pandas.Series.str.extractall¶

Series.str.
extractall
(self, pat, flags=0)[source]¶ For each subject string in the Series, extract groups from all matches of regular expression pat. When each subject string in the Series has exactly one match, extractall(pat).xs(0, level=’match’) is the same as extract(pat).
 Parameters
 patstr
Regular expression pattern with capturing groups.
 flagsint, default 0 (no flags)
A
re
module flag, for examplere.IGNORECASE
. These allow to modify regular expression matching for things like case, spaces, etc. Multiple flags can be combined with the bitwise OR operator, for examplere.IGNORECASE  re.MULTILINE
.
 Returns
 DataFrame
A
DataFrame
with one row for each match, and one column for each group. Its rows have aMultiIndex
with first levels that come from the subjectSeries
. The last level is named ‘match’ and indexes the matches in each item of theSeries
. Any capture group names in regular expression pat will be used for column names; otherwise capture group numbers will be used.
See also
extract
Returns first match only (not all matches).
Examples
A pattern with one group will return a DataFrame with one column. Indices with no matches will not appear in the result.
>>> s = pd.Series(["a1a2", "b1", "c1"], index=["A", "B", "C"]) >>> s.str.extractall(r"[ab](\d)") 0 match A 0 1 1 2 B 0 1
Capture group names are used for column names of the result.
>>> s.str.extractall(r"[ab](?P<digit>\d)") digit match A 0 1 1 2 B 0 1
A pattern with two groups will return a DataFrame with two columns.
>>> s.str.extractall(r"(?P<letter>[ab])(?P<digit>\d)") letter digit match A 0 a 1 1 a 2 B 0 b 1
Optional groups that do not match are NaN in the result.
>>> s.str.extractall(r"(?P<letter>[ab])?(?P<digit>\d)") letter digit match A 0 a 1 1 a 2 B 0 b 1 C 0 NaN 1