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Series.str.extract(pat, flags=0, expand=None)[source]

For each subject string in the Series, extract groups from the first match of regular expression pat.


pat : string

Regular expression pattern with capturing groups

flags : int, default 0 (no flags)

re module flags, e.g. re.IGNORECASE

expand : bool, default False

  • If True, return DataFrame.
  • If False, return Series/Index/DataFrame.

New in version 0.18.0.


DataFrame with one row for each subject string, and one column for

each group. Any capture group names in regular expression pat will

be used for column names; otherwise capture group numbers will be

used. The dtype of each result column is always object, even when

no match is found. If expand=False and pat has only one capture group,

then return a Series (if subject is a Series) or Index (if subject

is an Index).

See also

returns all matches (not just the first match)


A pattern with two groups will return a DataFrame with two columns. Non-matches will be NaN.

>>> s = Series(['a1', 'b2', 'c3'])
>>> s.str.extract('([ab])(\d)')
     0    1
0    a    1
1    b    2
2  NaN  NaN

A pattern may contain optional groups.

>>> s.str.extract('([ab])?(\d)')
     0  1
0    a  1
1    b  2
2  NaN  3

Named groups will become column names in the result.

>>> s.str.extract('(?P<letter>[ab])(?P<digit>\d)')
  letter digit
0      a     1
1      b     2
2    NaN   NaN

A pattern with one group will return a DataFrame with one column if expand=True.

>>> s.str.extract('[ab](\d)', expand=True)
0    1
1    2
2  NaN

A pattern with one group will return a Series if expand=False.

>>> s.str.extract('[ab](\d)', expand=False)
0      1
1      2
2    NaN
dtype: object
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