pandas.Series.str.extractall¶
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Series.str.extractall(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). - New in version 0.18.0. - Parameters: - pat : string - Regular expression pattern with capturing groups - flags : int, default 0 (no flags) - re module flags, e.g. re.IGNORECASE - Returns: - 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 indicates - the order in the subject. 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 = Series(["a1a2", "b1", "c1"], index=["A", "B", "C"]) >>> s.str.extractall("[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("[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("(?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("(?P<letter>[ab])?(?P<digit>\d)") letter digit match A 0 a 1 1 a 2 B 0 b 1 C 0 NaN 1