dabl.plot(X, y=None, target_col=None, type_hints=None, scatter_alpha='auto', scatter_size='auto', verbose=10, plot_pairwise=True, **kwargs)[source]

Automatic plots for classification and regression.

Determines whether the target is categorical or continuous and plots the target distribution. Then calls the relevant plotting functions accordingly.


Input features. If target_col is specified, X also includes the target.

ySeries or numpy array, optional.

Target. You need to specify either y or target_col.

target_colstring or int, optional

Column name of target if included in X.

type_hintsdict or None

If dict, provide type information for columns. Keys are column names, values are types as provided by detect_types.

scatter_alphafloat, default=’auto’

Alpha values for scatter plots. ‘auto’ is dirty hacks.

scatter_sizefloat, default=’auto’.

Marker size for scatter plots. ‘auto’ is dirty hacks.

plot_pairwisebool, default=True

Whether to include pairwise scatterplots for classification. These can be somewhat expensive to compute.

verboseint, default=10

Controls the verbosity (output).

See also

plot_regression_continuous, plot_regression_categorical, plot_classification_continuous, plot_classification_categorical