Resid Plot¶

Plot the residuals of a linear regression.

plot: 'residplot'

Plot-Specific Parameters

lowess (bool or None, default: False): Fit a lowess smoother to the residual scatterplot.
x_partial (str or None, default: None): Confounding variables to regress out of the x variable before plotting.
y_partial (str or None, default: None): Confounding variables to regress out of the y variable before plotting.
order (int or None, default: 1): Order of the polynomial to fit when calculating the residuals.
robust (bool or None, default: False): Fit a robust linear regression when calculating the residuals.
dropna (bool or None, default: True): If True, ignore observations with missing data when fitting and plotting.
label (str or None, default: None): Label that will be used in any plot legends.
color (matplotlib.colors or None, default: None): Color to use for all elements of the plot.
scatter_kws (dict or None, default: None): Additional keyword arguments to pass to plt.scatter.
line_kws (dict or None, default: None): Additional keyword arguments to pass to plt.plot.

from grplot import plot2d
import grplot_seaborn as gs
gs.set_theme(context='notebook', style='darkgrid', palette='deep')

tips = gs.load_dataset('tips')
ax = plot2d(plot='residplot',
            df=tips.head(10),
            x='tip',
            y='total_bill',
            sep='.c',
            text=True,
            tick_add='Rp(_)',
            title='total_bill vs tip rate')