Bivariate univariate charts

daspi.plotlib.precast.BivariateUnivariateCharts(source, target, feature, hue='', dodge_univariates=False, categorical_feature_univariates=False, ratios=[3, 1], stretch_figsize=False, colors=())

Bases: JointChart

Provides a set of charts for visualizing the relationship between a target variable and a feature variable.

This class prepares a grid for drawing a bivariate plot with marginal univariate plots: - Bottom left there is a large square axis for the bivariate diagram. For example, use a LinearRegressionLine plotter to show the dependence of the target variable on the feature variable. - Top left there is a small square axis for the univariate plot of the feature variable. - Bottom right there is a small square axis for the univariate plot of the target variable. - Top right there is a small square axis hidden as soon a plot is done.

PARAMETER	DESCRIPTION
source	The source data. TYPE: DataFrame
target	The target (dependant) variable. TYPE: str
feature	The feature (independant) variable. TYPE: str
hue	The hue variable. TYPE: str DEFAULT: ''
dodge_univariates	Whether to dodge the univariate plots, by default False. TYPE: bool DEFAULT: False
categorical_feature_univariates	Whether to treat the feature variable for univariate charts as categorical, by default False. TYPE: bool DEFAULT: False
ratios	The ratios of the bivariate axes height to the univariate axes height, by default [4, 1]. TYPE: List[float] DEFAULT: [3, 1]
stretch_figsize	If True, the height and width of the figure are stretched based on the number rows and columns in the axes grid. If a float is provided, the figure size is stretched by the given factor. If a tuple of two floats is provided, the figure size is stretched by the given factors for the x and y axis, respectively. by default False. TYPE: bool | float | Tuple[float, float] DEFAULT: False
colors	Tuple of unique colors used for hue categories as hex or str. If not provided, the default colors will be used, by default (). TYPE: Tuple[str, ...] DEFAULT: ()

Examples:

import daspi as dsp

df = dsp.load_dataset('painkillers-dissolution')
hue = 'brand'
n_groups = df.groupby(hue).ngroups
chart = dsp.BivariateUnivariateCharts(
        source=df,
        target='dissolution',
        feature='temperature',
        hue=hue,
        dodge_univariates=True,
    ).plot_univariates(
        dsp.MeanTest, n_groups=n_groups
    ).plot_univariates(
        dsp.QuantileBoxes, strategy='data'
    ).plot_bivariate(
        dsp.LinearRegressionLine, show_fit_ci=True
    ).label(
        fig_title='Regression and distribution analysis',
        sub_title='Painkillers dissolution time vs. temperature',
        feature_label='Water temperature (°C)',
        target_label='Dissolution time (s)',
        axes_titles=('95 % Bonferroni confidence interval of mean', '', '', ''),
        info=True
    )

Information about which distribution is used to calculate the quantile boxes can be obtained as follows:

brands = (brand for brand in df[hue].unique().tolist()*2)
for plot in chart.plots:
    if isinstance(plot, dsp.QuantileBoxes):
        print(f'{next(brands)} {plot.target}: {plot.estimation.dist.dist_name}')

hidden_ax property

Get the top right axis (read-only).

univariate_axs property

Get the univariate axes (read-only).

bivariate_ax property

Get the bivariate axis (read-only).

hide_top_right_ax()

Hides the top right axis if it is not already hidden.

plot_univariates(plotter, *, kw_call={}, kw_where={}, **kwds)

Plots the univariate plots on the top left and bottom right axes.

PARAMETER	DESCRIPTION
plotter	The plotter to use for the univariate plots. TYPE: Type[Plotter]
kw_call	Additional keyword arguments for the plotter call method. TYPE: Dict[str, Any] DEFAULT: {}
kw_where	Additional keyword arguments for the where method used to filter the data. TYPE: Dict[str, Any] DEFAULT: {}
**kwds	Additional keyword arguments to be passed to the super plot method. DEFAULT: {}

RETURNS	DESCRIPTION
Self	The BivariateUnivariateCharts instance, for method chaining.

plot_bivariate(plotter, *, kw_call={}, kw_where={}, **kwds)

Plots the bivariate plot on the bottom left axis.

PARAMETER	DESCRIPTION
plotter	The plotter to use for the univariate plots. TYPE: Type[Plotter]
kw_call	Additional keyword arguments for the plotter call method. TYPE: Dict[str, Any] DEFAULT: {}
kw_where	Additional keyword arguments for the where method used to filter the data. TYPE: Dict[str, Any] DEFAULT: {}
**kwds	Additional keyword arguments to be passed to the super plot method. DEFAULT: {}

RETURNS	DESCRIPTION
Self	The BivariateUnivariateCharts instance, for method chaining.

label(*, fig_title='', sub_title='', feature_label='', target_label='', info=False, axes_titles=(), rows=(), cols=(), row_title='', col_title='')

Add labels and titles to the chart.

This method sets various labels and titles for the chart, including figure title, subplot title, axis labels, row and column titles, and additional information.

PARAMETER	DESCRIPTION
fig_title	The main title for the entire figure, by default ''. TYPE: str DEFAULT: ''
sub_title	The subtitle for the entire figure, by default ''. TYPE: str DEFAULT: ''
feature_label	The label for the feature variable (x-axis), by default ''. If set to True, the feature variable name will be used. If set to False or None, no label will be added. TYPE: str | bool | None DEFAULT: ''
target_label	The label for the target variable (y-axis), by default ''. If set to True, the target variable name will be used. If set to False or None, no label will be added. TYPE: str | bool | None DEFAULT: ''
info	Additional information to display on the chart. If True, the date and user information will be automatically added at the lower left corner of the figure. If a string is provided, it will be shown next to the date and user, separated by a comma. By default, no additional information is displayed. TYPE: bool | str DEFAULT: False
axes_titles	Title for each Axes, by default () TYPE: Tuple[str, ...] DEFAULT: ()
rows	The row labels of the figure, by default (). TYPE: Tuple[str, ...] DEFAULT: ()
cols	The column labels of the figure, by default (). TYPE: Tuple[str, ...] DEFAULT: ()
row_title	The title of the rows, by default ''. TYPE: str DEFAULT: ''
col_title	The title of the columns, by default ''. TYPE: str DEFAULT: ''

RETURNS	DESCRIPTION
Self	The BivariateUnivariateCharts instance, for method chaining.

Notes

This method allows customization of chart labels and titles to enhance readability and provide context for the visualized data.