Changing multiple column names by column number in Pandas?

Question

I am borrowing this example from here. I have a dataframe like this:

# Import pandas package 
import pandas as pd 
   
# Define a dictionary containing ICC rankings 
rankings = {'test': ['India', 'South Africa', 'England', 
                            'New Zealand', 'Australia'], 
              'odi': ['England', 'India', 'New Zealand', 
                            'South Africa', 'Pakistan'], 
               't20': ['Pakistan', 'India', 'Australia', 
                              'England', 'New Zealand']} 
   
# Convert the dictionary into DataFrame 
rankings_pd = pd.DataFrame(rankings) 
   
# Before renaming the columns 
print(rankings_pd)
          test           odi          t20
0         India       England     Pakistan
1  South Africa         India        India
2       England   New Zealand    Australia
3   New Zealand  South Africa      England
4     Australia      Pakistan  New Zealand

Now let's say I want to change the name of the 1st and 2nd columns. This is what I am trying:

rankings_pd[rankings_pd.columns[0:2]].columns =  ['tes_after_change', 'odi_after_change']
print(rankings_pd[rankings_pd.columns[0:2]].columns)
Index(['test', 'odi'], dtype='object')

But this seems to return exactly the same columns names and not changing them.

Pretty close to being a dupe... but ever so slightly different (-: However, you learn a bit from these [Q&As](https://stackoverflow.com/a/46192213/2336654) — piRSquared, Mar 10 '21 at 18:01

Anurag Dabas · Answer 1 · 2021-03-28T05:59:03.557

8

Just use rename() method and pass the dictionary of old values and new values as key-value pair in columns parameter:-

rankings_pd=rankings_pd.rename(columns={'test':'tes_after_change','odi':'odi_after_change'})

Edit by @sammywemmy:

You could extend the idea with an anonymous function :

rankings_pd.rename(columns= lambda df: f"{df}_after_change" if df in ("test", "odi") else df)

edited Mar 28 '21 at 05:59

answered Mar 10 '21 at 17:23

Anurag Dabas

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You could extend the idea with an anonymous function : ``rankings_pd.rename(columns= lambda df: f"{df}_after_change" if df in ("test", "odi") else df)`` – sammywemmy Mar 27 '21 at 23:25
@sammywemmy thanks for the suggestion....added this In answer :) – Anurag Dabas Mar 28 '21 at 05:59

score 4 · Accepted Answer · answered Mar 10 '21 at 17:22

4

You should/could not replace part of the columns. You need to replace them all at once:

rankings_pd.columns = ['tes_after_change', 'odi_after_change'] + rankings_pd.columns[2:].tolist()

answered Mar 10 '21 at 17:22

Quang Hoang

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anky · Answer 3 · 2021-03-10T17:29:20.267

4

You can use to_numpy() and replace the slice:

rankings_pd.columns.to_numpy()[0:2] = ['tes_after_change', 'odi_after_change']

rankings_pd.columns
#Index(['tes_after_change', 'odi_after_change', 't20'], dtype='object')

Or using np.r_ with df.rename

rankings_pd.rename(dict(zip(rankings_pd.columns[np.r_[0:2]],
                        ['tes_after_change', 'odi_after_change'])),axis=1)

edited Mar 10 '21 at 17:29

answered Mar 10 '21 at 17:23

anky

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Changing multiple column names by column number in Pandas?

3 Answers3