plot_correlation

---

method plot_correlation(columns=None, method="pearson", title=None, legend=None, figsize=(800, 700), filename=None, display=True)[source]

Plot a correlation matrix.

Displays a heatmap showing the correlation between columns in the dataset. The colors red, blue and white stand for positive, negative, and no correlation respectively.

Parameters

columns: segment, sequence, dataframe or None, default=None Columns to plot. If None, plot all columns in the dataset. Selected categorical columns are ignored. method: str, default="pearson" Method of correlation. Choose from: pearson, kendall or spearman. title: str, dict or None, default=None Title for the plot. If None, no title is shown. If str, text for the title. If dict, title configuration. legend: str, dict or None, default=None Do nothing. Implemented for continuity of the API. figsize: tuple, default=(800, 700) Figure's size in pixels, format as (x, y). filename: str, Path 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.

Returns

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

See Also

plot_distribution

Plot column distributions.

plot_qq

Plot a quantile-quantile plot.

plot_relationships

Plot pairwise relationships in a dataset.

Example

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

>>> X, y = load_breast_cancer(return_X_y=True, as_frame=True)

>>> atom = ATOMClassifier(X, y, random_state=1)
>>> atom.plot_correlation()