pandas.Series.str.findall¶
- Series.str.findall(pat, flags=0)[source]¶
Find all occurrences of pattern or regular expression in the Series/Index.
Equivalent to applying
re.findall()to all the elements in the Series/Index.- Parameters
- patstr
Pattern or regular expression.
- flagsint, default 0
Flags from
remodule, e.g. re.IGNORECASE (default is 0, which means no flags).
- Returns
- Series/Index of lists of strings
All non-overlapping matches of pattern or regular expression in each string of this Series/Index.
See also
countCount occurrences of pattern or regular expression in each string of the Series/Index.
extractallFor each string in the Series, extract groups from all matches of regular expression and return a DataFrame with one row for each match and one column for each group.
re.findallThe equivalent
refunction to all non-overlapping matches of pattern or regular expression in string, as a list of strings.
Examples
>>> s = pd.Series(['Lion', 'Monkey', 'Rabbit'])
The search for the pattern ‘Monkey’ returns one match:
>>> s.str.findall('Monkey') 0 [] 1 [Monkey] 2 [] dtype: object
On the other hand, the search for the pattern ‘MONKEY’ doesn’t return any match:
>>> s.str.findall('MONKEY') 0 [] 1 [] 2 [] dtype: object
Flags can be added to the pattern or regular expression. For instance, to find the pattern ‘MONKEY’ ignoring the case:
>>> import re >>> s.str.findall('MONKEY', flags=re.IGNORECASE) 0 [] 1 [Monkey] 2 [] dtype: object
When the pattern matches more than one string in the Series, all matches are returned:
>>> s.str.findall('on') 0 [on] 1 [on] 2 [] dtype: object
Regular expressions are supported too. For instance, the search for all the strings ending with the word ‘on’ is shown next:
>>> s.str.findall('on$') 0 [on] 1 [] 2 [] dtype: object
If the pattern is found more than once in the same string, then a list of multiple strings is returned:
>>> s.str.findall('b') 0 [] 1 [] 2 [b, b] dtype: object