Suppose I have a pandas dataframe like this:
Word Rating
0 Bear 1
1 Yuck 2
2 Girl 3
3 Yellow 4
How can I use regex in pandas to filter out the rows that have the word that starts with the letter "y" but keep the dataframe formatting? I know the regex pattern would be r"\b[^y]\w+\b"
Expected output:
Word Rating
0 Bear 1
2 Girl 3
Using startswith
In [1187]: df[~df.Word.str.startswith('Y')]
Out[1187]:
Word Rating
0 Bear 1
2 Girl 3
Or, regex match
In [1203]: df[df.Word.str.match('^[^Y]')]
Out[1203]:
Word Rating
0 Bear 1
2 Girl 3
Regular expressions are not necessary. Just check the first letter:
df[df.Word.str[0] != 'Y']
Use lower and startswith to get both uppercase 'Y' and lowercase 'y':
df[~df.Word.str.lower().str.startswith('y')]
Input:
df
Word Rating
0 Bear 1
1 Yuck 2
2 Girl 3
3 Yellow 4
4 yes 5
5 color 6
Output:
Word Rating
0 Bear 1
2 Girl 3
5 color 6
