- lets_plot.geom_vline(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, xintercept=None, **other_args)¶
Add a straight vertical line to the plot.
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
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.
Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.
Result of the call to the layer_tooltips() function. Specifies appearance, style and content.
The value of x at the point where the line crosses the x axis.
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.
Geom object specification.
geom_hline() understands the following aesthetics mappings:
xintercept : line x-intercept.
alpha : transparency level of a layer. Understands numbers between 0 and 1.
color (colour) : color of a geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.
size : lines width. Defines line width.
linetype : type of the line. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.
1from lets_plot import * 2LetsPlot.setup_html() 3ggplot() + geom_vline(xintercept=0)