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Adding suffix to column labels in Pandas DataFrame
schedule Aug 10, 2023
Last updated local_offer
Tags Python●Pandas
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To append a suffix to column labels, use the DataFrame's add_suffix(~) method.
Example
Consider the following DataFrame:
df = pd.DataFrame({"A":[4,5],"B":[6,7]})df
A B0 4 61 5 7
Solution
To append the suffix "C" to each column label of df:
df.add_suffix("C")
AC BC0 4 61 5 7
Here, add_suffix(~) returns a new DataFrame with the added suffix and so the original df is kept intact.
WARNING
If your DataFrame is memory-heavy, then add_suffix(~) is not ideal since the method allocates new memory for the returned DataFrame. To perform the same operation in-place, that is, directly modifying the original DataFrame without creating a new DataFrame, refer to the section below.
Adding a suffix in-place
Consider the same df as before:
df
A B0 4 61 5 7
Solution
To add a suffix to the column labels in-place:
df.columns = df.columns + "C"df
AC BC0 4 61 5 7
Explanation
Here, df.columns returns a Series like so:
df.columns
Index(['A', 'B'], dtype='object')
We then use the broadcasting technique of adding a Series and a scalar (string):
df.columns + "C"
Index(['AC', 'BC'], dtype='object')
We then finally assign this to be our new columns:
df.columns = df.columns + "C"
Index(['AC', 'BC'], dtype='object')
Published by Isshin Inada
Edited by 0 others
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