Table Of Contents

Search

Enter search terms or a module, class or function name.

pandas.Series.str.extractall

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 = 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
Scroll To Top