python pandas rename multiple column headers the same way

Question

Considering a simple df:

HeaderA | HeaderB | HeaderC 
    476      4365      457

Is there a way to rename all columns, for example to add to all columns an "X" in the end?

HeaderAX | HeaderBX | HeaderCX 
    476      4365      457

I am concatenating multiple dataframes and want to easily differentiate the columns dependent on which dataset they came from.

Or is this the only way?

df.rename(columns={'HeaderA': 'HeaderAX'}, inplace=True)

I have over 50 column headers and ten files; so the above approach will take a long time.

Thank You

Answer 1

pd.DataFrame.add_suffix

df.add_suffix('X')

   HeaderAX  HeaderBX  HeaderCX
0       476      4365       457

---

And the sister method
pd.DataFrame.add_prefix

df.add_prefix('X')

   XHeaderA  XHeaderB  XHeaderC
0       476      4365       457

---

You can also use the pd.DataFrame.rename method and pass a function. To accomplish the same thing:

df.rename(columns='{}X'.format)

   HeaderAX  HeaderBX  HeaderCX
0       476      4365       457

In this example, '{}X'.format is a function that takes a single argument and appends an 'X'

The advantage of this method is that you can use inplace=True if you chose to.

Answer 2

df.columns = list(map(lambda s: s+'X', df.columns))

Answer 3

From SO post. Let's try using a lambda function in rename:

df.rename(columns = lambda x: x+'X', inplace = True)

Answer 4

df.columns = [column + 'X' for column in df.columns]