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plot_qq

method plot_qq(columns=0, distributions="norm", title=None, legend="lower right", figsize=(900, 600), filename=None, display=True)[source]
Plot a quantile-quantile plot.

Columns are distinguished by color and the distributions are distinguished by marker type. Missing values are ignored.

Parameterscolumns: int, str, slice or sequence, default=0
Columns to plot. Selected categorical columns are ignored.

distributions: str or sequence, default="norm"
Names of the scipy.stats distributions to fit to the columns.

title: str, dict or None, default=None
Title for the plot.

legend: str, dict or None, default="lower right"
Legend for the plot. See the user guide for an extended description of the choices.

  • If None: No legend is shown.
  • If str: Location where to show the legend.
  • If dict: Legend configuration.

figsize: tuple, default=(900, 600)
Figure's size in pixels, format as (x, y).

filename: str or None, default=None
Save the plot using this name. Use "auto" for automatic naming. The type of the file depends on the provided name (.html, .png, .pdf, etc...). If filename has no file type, the plot is saved as html. If None, the plot is not saved.

display: bool or None, default=True
Whether to render the plot. If None, it returns the figure.

Returnsgo.Figure or None
Plot object. Only returned if display=None.


See Also

plot_correlation

Plot a correlation matrix.

plot_distribution

Plot column distributions.

plot_relationships

Plot pairwise relationships in a dataset.


Example

>>> from atom import ATOMClassifier
>>> from sklearn.datasets import load_breast_cancer

>>> atom = ATOMClassifier(X, y)
>>> atom.plot_qq(columns=[5, 6])

>>> atom.plot_qq(columns=0, distributions=["norm", "invgauss", "triang"])