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Showing content from https://pandas.pydata.org/pandas-docs/stable/reference/api/../api/pandas.Series.duplicated.html below:

pandas.Series.duplicated — pandas 2.3.1 documentation

Series.duplicated(keep='first')[source]#

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.

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

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