lets_plot.geom_abline

lets_plot.geom_abline(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, slope=None, intercept=None, **other_args)

Add a straight line with specified slope and intercept to the plot.

Parameters

mappingFeatureSpec

Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.

datadict or DataFrame or polars.DataFrame

The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.

statstr, default=’identity’

The statistical transformation to use on the data for this layer, as a string.

positionstr or FeatureSpec

Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.

show_legendbool, default=True

False - do not show legend for this layer.

samplingFeatureSpec

Result of the call to the sampling_xxx() function. To prevent any sampling for this layer pass value “none” (string “none”).

slopefloat

The line slope.

interceptfloat

The value of y at the point where the line crosses the y axis.

other_args

Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.

Returns

LayerSpec

Geom object specification.

Notes

geom_abline() understands the following aesthetics mappings:

• slope : line slope.

• intercept : line y-intercept.

• alpha : transparency level of a layer. Accept values between 0 and 1.

• color (colour) : color of the geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.

• size : lines width.

• linetype : type of the line. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.

Examples

from lets_plot import *
LetsPlot.setup_html()
ggplot() + geom_abline(slope=0)

import numpy as np
import pandas as pd
from lets_plot import *
LetsPlot.setup_html()
n, m = 10, 3
np.random.seed(42)
ids = np.arange(m).astype(str)
x = np.linspace(0, 1, n)
y = x + np.random.uniform(size=(m, n))
df = pd.DataFrame({'id': np.repeat(ids, n),
                   'x': np.tile(x, m),
                   'y': y.reshape(m * n)})
slope = np.corrcoef(y, x)[0, :-1] * y.std(axis=1) / x.std()
intercept = y.mean(axis=1) - slope * x.mean()
reg_df = pd.DataFrame({'id': ids, 'slope': slope, 'intercept': intercept})
ggplot() + \
    geom_abline(aes(slope='slope', intercept='intercept', color='id'), \
                data=reg_df, size=1, linetype='dashed') + \
    geom_point(aes(x='x', y='y', color='id', fill='id'), \
               data=df, size=4, shape=21, alpha=.5)