How to make these sequential histogram/density estimates plots

Does anyone know how to make these sequential histogram/density estimates plots (source) in R or Python? I think I've also heard them called "waterfall" plots and "cascade" plots. It also kind of looks like the cover art of Joy Division's "Unknown Pleasures" album (c.f. that very popular t-shirt).

Here's another example, from a book I like:

As a python example from [matplotlib examples][1]https://matplotlib.org/examples/mplot3d/polys3d_demo.html

    """
=============================================
Generate polygons to fill under 3D line graph
=============================================

Demonstrate how to create polygons which fill the space under a line
graph. In this example polygons are semi-transparent, creating a sort
of 'jagged stained glass' effect.
"""

from mpl_toolkits.mplot3d import Axes3D
from matplotlib.collections import PolyCollection
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
import numpy as np


fig = plt.figure()
ax = fig.gca(projection='3d')


def cc(arg):
    return mcolors.to_rgba(arg, alpha=0.6)

xs = np.arange(0, 10, 0.4)
verts = []
zs = [0.0, 1.0, 2.0, 3.0]
for z in zs:
    ys = np.random.rand(len(xs))
    ys[0], ys[-1] = 0, 0
    verts.append(list(zip(xs, ys)))

poly = PolyCollection(verts, facecolors=[cc('r'), cc('g'), cc('b'),
                                         cc('y')])
poly.set_alpha(0.7)
ax.add_collection3d(poly, zs=zs, zdir='y')

ax.set_xlabel('X')
ax.set_xlim3d(0, 10)
ax.set_ylabel('Y')
ax.set_ylim3d(-1, 4)
ax.set_zlabel('Z')
ax.set_zlim3d(0, 1)

plt.show()

The idea is to create the 3d line plot line by line and let each line define a polygone with a semi-transperent color to achieve a nice effect. To make it look even more like the one in your example, simple switch the color values and make the offset between the lines a little smaller.

EDIT: I made an example for you based on the original code:

xs = np.arange(0, 10, 0.4)
verts = []
zs = np.arange(0, 5, 0.2)
for z in zs:
    r=[int(np.random.normal(5,5)) for i in range(0,10000)]
    ys = np.histogram(r,len(xs))[0]/10000
    ys[0], ys[-1] = 0, 0
    verts.append(list(zip(xs, ys)))

poly = PolyCollection(verts,facecolor='white')
poly.set_edgecolor('black')

This should come quite close to the effect you are looking for.