Calculate mean in pandas with even and odd columns

Create helper arange by length of columns with modulo and create new columns:

arr = np.arange(len(df.columns)) % 2df['avg_odd']  = df.iloc[:, arr == 0].mean(axis=1)df['avg_even'] = df.iloc[:, arr == 1].mean(axis=1)print (df)   col1  col2  col3  col4  col5  col6    avg_odd   avg_even0     1     7    56  16.0   1.0    13  19.333333  12.0000001     2    45    67   NaN   9.0     3  26.000000  24.0000002     3    12     8  25.0  23.0    53  11.333333  30.0000003     4    56    12   6.0  56.0    72  24.000000  44.6666674     5    14    39  19.0   NaN    88  22.000000  40.333333

Using % and groupby

df[['avg_odd', 'avg_even']] = df.groupby(np.arange(df.shape[1]) % 2, axis=1).mean()

   col1  col2  col3  col4  col5  col6   avg_even    avg_odd0     1     7    56  16.0   1.0    13  12.000000  19.3333331     2    45    67   NaN   9.0     3  24.000000  26.0000002     3    12     8  25.0  23.0    53  30.000000  11.3333333     4    56    12   6.0  56.0    72  44.666667  24.0000004     5    14    39  19.0   NaN    88  40.333333  22.000000

df = df.assign(avg_even = df[df.columns[::2]].mean(axis=1),               avg_odd = df[df.columns[1::2]].mean(axis=1))

Simple and direct