to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [206]: Series([’a1’, ’b2’, ’c3’]).str.extract(’(?P[ab])(

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like 50 Chapter 1. What’s New pandas: powerful Python data analysis toolkit DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [209]: Series([’a1’, ’b2’, ’c3’]).str.extract(’(?P[ab])(

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The results dtype always is object, even if no match is found and the result only contains

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The results dtype always is object, even if no match is found and the result only contains

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series(['a1', 'b2', 'c3']).str.extract( ....: '(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The results dtype always is object, even if no match is found and the result only contains

DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The dtype of the result is always object, even if no match is found and the result only False dtype: bool The distinction between match and contains is strictness: match relies on strict re.match, while contains relies on re.search. Methods like match, contains, startswith, and endswith take element findall() Compute list of all occurrences of pattern/regex for each string match() Call re.match on each element, returning matched groups as list extract() Call re.search on each element, returning

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series(['a1', 'b2', 'c3']).str.extract( ....: '(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The dtype of the result is always object, even if no match is found and the result only

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series(['a1', 'b2', 'c3']).str.extract( ....: '(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The dtype of the result is always object, even if no match is found and the result only

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [86]: Series(['a1', 'b2', 'c3']).str.extract( ....: '(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The dtype of the result is always object, even if no match is found and the result only

to contains, which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [86]: Series(['a1', 'b2', 'c3']).str.extract( ....: '(?P[ab])( DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. The dtype of the result is always object, even if no match is found and the result only