'endswith' method can be applied on a DataFrame column to check whether particular value ends with given string or not.
Example
name_ends_with_a = df['Name'].str.lower().str.endswith('a')
persons_name_ends_with_a = df[name_ends_with_a]
The endswith() method is applied to the 'Name' column with the substring 'a'. It returns a Boolean Series where True indicates that the string in that particular column ends with the specified substring 'k', else False.
endswith.py
import pandas as pd
# Create a sample DataFrame
data = {'Name': ['Krishna', 'Sailu', 'Joel', 'kranthi', 'Jitendra', "Kumar"],
'Age': [34, 35, 234, 35, 52, 34],
'City': ['Bangalore', 'Hyderabad', 'Hyderabad', 'Chennai', 'Bangalore', 'Chennai'],
'Hobbies': ['Football,Cricket', 'Tennis, cricket', 'Trekking, reading books', 'Chess', 'Read Books', 'Cricket']}
df = pd.DataFrame(data)
print('Original DataFrame')
print(df)
# Get a boolean series to find the names ends with a (case insensitive)
name_ends_with_a = df['Name'].str.lower().str.endswith('a')
print('\nname_ends_with_a\n', name_ends_with_a)
persons_name_ends_with_a = df[name_ends_with_a]
print('\npersons_name_ends_with_a\n', persons_name_ends_with_a)
Output
Original DataFrame Name Age City Hobbies 0 Krishna 34 Bangalore Football,Cricket 1 Sailu 35 Hyderabad Tennis, cricket 2 Joel 234 Hyderabad Trekking, reading books 3 kranthi 35 Chennai Chess 4 Jitendra 52 Bangalore Read Books 5 Kumar 34 Chennai Cricket name_ends_with_a 0 True 1 False 2 False 3 False 4 True 5 False Name: Name, dtype: bool persons_name_ends_with_a Name Age City Hobbies 0 Krishna 34 Bangalore Football,Cricket 4 Jitendra 52 Bangalore Read Books
Previous Next Home
No comments:
Post a Comment