Matplotlib

Customizing line appearance

In this lesson, you will learn how to change the appearance of the plot lines.

Let's generate some random data with NumPy and plot it:

import matplotlib.pyplot as plt
import numpy as np

# Generate data
np.random.seed(80)
y = np.cumsum(np.random.randn(100))
 
plt.plot(y)
 
plt.show()

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Output

Just by default, the figures generated by matplotlib look pretty nice.

Nevertheless, matplotlib offers countless customization options.

Let's take advantage of this and adjust the look of our line:

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(80)
y = np.cumsum(np.random.randn(100))
 
# customize style of line
plt.plot(y, linestyle='--', color='green', linewidth=1.5)
 
plt.show()

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Output

Here, we have changed the style, color, and width of the line.

The linestyle argument accepts specific values, which can either be symbols or descriptive names of the style:

# solid line
'-' or 'solid'
 
# dashed line
'--' or 'dashed'
 
# dotted line
':' or 'dotted'
 
# dash-dot line
'-.' or 'dashdot'
 
# no line
'' or 'none'

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Instead of specifying linestyle as an argument, you can also simply type ls. For instance:

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(80)
y = np.cumsum(np.random.randn(100))
 
# customize style of line
plt.plot(y, ls='-.')
 
plt.show()

Python

Output

You can even hightlight individual data points with markers using the marker argument:

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(80)
y = np.cumsum(np.random.randn(100))
 
# customize style of line
plt.plot(y, marker='.')
 
plt.show()

Python

Output

There are various possible markers that you can add.

Here are some of the most common ones:

'.' # point marker (small dot)
 
'o' # circle marker
 
's' # square marker
 
'*' # star marker
 
'+' # plus marker
 
'x' # X marker

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Great! Now you know many ways to adjust the appearance of the line.