pandas.Series.str.match — pandas 3.0.0rc0+33.g1fd184de2a documentation (original) (raw)

Series.str.match(pat, case=<no_default>, flags=<no_default>, 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 or compiled regex

Character sequence or regular expression.

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 the "str" dtype, False is used. For object dtype, numpy.nan is used. For the nullable StringDtype,pandas.NA 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

fullmatch

Stricter matching that requires the entire string to match.

contains

Analogous, but less strict, relying on re.search instead of re.match.

extract

Extract matched groups.

Examples

ser = pd.Series(["horse", "eagle", "donkey"]) ser.str.match("e") 0 False 1 True 2 False dtype: bool