pandas.Series.duplicated#
- 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 asTrue
.
- 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(['lama', 'cow', 'lama', 'beetle', 'lama']) >>> 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