia Dinar, CFA zone Countries CFA Franc, Morocco Dirham), `esa_source` (HDX), `esa_processed` (2026-04-18).

**Other** — `indicator` (range 91241909.0–91245009.0), `unit` (USD/Troy Ounce, US cents/tonne, USD/lb).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-afdb-market-trends-2015")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `indicator` | int64 | 0.0% | 91241909.0 – 91245009.0 (mean 91243415.1944) |
| `indicatorname` | object | 0.0% | Tunisia Dinar, CFA zone Countries CFA Franc, Morocco Dirham |
| `unit` | object | 66.0% | USD/Troy Ounce, US cents/tonne, USD/lb |
| `frequency` | object | 0.0% | D |
| `date` | datetime64[ns] | 0.0% | |
| `value` | float64 | 0.0% | 0.6743 – 55188.34 (mean 4092.9563) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-18 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `indicator` | 91241909.0 | 91245009.0 | 91243415.1944 | 91243409.0 |
| `value` | 0.6743 | 55188.34 | 4092.9563 | 507.7654 |

---

## 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 African Development Bank Group and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `unit`.
- This dataset spans 58 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/afdb-market-trends-2015) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_afdb_market_trends_2015,
title = {AFDB Market Trends, 2015},
author = {African Development Bank Group},
year = {2023},
url = {https://data.humdata.org/dataset/afdb-market-trends-2015},
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.*