Changing a specific column name in pandas DataFrame

user_1577110 0
Viewed 376458

I was looking for an elegant way to change a specified column name in a DataFrame.

play data ...

import pandas as pd
d = {
         'one': [1, 2, 3, 4, 5],
         'two': [9, 8, 7, 6, 5],
         'three': ['a', 'b', 'c', 'd', 'e']
    }
df = pd.DataFrame(d)

The most elegant solution I have found so far ...

names = df.columns.tolist()
names[names.index('two')] = 'new_name'
df.columns = names

I was hoping for a simple one-liner ... this attempt failed ...

df.columns[df.columns.tolist().index('one')] = 'another_name'

Any hints gratefully received.

pandas python
10 Answers

If you know which column # it is (first / second / nth) then this solution posted on a similar question works regardless of whether it is named or unnamed, and in one line: https://stackoverflow.com/a/26336314/4355695

df.rename(columns = {list(df)[1]:'new_name'}, inplace=True)
# 1 is for second column (0,1,2..)
user_43556950

Pandas 0.21 now has an axis parameter

The rename method has gained an axis parameter to match most of the rest of the pandas API.

So, in addition to this:

df.rename(columns = {'two':'new_name'})

You can do:

df.rename({'two':'new_name'}, axis=1)

or

df.rename({'two':'new_name'}, axis='columns')
user_37076070

For renaming the columns here is the simple one which will work for both Default(0,1,2,etc;) and existing columns but not much useful for a larger data sets(having many columns).

For a larger data set we can slice the columns that we need and apply the below code:

df.columns = ['new_name','new_name1','old_name']
user_88267950

pandas version 0.23.4

df.rename(index=str,columns={'old_name':'new_name'},inplace=True)

For the record:

omitting index=str will give error replace has an unexpected argument 'columns'

user_108844580

Following short code can help:

df3 = df3.rename(columns={c: c.replace(' ', '') for c in df3.columns})

Remove spaces from columns.

user_88680320

Another option would be to simply copy & drop the column:

df = pd.DataFrame(d)
df['new_name'] = df['two']
df = df.drop('two', axis=1)
df.head()

After that you get the result:

    one three   new_name
0   1   a       9
1   2   b       8
2   3   c       7
3   4   d       6
4   5   e       5
user_1351600 

size = 10
df.rename(columns={df.columns[i]: someList[i] for i in range(size)}, inplace = True)

user_50213180
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