df.col.str.contains('somestr') doesn't work

user_18965699 0
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Faced very weird thing - I need to drop rows containing '|' symbol in my df, but when I use .loc method the df stays the same, even though if I filter it by other character, f.e. 'a', it works.

df = pd.DataFrame({'A':['aaa', 'bbb | aaa', 'ccc'], 'B':['abababa', 'a | b', 'abab | abab']})
colA = 'A'

display(df.loc[df[colA].str.contains('|')])
A B
0 aaa abababa
1 bbb | aaa a | b
2 ccc abab | abab 
 display(df.loc[df['A'].str.contains('|')]
A B
0 aaa abababa
1 bbb | aaa a | b
2 ccc abab | abab 
display(df.loc[df['A'].str.contains('a')])
A B
0 aaa abababa
1 bbb | aaa a | b

Does anyone know how can I bypass it?

pandas-loc pandas dataframe python
2 Answers

Looking at the docs, the regex argument defaults to True, so it is interpreting the pipe character as a disjunction operator, not a literal pipe.

Simply set regex=False to fix this:

>>> print(df.loc[df['A'].str.contains('|', regex=False)])
           A      B
1  bbb | aaa  a | b
user_32824360

Try to use the regex


display(df.loc[df['A'].str.contains(r'\|', regex=True)])
display(df.loc[df['A'].str.contains(r'a', regex=True)]) 


            A       B
1   bbb | aaa   a | b

            A       B
0   aaa       abababa
1   bbb | aaa   a | b
user_34947540
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