Get mappings of all possible three-dimensional visualisations with python

Question

I have a dataframe with five columns. I have written a code for three-dimensional scatter for three columns from it:

from mpl_toolkits import mplot3d

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

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

ax = plt.axes(projection='3d')
ax.scatter(df[['col1']],df[['col2']],df[['col3']], cmap='viridis', linewidth=0.5)

It gives me scatter like this:

But I have 5 columns and i want to see all possible 3D scatter plots from them: (col1, col4, col5), (col2, col3, col5), .....

How could i do that?

Answer 1

What about using itertools?

from itertools import combinations 
com = combinations(['col1','col2','col3','col4','col5'], 3)  
for i in com:  
    print(i)

Something like:

from itertools import combinations 
comb = combinations(['col1','col2','col3','col4','col5'], 3)  
for i in list(comb): 
    fig = plt.figure()
    ax = plt.axes(projection='3d')
    ax.scatter(df[[i[0]]],df[[i[1]]],df[[i[2]]], cmap='viridis', linewidth=0.5)