Skip to main content
`Ctrl`+`K`

# pandas.Series.duplicated

Series.duplicated(keep='first')

  Indicate duplicate Series values.

  Duplicated values are indicated as `True` values in the resulting Series. Either all duplicates, all except the first or all except the last occurrence of duplicates can be indicated.

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

      Method to handle dropping duplicates:

      - ‘first’ : Mark duplicates as `True` except for the first occurrence.

      - ‘last’ : Mark duplicates as `True` except for the last occurrence.

      - `False` : Mark all duplicates as `True`.

  Returns:
    Series[bool]

      Series indicating whether each value has occurred in the preceding values.

  See also

  `Index.duplicated`

    Equivalent method on pandas.Index.

  `DataFrame.duplicated`

    Equivalent method on pandas.DataFrame.

  `Series.drop_duplicates`

    Remove duplicate values from Series.

  Examples

  By default, for each set of duplicated values, the first occurrence is set on False and all others on True:

      >>> animals = pd.Series(["llama", "cow", "llama", "beetle", "llama"])
      >>> animals.duplicated()
      0    False
      1    False
      2     True
      3    False
      4     True
      dtype: bool

  which is equivalent to

      >>> animals.duplicated(keep="first")
      0    False
      1    False
      2     True
      3    False
      4     True
      dtype: bool

  By using ‘last’, the last occurrence of each set of duplicated values is set on False and all others on True:

      >>> animals.duplicated(keep="last")
      0     True
      1    False
      2     True
      3    False
      4    False
      dtype: bool

  By setting keep on `False`, all duplicates are True:

      >>> animals.duplicated(keep=False)
      0     True
      1    False
      2     True
      3    False
      4     True
      dtype: bool