Python使用Matplotlib绘制三维散点图详解流程

# importing the necessary libraries  
import numpy as np  
import matplotlib.pyplot as plt  
from mpl_toolkits import mplot3d  
# generating  random dataset  
z = np.random.randint(80, size =(55))  
x = np.random.randint(60, size =(55))  
y = np.random.randint(64, size =(55))  
# Creating figures for the plot  
fig = plt.figure(figsize = (10, 7))  
ax = plt.axes(projection ="3d")  
# Creating a plot using the random datasets   
ax.scatter3D(x, y, z, color = "red")  
plt.title("3D scatter plot")  
# display the  plot  
plt.show()  

# importing the necessary libraries  
from mpl_toolkits import mplot3d  
import matplotlib.pyplot as plt  
import numpy as np  
# Creating random 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, 12))  
ax = plt.axes(projection ="3d")  
# Add x, and y gridlines for the figure  
ax.grid(b = True, color ='blue',linestyle ='-.', linewidth = 0.5,alpha = 0.3)  
# Creating the color map for the plot  
my_cmap = plt.get_cmap('hsv')  
# Creating the 3D plot  
sctt = ax.scatter3D(x, y, z,alpha = 0.8,c = (x + y + z),cmap = my_cmap,marker ='^')  
plt.title("3D scatter plot in Python")  
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 = 0.6, aspect = 5)  
# display the plot  
plt.show()