Fastest way to calculate in Pandas?

Question

Given these two dataframes:

df1 =
     Name  Start  End
  0  A     10     20
  1  B     20     30
  2  C     30     40

df2 =
     0   1
  0  5   10
  1  15  20
         


        

Answer 1

I suggest use here numpy - convert selected columns to 2d numpy array in first step::

a = df1[['Start','End']].to_numpy()
b = df2[[0,1]].to_numpy()

Output is 3d array, convert it to 2d array:

c = (a - b[:, None]).swapaxes(0,1).reshape(a.shape[0],-1)
print (c)
[[  5  10  -5   0 -15 -10]
 [ 15  20   5  10  -5   0]
 [ 25  30  15  20   5  10]]

Last generate columns names and with DataFrame.join add to original:

cols = [item for x in range(b.shape[0]) for item in (f'Start_Diff_{x}', f'End_Diff_{x}')]
df = df1.join(pd.DataFrame(c, columns=cols, index=df1.index))
print (df)
  Name  Start  End  Start_Diff_0  End_Diff_0  Start_Diff_1  End_Diff_1  \
0    A     10   20             5          10            -5           0   
1    B     20   30            15          20             5          10   
2    C     30   40            25          30            15          20   

   Start_Diff_2  End_Diff_2  
0           -15         -10  
1            -5           0  
2             5          10