# pandas.Index.drop_duplicates

`Index.``drop_duplicates`(keep='first')

  Return Index with duplicate values removed.

  Parameters:

  keep : {‘first’, ‘last’, `False`}, default ‘first’

  > - ‘first’ : Drop duplicates except for the first occurrence.
  > - ‘last’ : Drop duplicates except for the last occurrence.
  > - `False` : Drop all duplicates.

  Returns: | deduplicated : Index

  See also

  `Series.drop_duplicates`
    Equivalent method on Series.
  `DataFrame.drop_duplicates`
    Equivalent method on DataFrame.
  `Index.duplicated`
    Related method on Index, indicating duplicate Index values.

  Examples

  Generate an pandas.Index with duplicate values.

      >>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])

  The keep parameter controls which duplicate values are removed. The value ‘first’ keeps the first occurrence for each set of duplicated entries. The default value of keep is ‘first’.

      >>> idx.drop_duplicates(keep='first')
      Index(['lama', 'cow', 'beetle', 'hippo'], dtype='object')

  The value ‘last’ keeps the last occurrence for each set of duplicated entries.

      >>> idx.drop_duplicates(keep='last')
      Index(['cow', 'beetle', 'lama', 'hippo'], dtype='object')

  The value `False` discards all sets of duplicated entries.

      >>> idx.drop_duplicates(keep=False)
      Index(['cow', 'beetle', 'hippo'], dtype='object')

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