Skip to main content
`Ctrl`+`K`

# pandas.Series.str.match

Series.str.match(pat, case=True, flags=0, na=<no_default>)

  Determine if each string starts with a match of a regular expression.

  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 nullable `StringDtype`, `pandas.NA` is used. For the `"str"` dtype, `False` is used.

  Returns:
    Series/Index/array of boolean values

  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