lets_plot.geom_qq2¶
- lets_plot.geom_qq2(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, **other_args)¶
Display quantile-quantile 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=’qq2’
The statistical transformation to use on the data for this layer, as a string. Supported transformations: ‘identity’ (leaves the data unchanged), ‘qq2’ (compare two probability distributions), ‘count’ (counts number of points with same x-axis coordinate), ‘bin’ (counts number of points with x-axis coordinate in the same bin), ‘smooth’ (performs smoothing - linear default), ‘density’ (computes and draws kernel density estimate).
- 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. Value None (or ‘none’) will disable sampling for this layer.
- tooltipslayer_tooltips
Result of the call to the layer_tooltips() function. Specifies appearance, style and content.
- 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
The Q-Q plot is used for comparing two probability distributions by plotting their quantiles against each other. A point (x, y) on the plot corresponds to one of the quantiles of the first distribution (x-coordinate) plotted against the same quantile of the second distribution (y-coordinate).
If the two distributions being compared are similar, the points in the Q-Q plot will approximately lie on the straight line.
geom_qq2() understands the following aesthetics mappings:
x : x-axis value.
y : y-axis value.
alpha : transparency level of a point. Understands numbers between 0 and 1.
color (colour) : color of a geometry. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.
fill : color to paint shape’s inner points. Is applied only to the points of shapes having inner points.
shape : shape of the point.
size : size of the point.
Examples
1import numpy as np 2from lets_plot import * 3LetsPlot.setup_html() 4n = 500 5np.random.seed(42) 6x = np.random.normal(0, 1, n) 7y = np.random.normal(1, 2, n) 8ggplot({'x': x, 'y': y}, aes('x', 'y')) + geom_qq2()