Series.str can be used to access the values of the series as strings and apply several methods to it. Pandas Series.str.extract() function is used to extract capture groups in the regex pat as columns in a DataFrame. For each subject string in the Series, extract groups from the first match of regular expression pat.
Regular expression pattern with capturing groups.
Flags from the re module, e.g. re.IGNORECASE, that
modify regular expression matching for things like case,
spaces, etc. For more details, see re.
If True, return DataFrame with one column per capture group. If False, return a Series/Index if there is one capture group or DataFrame if there are multiple capture groups.
A 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).
A pattern with two groups will return a DataFrame with two columns. Non-matches will be NaN.
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>>> s=pd.Series(['name1','name2','name3'])
>>> s.str.extract('([a-z]*(\d))')
0 1
0 name1 1
1 name2 2
2 name3 3
>>>
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