Pandas – Remove special characters from column names
Last Updated :
05 Sep, 2020
Let us see how to remove special characters like #, @, &, etc. from column names in the pandas data frame. Here we will use replace function for removing special character.
Example 1: remove a special character from column names
Python
import pandas as pd
Data = { 'Name#' : [ 'Mukul' , 'Rohan' , 'Mayank' ,
'Shubham' , 'Aakash' ],
'Location' : [ 'Saharanpur' , 'Meerut' , 'Agra' ,
'Saharanpur' , 'Meerut' ],
'Pay' : [ 25000 , 30000 , 35000 , 40000 , 45000 ]}
df = pd.DataFrame(Data)
print (df)
df.columns = df.columns. str .replace( '[#,@,&]' , '')
print ( "\n\n" , df)
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Output:
Here, we have successfully remove a special character from the column names. Now we will use a list with replace function for removing multiple special characters from our column names.
Example 2: remove multiple special characters from the pandas data frame
Python
import pandas as pd
Data = { 'Name#' : [ 'Mukul' , 'Rohan' , 'Mayank' ,
'Shubham' , 'Aakash' ],
'Location@' : [ 'Saharanpur' , 'Meerut' , 'Agra' ,
'Saharanpur' , 'Meerut' ],
'Pay&' : [ 25000 , 30000 , 35000 , 40000 , 45000 ]}
df = pd.DataFrame(Data)
print (df)
df.columns = df.columns. str .replace( '[#,@,&]' ,'')
print ( "\n\n" , df)
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Output:
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