Renaming Column Names in Pandas

Renaming column names in Pandas

Just assign it to the .columns attribute:

>>> df = pd.DataFrame({'$a':[1,2], '$b': [10,20]})
>>> df
   $a  $b
0   1  10
1   2  20

>>> df.columns = ['a', 'b']
>>> df
   a   b
0  1  10
1  2  20

How to change column names in pandas Dataframe using a list of names?

you could use

df.columns = ['Leader', 'Time', 'Score']

Renaming columns in pandas

You can just rename it directly, like:

df.columns = ['first', 'second', 'third']

In your case you can use:

df.columns = ['Special{i}'.format(i=i) for i in range(0, len(df.columns))]

renaming the column names in dataframe using some parts of original column name

You can achieve this with a single regex:

df.columns = df.columns.str.replace(r'.*?([^_]+:).+?([^_]+_[^_]+)@.*',
                                    r'\1\2', regex=True)

output:

   mynumber  trial1:type_id  trial1:king_que  fer45:gul_har23  chb1:kaam_nix
0        11               4                0                4              2
1        20               5                2                5              1
2        25              42                3               42              1

To understand ho this works, you can check the regex demo.

Programmatic way to rename pandas column, insert '_'

You can use a generator expression combined with the string method replace() for this:

df = pd.DataFrame({
                   'col 1': [1],
                   'col 2': [2],
                   'col 3': [3]
                 })

df.columns = (x.replace(' ', '_') for x in df.columns)

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