extractall(self, pat, flags=0)
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).
Regular expression pattern with capturing groups.
A re
module flag, for example re.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 example re.IGNORECASE | re.MULTILINE
.
A DataFrame
with one row for each match, and one column for each group. Its rows have a MultiIndex
with first levels that come from the subject Series
. The last level is named 'match' and indexes the matches in each item of the Series
. Any capture group names in regular expression pat will be used for column names; otherwise capture group numbers will be used.
Extract capture groups in the regex :None:None:`pat` as columns in DataFrame.
extract
Returns first match only (not all matches).
A pattern with one group will return a DataFrame with one column. Indices with no matches will not appear in the result.
This example is valid syntax, but we were not able to check execution>>> 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.
This example is valid syntax, but we were not able to check execution>>> 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.
This example is valid syntax, but we were not able to check execution>>> 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.
This example is valid syntax, but we were not able to check execution>>> 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 1See :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.strings.accessor.StringMethods.findall
pandas.core.strings.accessor.StringMethods.extract
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