pandas.Series.duplicated

Series.duplicated(keep='first')

Indicate duplicate Series values.

Duplicated values are indicated as True values in the resulting Series. Values are considered duplicated when the same value appears more than once. Either all duplicated values, all except the first, or all except the last occurrence of duplicated values 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 is a duplicated value according to keep.

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