A 3D Scatter Plot is a mathematical diagram, the most basic version of three-dimensional plotting used to display the properties of data as three variables of a dataset using the cartesian coordinates.To create a 3D Scatter plot, Matplotlib’s mplot3d toolkit is used to enable three dimensional plotting.Generally 3D scatter plot is created by using ax.scatter3D() the function of the matplotlib library which accepts a data sets of X, Y and Z to create the plot while the rest of the attributes of the function are the same as that of two dimensional scatter plot.
Example 1: Let’s create a basic 3D scatter plot using the ax.scatter3D() function.
Python3
# Import libraries from mpl_toolkits import mplot3d import numpy as np import matplotlib.pyplot as plt # Creating dataset z = np.random.randint( 100 , size = ( 50 )) x = np.random.randint( 80 , size = ( 50 )) y = np.random.randint( 60 , size = ( 50 )) # Creating figure fig = plt.figure(figsize = ( 10 , 7 )) ax = plt.axes(projection = "3d" ) # Creating plot ax.scatter3D(x, y, z, color = "green" ) plt.title( "simple 3D scatter plot" ) # show plot plt.show() |
Output :
Example 2 : For better understanding Let’s take another example.
Python3
# Import libraries from mpl_toolkits import mplot3d import numpy as np import matplotlib.pyplot as plt # Creating dataset z = 4 * np.tan(np.random.randint( 10 , size = ( 500 ))) + np.random.randint( 100 , size = ( 500 )) x = 4 * np.cos(z) + np.random.normal(size = 500 ) y = 4 * np.sin(z) + 4 * np.random.normal(size = 500 ) # Creating figure fig = plt.figure(figsize = ( 16 , 9 )) ax = plt.axes(projection = "3d" ) # Add x, y gridlines ax.grid(b = True , color = 'grey' , linestyle = '-.' , linewidth = 0.3 , alpha = 0.2 ) # Creating color map my_cmap = plt.get_cmap( 'hsv' ) # Creating plot sctt = ax.scatter3D(x, y, z, alpha = 0.8 , c = (x + y + z), cmap = my_cmap, marker = '^' ) plt.title( "simple 3D scatter plot" ) ax.set_xlabel( 'X-axis' , fontweight = 'bold' ) ax.set_ylabel( 'Y-axis' , fontweight = 'bold' ) ax.set_zlabel( 'Z-axis' , fontweight = 'bold' ) fig.colorbar(sctt, ax = ax, shrink = 0.5 , aspect = 5 ) # show plot plt.show() |
Output :
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