duplicated(self, keep: "Literal['first', 'last', False]" = 'first') -> 'npt.NDArray[np.bool_]'
Duplicated values are indicated as True
values in the resulting array. Either all duplicates, all except the first, or all except the last occurrence of duplicates can be indicated.
The value or values in a set of duplicates to mark as missing.
Indicate duplicate index values.
DataFrame.duplicated
Equivalent method on pandas.DataFrame.
Index.drop_duplicates
Remove duplicate values from Index.
Series.duplicated
Equivalent method on pandas.Series.
By default, for each set of duplicated values, the first occurrence is set to False and all others to True:
This example is valid syntax, but we were not able to check execution>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama'])
... idx.duplicated() array([False, False, True, False, True])
which is equivalent to
This example is valid syntax, but we were not able to check execution>>> idx.duplicated(keep='first') array([False, False, True, False, True])
By using 'last', the last occurrence of each set of duplicated values is set on False and all others on True:
This example is valid syntax, but we were not able to check execution>>> idx.duplicated(keep='last') array([ True, False, True, False, False])
By setting keep on False
, all duplicates are True:
>>> idx.duplicated(keep=False) array([ True, False, True, False, True])See :
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