# Version 1: calling invert_yaxis() after populating the plot.
# Version 2 (omitted): calling invert_yaxis() after ax = fig.add_subplot(111, projection='3d')
# Using the official 3D scatter plot example. 

from mpl_toolkits.mplot3d import Axes3D 

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(19680801)

def randrange(n, vmin, vmax):
    '''
    Helper function to make an array of random numbers having shape (n, )
    with each number distributed Uniform(vmin, vmax).
    '''
    return (vmax - vmin)*np.random.rand(n) + vmin

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

n = 100

# For each set of style and range settings, plot n random points in the box
# defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].
for m, zlow, zhigh in [('o', -50, -25), ('^', -30, -5)]:
    xs = randrange(n, 23, 32)
    ys = randrange(n, 0, 100)
    zs = randrange(n, zlow, zhigh)
    ax.scatter(xs, ys, zs, marker=m)

ax.invert_yaxis()
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()