You are viewing documentation about an older version (1.21.0). View latest version

modin.pandas.Series.isin

Series.isin(values: Union[set, list, tuple, ndarray]) → Series[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.21.0/src/snowflake/snowpark/modin/plugin/extensions/series_overrides.py#L36-L120)

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:

values (set 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 of booleans indicating if each element is in values.

Return type:

Series

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

Note

See pandas API documentation for pandas.Series (https://pandas.pydata.org/pandas-docs/version/2.2.1/reference/api/pandas.Series.html) for more.