tabensemb.trainer.Trainer.plot_kde#
method
- Trainer.plot_kde(x_col: str, y_col: str | None = None, ax=None, clr: Iterable | None = None, imputed: bool = False, figure_kwargs: Dict | None = None, kdeplot_kwargs: Dict | None = None, select_by_value_kwargs: Dict | None = None, savefig_kwargs: Dict | None = None, save_show_close: bool = True) Axes[source]#
Plot the kernel density estimation of a feature or two features.
- Parameters:
- x_col
The investigated feature.
- y_col
If not None, a bi-variate distribution will be plotted.
- ax
matplotlib.axes.Axes- clr
A seaborn color palette or an Iterable of colors. For example seaborn.color_palette(“deep”).
- imputed
Whether the imputed dataset should be considered.
- figure_kwargs
Arguments for
plt.figure.- kdeplot_kwargs
Arguments for
seaborn.kdeplot- select_by_value_kwargs
Arguments for
tabensemb.data.datamodule.DataModule.select_by_value().- savefig_kwargs
Arguments for
plt.savefig- save_show_close
Whether to save, show (in the notebook), and close the figure if
axis not given.
- Returns:
- matplotlib.axes.Axes