Renaming selected columns in a Pandas dataframe

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Let say I have below data frame:

import pandas as pd
raw_data = {'col1': [23,45,21,45,23],'col2': [3,4,5,22,3],'col3': ['y1', 'y2', 'y3', 'y1', 'y2'],'col4': ['x1', 'x2', 'x3', 'x1', 'x2']}
df = pd.DataFrame(raw_data, columns = ['col1','col2','col3','col4','col5'])

Now I want to prefix 'PRE-' to each column names except 'col2' and 'col4' in a programmatic way.

Is there any method/function available to achieve this?

Thanks for your pointer

pandas dataframe python-3.x python
2 Answers

Use DataFrame.rename with lambda function:

df = df.rename(columns = lambda x: f'PRE-{x}' if x not in ['col2','col4'] else x)
print (df)
   PRE-col1  col2 PRE-col3 col4 PRE-col5
0        23     3       y1   x1      NaN
1        45     4       y2   x2      NaN
2        21     5       y3   x3      NaN
3        45    22       y1   x1      NaN
4        23     3       y2   x2      NaN
user_29010020

We can also use a simple list comprehension:

df.columns = [('' if col in ('col2','col4') else 'PRE-') + col for col in df.columns]

Output:

   PRE-col1  col2 PRE-col3 col4 PRE-col5
0        23     3       y1   x1      NaN
1        45     4       y2   x2      NaN
2        21     5       y3   x3      NaN
3        45    22       y1   x1      NaN
4        23     3       y2   x2      NaN
Admin1
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