Method extractall

pandas/core/strings/accessor.py:3460–3535

r""" Extract capture groups in the regex `pat` as columns in DataFrame. 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'

(self, pat, flags: int = 0)

    @forbid_nonstring_types(["bytes"])
    def extractall(self, pat, flags: int = 0) -> DataFrame:
        r"""
        Extract capture groups in the regex `pat` as columns in DataFrame.

        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
        ----------
        pat : str
            Regular expression pattern with capturing groups.
        flags : int, default 0 (no flags)
            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``.

        Returns
        -------
        DataFrame
            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.

        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)")