# python – How to draw vertical lines on a given plot in matplotlib

## The Question :

307 people think this question is useful

Given a plot of signal in time representation, how to draw lines marking corresponding time index?

Specifically, given a signal plot with time index ranging from 0 to 2.6(s), I want to draw vertical red lines indicating corresponding time index for the list [0.22058956, 0.33088437, 2.20589566], how can I do it?

491 people think this answer is useful

The standard way to add vertical lines that will cover your entire plot window without you having to specify their actual height is plt.axvline

import matplotlib.pyplot as plt

plt.axvline(x=0.22058956)
plt.axvline(x=0.33088437)
plt.axvline(x=2.20589566)



OR

xcoords = [0.22058956, 0.33088437, 2.20589566]
for xc in xcoords:
plt.axvline(x=xc)



You can use many of the keywords available for other plot commands (e.g. color, linestyle, linewidth …). You can pass in keyword arguments ymin and ymax if you like in axes corrdinates (e.g. ymin=0.25, ymax=0.75 will cover the middle half of the plot). There are corresponding functions for horizontal lines (axhline) and rectangles (axvspan).

64 people think this answer is useful

For multiple lines

xposition = [0.3, 0.4, 0.45]
for xc in xposition:
plt.axvline(x=xc, color='k', linestyle='--')



41 people think this answer is useful

## If someone wants to add a legend and/or colors to some vertical lines, then use this:

import matplotlib.pyplot as plt

# x coordinates for the lines
xcoords = [0.1, 0.3, 0.5]
# colors for the lines
colors = ['r','k','b']

for xc,c in zip(xcoords,colors):
plt.axvline(x=xc, label='line at x = {}'.format(xc), c=c)

plt.legend()
plt.show()



Results:

30 people think this answer is useful

Calling axvline in a loop, as others have suggested, works, but can be inconvenient because

1. Each line is a separate plot object, which causes things to be very slow when you have many lines.
2. When you create the legend each line has a new entry, which may not be what you want.

Instead you can use the following convenience functions which create all the lines as a single plot object:

import matplotlib.pyplot as plt
import numpy as np

def axhlines(ys, ax=None, lims=None, **plot_kwargs):
"""
Draw horizontal lines across plot
:param ys: A scalar, list, or 1D array of vertical offsets
:param ax: The axis (or none to use gca)
:param lims: Optionally the (xmin, xmax) of the lines
:param plot_kwargs: Keyword arguments to be passed to plot
:return: The plot object corresponding to the lines.
"""
if ax is None:
ax = plt.gca()
ys = np.array((ys, ) if np.isscalar(ys) else ys, copy=False)
if lims is None:
lims = ax.get_xlim()
y_points = np.repeat(ys[:, None], repeats=3, axis=1).flatten()
x_points = np.repeat(np.array(lims + (np.nan, ))[None, :], repeats=len(ys), axis=0).flatten()
plot = ax.plot(x_points, y_points, scalex = False, **plot_kwargs)
return plot

def axvlines(xs, ax=None, lims=None, **plot_kwargs):
"""
Draw vertical lines on plot
:param xs: A scalar, list, or 1D array of horizontal offsets
:param ax: The axis (or none to use gca)
:param lims: Optionally the (ymin, ymax) of the lines
:param plot_kwargs: Keyword arguments to be passed to plot
:return: The plot object corresponding to the lines.
"""
if ax is None:
ax = plt.gca()
xs = np.array((xs, ) if np.isscalar(xs) else xs, copy=False)
if lims is None:
lims = ax.get_ylim()
x_points = np.repeat(xs[:, None], repeats=3, axis=1).flatten()
y_points = np.repeat(np.array(lims + (np.nan, ))[None, :], repeats=len(xs), axis=0).flatten()
plot = ax.plot(x_points, y_points, scaley = False, **plot_kwargs)
return plot



18 people think this answer is useful

In addition to the plt.axvline and plt.plot((x1, x2), (y1, y2)) OR plt.plot([x1, x2], [y1, y2]) as provided in the answers above, one can also use

plt.vlines(x_pos, ymin=y1, ymax=y2)



to plot a vertical line at x_pos spanning from y1 to y2 where the values y1 and y2 are in absolute data coordinates.

10 people think this answer is useful

## matplotlib.pyplot.vlines vs. matplotlib.pyplot.axvline

• The difference is that vlines accepts 1 or more locations for x, while axvline permits one location.
• Single location: x=37
• Multiple locations: x=[37, 38, 39]
• vlines takes ymin and ymax as a position on the y-axis, while axvline takes ymin and ymax as a percentage of the y-axis range.
• When passing multiple lines to vlines, pass a list to ymin and ymax.
• If you’re plotting a figure with something like fig, ax = plt.subplots(), then replace plt.vlines or plt.axvline with ax.vlines or ax.axvline, respectively.
import numpy as np
import matplotlib.pyplot as plt

xs = np.linspace(1, 21, 200)

plt.figure(figsize=(10, 7))

# only one line may be specified; full height
plt.axvline(x=36, color='b', label='axvline - full height')

# only one line may be specified; ymin &amp; ymax spedified as a percentage of y-range
plt.axvline(x=36.25, ymin=0.05, ymax=0.95, color='b', label='axvline - % of full height')

# multiple lines all full height
plt.vlines(x=[37, 37.25, 37.5], ymin=0, ymax=len(xs), colors='purple', ls='--', lw=2, label='vline_multiple - full height')

# multiple lines with varying ymin and ymax
plt.vlines(x=[38, 38.25, 38.5], ymin=[0, 25, 75], ymax=[200, 175, 150], colors='teal', ls='--', lw=2, label='vline_multiple - partial height')

# single vline with full ymin and ymax
plt.vlines(x=39, ymin=0, ymax=len(xs), colors='green', ls=':', lw=2, label='vline_single - full height')

# single vline with specific ymin and ymax
plt.vlines(x=39.25, ymin=25, ymax=150, colors='green', ls=':', lw=2, label='vline_single - partial height')

# place legend outside
plt.legend(bbox_to_anchor=(1.0, 1), loc='upper left')

plt.show()