Fastest way to calculate difference in all columns

Question

I have a dataframe of all float columns. For example:

import numpy as np
import pandas as pd

df = pd.DataFrame(np.arange(12.0).reshape(3,4), columns=list(\'         


        

Answer 1

import itertools
df = pd.DataFrame(np.arange(12.0).reshape(3,4), columns=list('ABCD'))
df_cols = df.columns.tolist()
#build a index array of all the pairs need to do the subtraction
idx = np.asarray(list(itertools.combinations(range(len(df_cols)),2))).T
#build a new DF using the pairwise difference and column names
df_new = pd.DataFrame(data=df.values[:,idx[0]]-df.values[:,idx[1]], 
                      columns=[''.join(e) for e in (itertools.combinations(df_cols,2))])

df_new
Out[43]: 
    AB   AC   AD   BC   BD   CD
0 -1.0 -2.0 -3.0 -1.0 -2.0 -1.0
1 -1.0 -2.0 -3.0 -1.0 -2.0 -1.0
2 -1.0 -2.0 -3.0 -1.0 -2.0 -1.0