pyspark.pandas.Series.str.contains¶
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str.contains(pat: str, case: bool = True, flags: int = 0, na: Any = None, regex: bool = True) → pyspark.pandas.series.Series¶ Test if pattern or regex is contained within a string of a Series.
Return boolean Series based on whether a given pattern or regex is contained within a string of a Series.
Analogous to
match(), but less strict, relying onre.search()instead ofre.match().- Parameters
- patstr
Character sequence or regular expression.
- casebool, default True
If True, case sensitive.
- flagsint, default 0 (no flags)
Flags to pass through to the re module, e.g. re.IGNORECASE.
- nadefault None
Fill value for missing values. NaN converted to None.
- regexbool, default True
If True, assumes the pat is a regular expression. If False, treats the pat as a literal string.
- Returns
- Series of boolean values or object
A Series of boolean values indicating whether the given pattern is contained within the string of each element of the Series.
Examples
Returning a Series of booleans using only a literal pattern.
>>> s1 = ps.Series(['Mouse', 'dog', 'house and parrot', '23', np.NaN]) >>> s1.str.contains('og', regex=False) 0 False 1 True 2 False 3 False 4 None dtype: object
Specifying case sensitivity using case.
>>> s1.str.contains('oG', case=True, regex=True) 0 False 1 False 2 False 3 False 4 None dtype: object
Specifying na to be False instead of NaN replaces NaN values with False. If Series does not contain NaN values the resultant dtype will be bool, otherwise, an object dtype.
>>> s1.str.contains('og', na=False, regex=True) 0 False 1 True 2 False 3 False 4 False dtype: bool
Returning ‘house’ or ‘dog’ when either expression occurs in a string.
>>> s1.str.contains('house|dog', regex=True) 0 False 1 True 2 True 3 False 4 None dtype: object
Ignoring case sensitivity using flags with regex.
>>> import re >>> s1.str.contains('PARROT', flags=re.IGNORECASE, regex=True) 0 False 1 False 2 True 3 False 4 None dtype: object
Returning any digit using regular expression.
>>> s1.str.contains('[0-9]', regex=True) 0 False 1 False 2 False 3 True 4 None dtype: object
Ensure pat is a not a literal pattern when regex is set to True. Note in the following example one might expect only s2[1] and s2[3] to return True. However, ‘.0’ as a regex matches any character followed by a 0.
>>> s2 = ps.Series(['40','40.0','41','41.0','35']) >>> s2.str.contains('.0', regex=True) 0 True 1 True 2 False 3 True 4 False dtype: bool