plotnine.geom_vline

geom_vline(
    mapping=None,
    data=None,
    *,
    stat="identity",
    position="identity",
    na_rm=False,
    inherit_aes=False,
    show_legend=None,
    raster=False,
    **kwargs
)

Vertical line

Parameters

mapping : aes = None

Aesthetic mappings created with aes. If specified and inherit_aes=True, it is combined with the default mapping for the plot. You must supply mapping if there is no plot mapping.

Aesthetic	Default value
xintercept
alpha	`1`
color	`'black'`
group
linetype	`'solid'`
size	`0.5`

The bold aesthetics are required.

data : DataFrame = None

The data to be displayed in this layer. If None, the data from from the ggplot() call is used. If specified, it overrides the data from the ggplot() call.

stat : str | stat = "identity"

The statistical transformation to use on the data for this layer. If it is a string, it must be the registered and known to Plotnine.

position : str | position = "identity"

Position adjustment. If it is a string, it must be registered and known to Plotnine.

na_rm : bool = False

If False, removes missing values with a warning. If True silently removes missing values.

inherit_aes : bool = False

If False, overrides the default aesthetics.

show_legend : bool | dict = None

Whether this layer should be included in the legends. None the default, includes any aesthetics that are mapped. If a bool, False never includes and True always includes. A dict can be used to exclude specific aesthetis of the layer from showing in the legend. e.g show_legend={'color': False}, any other aesthetic are included by default.

raster : bool = False

If True, draw onto this layer a raster (bitmap) object even ifthe final image is in vector format.

**kwargs : Any = {}

Aesthetics or parameters used by the stat.

Examples


from plotnine import (
    ggplot,
    aes,
    geom_point,
    geom_vline,
    facet_grid,
    labs,
    element_rect,
    theme,
    theme_matplotlib,
    theme_set,
)
from plotnine.data import mpg

# Set default theme
# matplotlib + the background of 538
theme_set(
    theme_matplotlib()
    + theme(
        plot_background=element_rect(fill="#F0F0F0"),
        panel_background=element_rect(fill="#F0F0F0"),
        panel_spacing=0.015,
        
    )
)

Vertical line

geom_vline() draws a vertical line, and is useful as a guide.

mpg.head()

	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
0	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
1	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
2	audi	a4	2.0	2008	4	manual(m6)	f	20	31	p	compact
3	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact

It’s useful to use geom_vline() with some data, so we start with a basic scatter plot:

(
    ggplot(mpg, aes(x="displ", y="hwy"))
    + geom_point()
    + labs(x="displacement", y="horsepower")
)

Add a vertical line to the scatter plot:

(
    ggplot(mpg, aes(x="displ", y="hwy"))
    + geom_point()
    + geom_vline(xintercept=5)  # add one vertical line
    + labs(x="displacement", y="horsepower")
)

You can add many vertical lines:

(
    ggplot(mpg, aes(x="displ", y="hwy"))
    + geom_point()
    + geom_vline(xintercept=[4, 5, 7])  # add many vertical lines using a list
    + labs(x="displacement", y="horsepower")
)

(
    ggplot(mpg, aes(x="displ", y="hwy"))
    + geom_point()
    + geom_vline(
        xintercept=[4, 5, 7],
        colour=["red", "orange", "green"],  # add colour
        size=[1, 2, 3],  # set line thickness
        linetype="dotted",  # set line type
    )
    + labs(x="displacement", y="horsepower")
)

Add vertical lines to a facet plot:

Facets with a Vertical Line

# Gallery, lines
(
    ggplot(mpg, aes(x="displ", y="hwy"))
    + geom_point()
    + geom_vline(xintercept=5, color="brown", size=1)  # add a vertical line...
    + facet_grid("drv")  # ... to a facet plot
    + labs(x="displacement", y="horsepower")
)

Source: Set default theme