Matplotlib: Matplotlib Markers

• Markers 

When you want to emphasize each point with a specified marker, you can use the argument marker. 

Example 

Mark each point with a circle.

import matplotlib.pyplot as plt 
import numpy as np

ypoints =([5, 8, 0, 8])
plt.plot (ypoints, marker = 'o')
plt.show()

 

Result

 

 

Mark each point with a star.

Result

 

• Marker Reference 

Marker	Description
'o'	Circle
'*'	Star
'.'	Point
','	Pixel
'x'	X
'X'	X (filled)
'+'	Plus
'P'	Plus (filled)
's'	Square
'D'	Diamond
'd'	Diamond (thin)
'p'	Pentagon
'H'	Hexagon
'h'	Hexagon
'v'	Triangle Down
'^'	Triangle Up
'<'	Triangle Left
'>'	Triangle Right
'1'	Tri Down
'2'	Tri Up
'3'	Tri Left
'4'	Tri Right
'|'	Vline
'_'	Hline

• Format Strings fmt 

You can also use shortcut string notation parameter to specify the marker which is called fmt. 

Fmt has the following syntax: 

 

marker \ line \ color 

 

Example 

import matplotlib.pyplot as plt 
import numpy as np 

ypoints = ([1,3,6,9]) 
plt.plot(ypoints, 'o:r')

plt.show()

 

Result

 

• Line Referecne 

Line Syntax	Description
'-'	Solid line
':'	Dotted line
'--'	Dashed line
'-.'	Dashed/dotted line

 

• Color Reference 

Color Syntax	Description
'r'	Red
'g'	Green
'b'	Blue
'c'	Cyan
'm'	Magenta
'y'	Yellow
'k'	Black
'w'	White

 

 

• Marker Size 

We can address the size of the marker by using ms.

 

Example 

Set the size of the markers to 20.

import matplotlib.pyplot as plt 
import numpy as np 

ypoints = ([2, 4, 8, 1]) 

plt.plot(ypoints, marker = 'X', ms = 12)
plt.show()

 

Result

 

• Marker Color

You can use the keyword argument markeredgecolor or mec to set the color of the edge of the marker. 

 

Example 

Set the EDGE color to red.

import matplotlib.pyplot as plt 
import numpy as np 

ypoints = ([2, 4, 8, 1]) 

plt.plot(ypoints, marker = 'X', ms = 12, mec = 'r')
plt.show()

Result

 

You can use mfc to fill the color of the marker. 

Example 

Set the FACE color to red.

import matplotlib.pyplot as plt 
import numpy as np 

ypoints = ([2, 4, 8, 1]) 

plt.plot(ypoints, marker = 'X', ms = 12, mfc = 'r')
plt.show()

 

Result 

 

You can also change the color with Hexadecimal color values. 

Example 

import matplotlib.pyplot as plt 
import numpy as np 

ypoints = ([2, 4, 8, 1]) 

plt.plot(ypoints, marker = '*', ms = 12, mec = '#4CAF50', mfc = '#4CAF50' )
plt.show()

 

Result

 

Or you can use 140 supported color names.

...
plt.plot(ypoints, marker = 'o', ms = 12, mec = 'hotpink', mfc = 'hotpink')
...

 

Result

 

 

Exercise 

Create a scatter plot using matplotlib.pyplot to visualize the relationship between two variables, 'X' and 'Y.' Use blue circular markers (o) with a size of 50, and label it 'Data Points.' Customize the marker style, size, and color to your preference to make the plot visually appealing.

import matplotlib.pyplot as plt 
import numpy as np 

xpoints= ([0, 4, 6, 2])
ypoints = ([3, 6, 7, 10])

plt.plot(xpoints, ypoints, marker= 'o', ms = 50, c= 'w', mec = 'hotpink', label = 'Data Points') 
plt.title('Scatter Plot Example')
plt.show()

Result