TableReportDisplay#

class skore.TableReportDisplay(summary)[source]#

Display reporting information about a given dataset.

This display summarizes the dataset and provides a way to visualize the distribution of its columns.

Parameters:
summarydict

The summary of the dataset, as returned by summarize_dataframe.

Attributes:
ax_matplotlib axes

The axes of the figure.

figure_matplotlib figure.

The figure of the plot.

Examples

>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.linear_model import LogisticRegression
>>> from skore import train_test_split
>>> from skore import EstimatorReport
>>> X, y = load_breast_cancer(return_X_y=True)
>>> split_data = train_test_split(X=X, y=y, random_state=0, as_dict=True)
>>> classifier = LogisticRegression(max_iter=10_000)
>>> report = EstimatorReport(classifier, **split_data)
>>> display = report.data.analyze()
>>> display.plot(kind="corr")
frame(*, kind='dataset')[source]#

Get the data related to the table report.

Parameters:
kind{‘dataset’, ‘top-associations’}

The kind of data to return.

Returns:
DataFrame

The dataset used to create the table report.

help()[source]#

Display available attributes and methods using rich.

set_style(**kwargs)[source]#

Set the style parameters for the display.

Parameters:
**kwargsdict

Style parameters to set. Each parameter name should correspond to a a style attribute passed to the plot method of the display.

Returns:
selfobject

Returns the instance itself.

Raises:
ValueError

If a style parameter is unknown.

static style_plot(plot_func)[source]#

Apply consistent style to skore displays.

This decorator: 1. Applies default style settings 2. Executes plot_func 3. Applies tight_layout

Parameters:
plot_funccallable

The plot function to be decorated.

Returns:
callable

The decorated plot function.