The function seasonal_plot in the hana_ml.visualizers.eda module plots time series data by year, taking parameters such as data, column name, ID column name, axes for the plot, whether to use plotly instead of matplotlib, a plotly graph object, and other optional properties, and returns either a matplotlib.axes.Axes object or a plotly.graph_objects.Figure object.
------
Here is a Python code template for the `seasonal_plot` function from the `hana_ml.visualizers.eda` module:

```python
# Import required module
from hana_ml.visualizers.eda import seasonal_plot

# Assuming that `df` is your HANA DataFrame
# Define the column name of the time series data
col = "your_column_name"

# Define the ID column name (optional)
key = "your_id_column_name"

# Use plotly instead of matplotlib (optional)
enable_plotly = True

# Define the axes for the plot (optional)
ax = None

# Define the plotly graph object (optional)
fig = None

# Define additional properties for plotly (optional)
kwargs = {}

# Call the function
seasonal_plot(data=df, col=col, key=key, ax=ax, enable_plotly=enable_plotly, fig=fig, **kwargs)
```

Please replace `"your_column_name"` and `"your_id_column_name"` with your actual column names. If you don't have an ID column, you can omit the `key` parameter. The `ax` parameter is for the axes of the plot and is optional. If `enable_plotly` is set to `True`, the function will use plotly for plotting instead of matplotlib. The `fig` parameter is for the plotly graph object and is optional. The `kwargs` parameter is for additional properties for plotly and is optional.