A good starting place:

matplotlib.org/mpl_toolkits/mplot3d/tutorial.html

Simple 3D scatter plot

Preliminary

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np

Data : create matrix X,Y,Z

X=[ [ i for i in range(0,10) ], ]*10
Y=np.transpose(X)

Z=[]
for i in range(len(X)):
    R=[]
    for j in range(len(Y)):
        if i==j: R.append(2)
        else: R.append(1)
    Z.append(R)

X:

[[0, 1, 2, 3, 4],
 [0, 1, 2, 3, 4],
 [0, 1, 2, 3, 4],
 [0, 1, 2, 3, 4],
 [0, 1, 2, 3, 4]]

Y:

[[0, 0, 0, 0, 0],
 [1, 1, 1, 1, 1],
 [2, 2, 2, 2, 2],
 [3, 3, 3, 3, 3],
 [4, 4, 4, 4, 4]])

Z:

[[2, 1, 1, 1, 1],
 [1, 2, 1, 1, 1],
 [1, 1, 2, 1, 1],
 [1, 1, 1, 2, 1],
 [1, 1, 1, 1, 2]]

Scatter plot

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(X, Y, Z)
plt.show()

Wireframe plot

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from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
import math


# create matrix X,Y,Z
X=[ [ i for i in range(0,25) ], ]*25
Y=np.transpose(X)

Z=[]
for i in range(len(X)):
    R=[]
    for j in range(len(Y)):
        z=math.sin( float(X[i][j])* 2.0*math.pi/25.0) * math.sin( float(Y[i][j])* 2.0*math.pi/25.0)
        R.append(z)
    Z.append(R)

# plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X, Y, Z)
plt.show()