pandas.Series.str.match — pandas 3.0.0.dev0+2105.g29e01463a6 documentation (original) (raw)
Series.str.match(pat, case=True, flags=0, na=<no_default>)[source]#
Determine if each string starts with a match of a regular expression.
Determines whether each string in the Series or Index starts with a match to a specified regular expression. This function is especially useful for validating prefixes, such as ensuring that codes, tags, or identifiers begin with a specific pattern.
Parameters:
patstr
Character sequence.
casebool, default True
If True, case sensitive.
flagsint, default 0 (no flags)
Regex module flags, e.g. re.IGNORECASE.
nascalar, optional
Fill value for missing values. The default depends on dtype of the array. For object-dtype, numpy.nan
is used. For the nullableStringDtype
, pandas.NA
is used. For the "str"
dtype,False
is used.
Returns:
Series/Index/array of boolean values
A Series, Index, or array of boolean values indicating whether the start of each string matches the pattern. The result will be of the same type as the input.
See also
Stricter matching that requires the entire string to match.
Analogous, but less strict, relying on re.search instead of re.match.
Extract matched groups.
Examples
ser = pd.Series(["horse", "eagle", "donkey"]) ser.str.match("e") 0 False 1 True 2 False dtype: bool