Using strip(), lstrip(), rstrip() methods we can remove the whitespaces in given column values.
a. strip(): Remove leading and trailing whitespace from the given column.
b. lstrip(): Remove leading whitespace from the given column.
c. rstrip(): Remove trailing whitespace from the given column.
trim_spaces.py
import pandas as pd
# Create a sample DataFrame
data = {'Name': ['Krishna ', 'Sailu', 'Joel ', ' kranthi', ' Jitendra', "Kumar"],
'Hobbies': ['Football,Cricket ', ' Tennis, cricket ', ' Trekking, reading books', 'Chess', 'Read Books', 'Cricket']}
df = pd.DataFrame(data)
print('Original DataFrame')
print(df)
new_data = {}
new_df = pd.DataFrame(data)
new_df['Name'] = df['Name'].str.strip()
new_df['Hobbies'] = df['Hobbies'].str.strip()
print('\nDataFrame after trimming whitespaces\n',new_df)
new_df = pd.DataFrame(data)
new_df['Name'] = df['Name'].str.lstrip()
new_df['Hobbies'] = df['Hobbies'].str.lstrip()
print('\nDataFrame after trimming leading whitespaces\n',new_df)
new_df = pd.DataFrame(data)
new_df['Name'] = df['Name'].str.rstrip()
new_df['Hobbies'] = df['Hobbies'].str.rstrip()
print('\nDataFrame after trimming trailing whitespaces\n',new_df)
Output
Original DataFrame Name Hobbies 0 Krishna Football,Cricket 1 Sailu Tennis, cricket 2 Joel Trekking, reading books 3 kranthi Chess 4 Jitendra Read Books 5 Kumar Cricket DataFrame after trimming whitespaces Name Hobbies 0 Krishna Football,Cricket 1 Sailu Tennis, cricket 2 Joel Trekking, reading books 3 kranthi Chess 4 Jitendra Read Books 5 Kumar Cricket DataFrame after trimming leading whitespaces Name Hobbies 0 Krishna Football,Cricket 1 Sailu Tennis, cricket 2 Joel Trekking, reading books 3 kranthi Chess 4 Jitendra Read Books 5 Kumar Cricket DataFrame after trimming trailing whitespaces Name Hobbies 0 Krishna Football,Cricket 1 Sailu Tennis, cricket 2 Joel Trekking, reading books 3 kranthi Chess 4 Jitendra Read Books 5 Kumar Cricket
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