otp.Operation.str.extract#

extract(pat, rewrite='\\0', caseless=False)#

Match the string against a regular expression specified by pat and return the first match. The rewrite parameter can optionally be used to arrange the matched substrings and embed them within the string specified in rewrite.

Parameters

  • pat (str or Column or Operation) – Pattern to search for specified via the POSIX extended regular expression syntax.

  • rewrite (str or Column or Operation) – A string that specifies how to arrange the matched text. \0 refers to the entire matched text. \1 to \9 refer to the text matched by the corresponding parenthesized group in pat. \u and \l modifiers within the rewrite string convert the case of the text that matches the corresponding parenthesized group (e.g., \u1 converts \1 to uppercase).

  • caseless (bool) – If the caseless flag is set to True, matching is case-insensitive.

Returns

String matched by pat with format specified in rewrite.

Return type

Operation

Examples

>>> data = otp.Ticks(X=['Mr. Smith: +1348 +4781', 'Ms. Smith: +8971'])
>>> data['TEL'] = data['X'].str.extract(r'\+\d{4}')
>>> otp.run(data)
                     Time                       X    TEL
0 2003-12-01 00:00:00.000  Mr. Smith: +1348 +4781  +1348
1 2003-12-01 00:00:00.001        Ms. Smith: +8971  +8971

You can specify the group to extract in the rewrite parameter:

>>> data = otp.Ticks(X=['Mr. Smith: 1992/12/22', 'Ms. Smith: 1989/10/15'])
>>> data['BIRTH_YEAR'] = data['X'].str.extract(r'(\d{4})/(\d{2})/(\d{2})', rewrite=r'birth year: \1')
>>> otp.run(data)
                     Time                      X        BIRTH_YEAR
0 2003-12-01 00:00:00.000  Mr. Smith: 1992/12/22  birth year: 1992
1 2003-12-01 00:00:00.001  Ms. Smith: 1989/10/15  birth year: 1989

You can use a column as a rewrite or pat parameter:

>>> data = otp.Ticks(X=['Kelly, Mr. James', 'Wilkes, Mrs. James', 'Connolly, Miss. Kate'],
...                  PAT=['(Mrs?)\\.', '(Mrs?)\\.', '(Miss)\\.'],
...                  REWRITE=['Title 1: \\1', 'Title 2: \\1', 'Title 3: \\1'])
>>> data['TITLE'] = data['X'].str.extract(data['PAT'], rewrite=data['REWRITE'])
>>> otp.run(data)
                     Time                     X       PAT      REWRITE          TITLE
0 2003-12-01 00:00:00.000      Kelly, Mr. James  (Mrs?)\.  Title 1: \1  Title 1:   Mr
1 2003-12-01 00:00:00.001    Wilkes, Mrs. James  (Mrs?)\.  Title 2: \1  Title 2:  Mrs
2 2003-12-01 00:00:00.002  Connolly, Miss. Kate  (Miss)\.  Title 3: \1  Title 3: Miss

Case of the extracted string can be changed by adding l and u to extract group:

>>> data = otp.Ticks(NAME=['mr. BroWn', 'Ms. smITh'])
>>> data['RESULT'] = data['NAME'].str.extract(r'(m)([rs]\. )([a-z])([a-z]*)', r'\u1\l2\u3\l4', caseless=True)
>>> otp.run(data)
                     Time       NAME     RESULT
0 2003-12-01 00:00:00.000  mr. BroWn  Mr. Brown
1 2003-12-01 00:00:00.001  Ms. smITh  Ms. Smith

See also

regex_replace