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# pandas.Series.isin

Series.isin(values)

  Whether elements in Series are contained in values.

  Return a boolean Series showing whether each element in the Series matches an element in the passed sequence of values exactly.

  Parameters:
    valuesset or list-like

      The sequence of values to test. Passing in a single string will raise a `TypeError`. Instead, turn a single string into a list of one element.

  Returns:
    Series

      Series of booleans indicating if each element is in values.

  Raises:
    TypeError

      - If values is a string

  See also

  `DataFrame.isin`

    Equivalent method on DataFrame.

  Examples

      >>> s = pd.Series(['llama', 'cow', 'llama', 'beetle', 'llama',
      ...                'hippo'], name='animal')
      >>> s.isin(['cow', 'llama'])
      0     True
      1     True
      2     True
      3    False
      4     True
      5    False
      Name: animal, dtype: bool

  To invert the boolean values, use the `~` operator:

      >>> ~s.isin(['cow', 'llama'])
      0    False
      1    False
      2    False
      3     True
      4    False
      5     True
      Name: animal, dtype: bool

  Passing a single string as `s.isin('llama')` will raise an error. Use a list of one element instead:

      >>> s.isin(['llama'])
      0     True
      1    False
      2     True
      3    False
      4     True
      5    False
      Name: animal, dtype: bool

  Strings and integers are distinct and are therefore not comparable:

      >>> pd.Series([1]).isin(['1'])
      0    False
      dtype: bool
      >>> pd.Series([1.1]).isin(['1.1'])
      0    False
      dtype: bool