Add prefix to the columns in a slice of the dataframe

Question

I have a fairly huge DataFrame (~500 columns and >5000 rows). I want to add a prefix to the first 15 columns. I found a function called add_prefix() that can set a prefix to all columns at once. I tried the following:

df[df.columns[range(0,15)]] = df[df.columns[range(0,15)]].add_prefix('f_')

with 'f_' being the prefix I would like to add. Yet, the output doesn't seem to change.

>>>
       mean        std         var  ...         525       526  label
0 -2.546261  17.827072  317.804485  ...   -0.314016 -0.310878    0.0
1 -2.338710  17.915556  320.967136  ...   -0.345603 -0.343088    0.0
2 -2.095051  17.539407  307.630788  ...   -0.323596 -0.324990    0.0
3 -1.685209  18.257797  333.347150  ...   -0.310060 -0.320796    0.0
4 -1.846169  17.240523  297.235618  ...   -0.318660 -0.322732    0.0

What I would like to have is:

>>>
     f_mean      f_std       f_var  ...         525       526  label
0 -2.546261  17.827072  317.804485  ...   -0.314016 -0.310878    0.0
1 -2.338710  17.915556  320.967136  ...   -0.345603 -0.343088    0.0
2 -2.095051  17.539407  307.630788  ...   -0.323596 -0.324990    0.0
3 -1.685209  18.257797  333.347150  ...   -0.310060 -0.320796    0.0
4 -1.846169  17.240523  297.235618  ...   -0.318660 -0.322732    0.0

What am I doing wrong?

Answer 1

You cannot directly assign a prefix as you are currently doing it, given that indices do not support mutable operations. So you would have to reassign all columns again. Here's one way to do it with a list comprehension:

df.columns = ['f_' + i if ix < 15 else i for ix, i in enumerate(df.columns)]