# Loading Dataset

SDGnE provides a demo dataset that helps you get started. You can load the demo dataset as below.

```python
from sdgne.demodata.demodataset import download_demodata

dataset = download_demodata()
```

The demo dataset contains 25 columns among which we include a *class* column. \
The class column helps us identify the minority class, for which we would like to generate synthetic data.

Below, we show a few columns from the dataset.

<table data-full-width="false"><thead><tr><th width="151">y_am_pef</th><th width="140">tempin</th><th data-type="number">humidin</th><th>.</th><th>.</th><th>class</th></tr></thead><tbody><tr><td>0.264</td><td>0.671</td><td>0.423</td><td>.</td><td>.</td><td>1</td></tr><tr><td>0.475</td><td>0.767</td><td>0.557</td><td>.</td><td>.</td><td>1</td></tr><tr><td>0.39</td><td>0.847</td><td>0.56</td><td>.</td><td>.</td><td>0</td></tr></tbody></table>

{% hint style="danger" %}
SDGnE requires all values to be scaled using min-max scaling to generate synthetic data.
{% endhint %}