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 pandasimport pandas as pd # create data frameData = {'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 frameprint(df) # remove special characterdf.columns = df.columns.str.replace('[#,@,&]', '') # print file after removing special characterprint("\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 pandasimport pandas as pd # create data frameData = {'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 frameprint(df) # remove special characterdf.columns=df.columns.str.replace('[#,@,&]','') # print file after removing special characterprint("\n\n" , df) |
Output:
