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Pandas – Remove special characters from column names

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  • Difficulty Level : Basic
  • 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
import pandas as pd
  
# create data frame
Data = {'Name#': ['Mukul', 'Rohan', 'Mayank',
                  'Shubham', 'Aakash'],
          
        'Location': ['Saharanpur', 'Meerut', 'Agra',
                     'Saharanpur', 'Meerut'],
          
        'Pay': [25000, 30000, 35000, 40000, 45000]}
  
df = pd.DataFrame(Data)
  
# print original data frame
print(df)
  
# remove special character
df.columns = df.columns.str.replace('[#,@,&]', '')
  
# print file after removing special character
print("\n\n", df)

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
import pandas as pd
  
# create data frame
Data = {'Name#': ['Mukul', 'Rohan', 'Mayank',  
                 'Shubham', 'Aakash'],  
          
        'Location@' : ['Saharanpur', 'Meerut', 'Agra',  
                      'Saharanpur', 'Meerut'],
          
        'Pay&' : [25000,30000,35000,40000,45000]}  
  
df=pd.DataFrame(Data)
  
# print original data frame
print(df)
  
# remove special character
df.columns=df.columns.str.replace('[#,@,&]','')
  
# print file after removing special character
print("\n\n" , df)

Output:


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