isin(self, values) -> 'Series'
Return a boolean Series showing whether each element in the Series matches an element in the passed sequence of :None:None:`values`
exactly.
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.
If :None:None:`values`
is a string
Series of booleans indicating if each element is in values.
Whether elements in Series are contained in :None:None:`values`
.
DataFrame.isin
Equivalent method on DataFrame.
>>> s = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama',
... 'hippo'], name='animal')
... s.isin(['cow', 'lama']) 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', 'lama']) 0 False 1 False 2 False 3 True 4 False 5 True Name: animal, dtype: bool
Passing a single string as s.isin('lama')
will raise an error. Use a list of one element instead:
>>> s.isin(['lama']) 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:
This example is valid syntax, but we were not able to check execution>>> pd.Series([1]).isin(['1']) 0 False dtype: boolThis example is valid syntax, but we were not able to check execution
>>> pd.Series([1.1]).isin(['1.1']) 0 False dtype: boolSee :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.indexes.multi.MultiIndex.isin
pandas.core.indexes.base.Index.isin
pandas.core.arrays.categorical.Categorical.isin
pandas.core.frame.DataFrame.isin
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