# pandas.Series.str.extractall

`Series.str.``extractall`(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).

  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

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