Visualizing 3D clustering using matplotlib

Question

I have clustered 3 features Feature1, Feature2 and Feature3 and came up with 2 clusters. I am trying to visualize a 3D cluster using matplotlib.

In the below table, there are three features upon which the clustering is executed. Number of clusters is 2.

    Feature1        Feature2    Feature3    ClusterIndex
  0 1.349656e-09    1.000000    1.090542e-09    0
  1 1.029752e-07    1.000000    6.040669e-08    0
  2 2.311729e-07    1.000000    1.568289e-11    0
  3 1.455860e-08    6.05e-08    1.000000        1
  4 3.095807e-07    2.07e-07    1.000000        1

Tried this code:

   fig = plt.figure()
   ax = fig.add_subplot(111, projection='3d')
   x = np.array(df['Feature1'])
   y = np.array(df['Feature2'])
   z = np.array(df['Feature3'])
   ax.scatter(x,y,z, marker=colormap[kmeans.labels_], s=40)

However, I get the error "ValueError: could not convert string to float: red". The marker part is thus where I get the error.

2D visualization of clusters is pretty simple by plotting the points in a scatter plot and distinguishing it with cluster labels.

Just wondering is there a way to do 3D visualization of clusters.

Any suggestions would be highly appreciated !!

Answer 1

In principle, the code from the question should work. However it is unclear what marker=colormap[kmeans.labels_] would do and why it is needed.

The 3D scatter plot works exactly as the 2D version of it.

The marker argument would expect a marker string, like "s" or "o" to determine the marker shape.
The color can be set using the c argument. You can provide a single color or an array/a list of colors. In the example below we simply provide the cluster index to c and use a colormap.

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

v = np.random.rand(10,4)
v[:,3] = np.random.randint(0,2,size=10)
df = pd.DataFrame(v, columns=['Feature1', 'Feature2','Feature3',"Cluster"])
print (df)

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = np.array(df['Feature1'])
y = np.array(df['Feature2'])
z = np.array(df['Feature3'])

ax.scatter(x,y,z, marker="s", c=df["Cluster"], s=40, cmap="RdBu")

plt.show()