How to make a 4d plot using Python with matplotlib

Question

I am looking for a way to create four-dimensional plots (surface plus a color scale) using Python and matplotlib. I am able to generate the surface using the first three variables, but I am not having success adding the color scale for the fourth variable. Here is a small subset of my data below. Any help would be greatly appreciated. Thanks

Data Subset

var1    var2    var3    var4
10.39   73.32   2.02    28.26
11.13   68.71   1.86    27.83
12.71   74.27   1.89    28.26
11.46   91.06   1.63    28.26
11.72   85.38   1.51    28.26
13.39   78.68   1.89    28.26
13.02   68.02   2.01    28.26
12.08   64.37   2.18    28.26
11.58   60.71   2.28    28.26
8.94    65.67   1.92    27.04
11.61   59.57   2.32    27.52
19.06   74.49   1.69    63.35
17.52   73.62   1.73    63.51
19.52   71.52   1.79    63.51
18.76   67.55   1.86    63.51
19.84   53.34   2.3     63.51
20.19   59.82   1.97    63.51
17.43   57.89   2.05    63.38
17.9    59.95   1.89    63.51
18.97   57.84   2       63.51
19.22   57.74   2.05    63.51
17.55   55.66   1.99    63.51
19.22   101.31  6.76    94.29
19.41   99.47   6.07    94.15
18.99   94.01   7.32    94.08
19.88   103.57  6.98    94.58
19.08   95.38   5.66    94.14
20.36   100.43  6.13    94.47
20.13   98.78   7.37    94.47
20.36   89.36   8.79    94.71
20.96   84.48   8.33    94.01
21.02   83.97   6.78    94.72
19.6    95.64   6.56    94.57

Answer 1

To create the plot you want, we need to use matplotlib's plot_surface to plot Z vs (X,Y) surface, and then use the keyword argument facecolors to pass in a new color for each patch.

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm

# create some fake data
x = y = np.arange(-4.0, 4.0, 0.02)
# here are the x,y and respective z values
X, Y = np.meshgrid(x, y)
Z = np.sinc(np.sqrt(X*X+Y*Y))
# this is the value to use for the color
V = np.sin(Y)

# create the figure, add a 3d axis, set the viewing angle
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.view_init(45,60)

# here we create the surface plot, but pass V through a colormap
# to create a different color for each patch
ax.plot_surface(X, Y, Z, facecolors=cm.Oranges(V))