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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.
New in version 0.13.0.
Parameters: pat : string
Regular expression pattern with capturing groups
flags : int, default 0 (no flags)
re module flags, e.g. re.IGNORECASE
.. versionadded:: 0.18.0
expand : bool, default False
- If True, return DataFrame.
- If False, return Series/Index/DataFrame.
Returns: 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
-
extractall
- returns all matches (not just the first match)
Examples
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 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
Series.str.extract()
2017-01-12 04:54:51
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