File size: 4,392 Bytes
c4055f7 08f4d6e c4055f7 08f4d6e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 | ---
license: other
language:
- en
task_categories:
- tabular-classification
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- 1K<n<10K
tags:
- tabular
- africa
- un-comtrade
- international-merchandise-trade
- trade
- exports-imports
- hs
- bilateral
- time-series
pretty_name: "Cabo Verde — Imports by Trading Partner | Africa (UN Comtrade)"
---
# Cabo Verde — Imports by Trading Partner | Africa (UN Comtrade)
🌍 **3,208 observations** · **1 Africa countries** · **2000–2023** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
    
## TL;DR
This dataset contains **3,208 observations** of `International merchandise trade` data across **1 Africa countries**, spanning **2000–2023**, covering **214 distinct indicators**.
## About the source
- **Source:** [UN Comtrade](https://comtradeplus.un.org/)
- **Publisher:** United Nations Statistics Division (UN Comtrade)
- **License:** [other](https://comtradeplus.un.org/TermsOfUse)
- **Topic:** International merchandise trade
## Geographic coverage
1 Africa countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---------|-----:|-----------:|----------:|
| `Cabo Verde` | 3,208 | 2000 | 2023 |
## Indicators (sample)
- `Afghanistan` — Afghanistan
- `Albania` — Albania
- `Algeria` — Algeria
- `American Samoa` — American Samoa
- `Andorra` — Andorra
- `Angola` — Angola
- `Anguilla` — Anguilla
- `Antarctica` — Antarctica
- `Antigua and Barbuda` — Antigua and Barbuda
- `Areas, nes` — Areas, nes
- _... and 204 more indicators_
## Schema
| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `country_name` | `string` | — | `Cabo Verde` |
| `country_iso3` | `string` | — | `CPV` |
| `partner_name` | `string` | — | `Angola` |
| `partner_iso3` | `string` | — | `AGO` |
| `year` | `int64` | — | `2000` |
| `flow` | `string` | — | `imports` |
| `trade_value_usd` | `float64` | — | `3106.0` |
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-comtrade-cabo-verde-imports-by-partner")
df = ds["train"].to_pandas()
print(df.head())
```
### Filter to one country
```python
kenya = df[df["country_name"] == "KEN"]
```
### Time-series for a single indicator
```python
sample = (df[df["partner_name"] == "Angola"]
.sort_values("year"))
sample.plot(x="year", y="trade_value_usd", title="Angola")
```
### Pivot to country × year matrix
```python
matrix = (df[df["partner_name"] == "Angola"]
.pivot_table(index="year", columns="country_name", values="trade_value_usd"))
print(matrix.tail())
```
## Citation
```bibtex
@misc{africa_comtrade_cabo_verde_imports_by_partner_2023,
title = {Cabo Verde — Imports by Trading Partner | Africa (UN Comtrade)},
author = {United Nations Statistics Division (UN Comtrade)},
year = {2023},
url = {https://comtradeplus.un.org/},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-comtrade-cabo-verde-imports-by-partner}}
}
```
## License
Released under [other](https://comtradeplus.un.org/TermsOfUse).
Original data © United Nations Statistics Division (UN Comtrade). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
## About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds.
Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
---
_Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://comtradeplus.un.org/_
|