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Python Pandas – Remove numbers from string in a DataFrame column
To remove numbers from string, we can use replace() method and simply replace. Let us first import the require library −
import pandas as pd
Create DataFrame with student records. The Id column is having string with numbers −
dataFrame = pd.DataFrame(
{
"Id": ['S01','S02','S03','S04','S05','S06','S07'],"Name": ['Jack', 'Robin', 'Ted', 'Robin', 'Scarlett', 'Kat', 'Ted'],"Result": ['Pass', 'Fail', 'Pass', 'Fail', 'Pass', 'Pass', 'Pass']
}
)Remove number from strings of a specific column i.e. “Id” here −
dataFrame['Id'] = dataFrame['Id'].str.replace('\d+', '')
Example
Following is the code −
import pandas as pd
# Create DataFrame with student records
dataFrame = pd.DataFrame(
{
"Id": ['S01','S02','S03','S04','S05','S06','S07'],"Name": ['Jack', 'Robin', 'Ted', 'Robin', 'Scarlett', 'Kat', 'Ted'],"Result": ['Pass', 'Fail', 'Pass', 'Fail', 'Pass', 'Pass', 'Pass']
}
)
print"DataFrame ...\n",dataFrame
# removing number from strings of a specific column
dataFrame['Id'] = dataFrame['Id'].str.replace('\d+', '')
print"\nUpdated DataFrame...\n", dataFrameOutput
This will produce the following output −
DataFrame ... Id Name Result 0 S01 Jack Pass 1 S02 Robin Fail 2 S03 Ted Pass 3 S04 Robin Fail 4 S05 Scarlett Pass 5 S06 Kat Pass 6 S07 Ted Pass Updated DataFrame... Id Name Result 0 S Jack Pass 1 S Robin Fail 2 S Ted Pass 3 S Robin Fail 4 S Scarlett Pass 5 S Kat Pass 6 S Ted Pass
Updated on: 20-Sep-2021
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