Matplotlib Scatter

• Creating Scatter Plots 

You can use the scatter() function to draw a scatter plot. 

 

Example 

import matplotlib.pyplot as plt 
import numpy as np 

x = np.array([1, 4, 6, 2])
y = np.array([4, 5, 2, 1])

plt.scatter(x, y)
plt.show()

Result 

 

• Compare plots

Example

import matplotlib.pyplot as plt
import numpy as np

#day one, the age and speed of 13 cars:
x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])
y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])
plt.scatter(x, y)

#day two, the age and speed of 15 cars:
x = np.array([2,2,8,1,15,8,12,9,7,3,11,4,7,14,12])
y = np.array([100,105,84,105,90,99,90,95,94,100,79,112,91,80,85])
plt.scatter(x, y)

plt.show()

Result 

 

• Adjusting the color 

You can use the c argument to adjust the color.

import matplotlib.pyplot as plt
import numpy as np

x = np.array([2,8,9,1])
y = np.array([5,5,5,5])
colors = np.array(["red","green","blue","magenta"])

plt.scatter(x, y, c=colors)

plt.show()

Result

 

• Size 

Use s argument to adjust the size of the dots.

 

Example

import matplotlib.pyplot as plt

# Sample data
x = [1, 2, 3, 4, 5]
y = [10, 20, 30, 40, 50]

# Define the size of dots
dot_size = [100, 200, 300, 400, 500]

# Create the scatter plot
plt.scatter(x, y, s=dot_size, label='Dots', c='blue')

# Add labels and a legend
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.legend()

# Show the plot
plt.show()

Result

 

• Alpha 

You can adjust the transparency of the dots with the alpha argument 

 

Example 

import matplotlib.pyplot as plt

# Sample data
x = [1, 2, 3, 4, 5]
y = [10, 20, 30, 40, 50]

# Define the size of dots
dot_size = [100, 200, 300, 400, 500]

# Create the scatter plot
plt.scatter(x, y, s=dot_size, label='Dots', c='blue', alpha =0.3)

# Add labels and a legend
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.legend()

# Show the plot
plt.show()

Result