matplotlib.axes.Axes.vlines() in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.vlines() Function

The Axes.vlines() function in axes module of matplotlib library is used to Plot vertical lines at each x from ymin to ymax.

Syntax: Axes.vlines(self, x, ymin, ymax, colors=’k’, linestyles=’solid’, label=”, *, data=None, **kwargs)

Parameters: This method accept the following parameters that are described below:

• x: This parameter is the sequence of x-indexes where to plot the lines.
• ymin, ymax: These parameter contains an array.And they represents the beginning and end of each line.
• colors: This parameter is an optional parameter. And it is the color of the lines with default value k.
• linetsyle: This parameter is also an optional parameter. And it is used to represent the linestyle{‘solid’, ‘dashed’, ‘dashdot’, ‘dotted’}.
• label: This parameter is also an optional parameter.It is the label of the plot.

Returns: This returns the LineCollection.

Below examples illustrate the matplotlib.axes.Axes.vlines() function in matplotlib.axes:

Example #1:

# Implementation of matplotlib function

import numpy as np
from matplotlib import patches
import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.vlines([1, 2, 3, 4], 0, 1,
          color ="green",
          transform = ax.get_xaxis_transform())

ax.set_title('matplotlib.axes.Axes.vlines Example')

plt.show()

Output:

Example #2:

# Implementation of matplotlib function

import numpy as np
from matplotlib import patches
import matplotlib.pyplot as plt

t = np.arange(0.0, 5.0, 0.1)
s = np.exp(-t) + np.cos(3 * np.pi * t) + np.sin(np.pi * t)
nse = np.random.normal(0.0, 0.8, t.shape) * s

fig, ax = plt.subplots()

ax.vlines(t, [0], s)
ax.vlines([1, 2], 0, 1, color ="lightgreen",
          transform = ax.get_xaxis_transform())

ax.set_xlabel('time (s)')
ax.set_title('matplotlib.axes.Axes.vlines Example')

plt.show()

Output: