plotnine.geoms.geom_vline

class plotnine.geoms.geom_vline(mapping=None, data=None, **kwargs)[source]

Vertical line

Usage

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

Only the mapping and data can be positional, the rest must be keyword arguments. **kwargs can be aesthetics (or parameters) used by the stat.

Parameters
mappingaes, optional

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.

datadataframe, optional

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.

statstr or stat, optional (default: 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.

positionstr or position, optional (default: position_identity)

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

na_rmbool, optional (default: False)

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

inherit_aesbool, optional (default: False)

If False, overrides the default aesthetics.

show_legendbool or dict, optional (default: 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.

Examples

[1]:
import pandas as pd
import numpy as np

from plotnine import *
from plotnine.data import *

%matplotlib inline

Vertical line

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

[2]:
mpg.head()
[2]:
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:

[3]:
(
    ggplot(mpg, aes(x='displ', y='hwy'))
    + geom_point()
    + labs(x='displacement', y='horsepower')
)
../_images/geom_vline_4_0.png
[3]:
<ggplot: (7012636557)>

Add a vertical line to the scatter plot:

[4]:
(
    ggplot(mpg, aes(x='displ', y='hwy'))
    + geom_point()
    + geom_vline(xintercept=5) # add one vertical line
    + labs(x='displacement', y='horsepower')
)
../_images/geom_vline_6_0.png
[4]:
<ggplot: (-9223372029839486972)>

You can add many vertical lines:

[5]:
(
    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')
)
../_images/geom_vline_8_0.png
[5]:
<ggplot: (-9223372029841960360)>
[ ]:

[6]:
(
    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')
)
../_images/geom_vline_10_0.png
[6]:
<ggplot: (-9223372029841746218)>

Add vertical lines to a facet plot:

[7]:
(
    ggplot(mpg, aes(x='displ', y='hwy'))
    + geom_point()
    + geom_vline(xintercept=5) # add a vertical line...
    + facet_grid('drv ~ .')      # ... to a facet plot
    + labs(x='displacement', y='horsepower')
)
../_images/geom_vline_12_0.png
[7]:
<ggplot: (-9223372029839459026)>