duplicated() to get duplicate values from a series in Pandas

Series.duplicated(keep)

keep Optional ,
'first' default, all duplicates are marked True except first one
'last', all duplicates are marked True except last one
'False',all duplicates are marked True

Series : indicates duplicate values.
DataFrame :indicates duplicate rows.( can consider based some column values )
dataframe.duplicated()

Using Series

In our series below, we have one element as duplicate value ( 'Two' )

import pandas as pd
my_data=pd.Series(['One','Two','Three','Two','Four'])
my_data.duplicated()

Output ( default value of keep is first , keep='first')

0    False
1    False
2    False
3     True
4    False
dtype: bool

with keep='last', duplicate values are marked True except last one

import pandas as pd
my_data=pd.Series(['One','Two','Three','Two','Four'])
my_data.duplicated(keep='last')

0    False
1     True
2    False
3    False
4    False
dtype: bool

with keep=False , all duplicate values are marked True

import pandas as pd
my_data=pd.Series(['One','Two','Three','Two','Four'])
my_data.duplicated(keep=False)

Output

0    False
1     True
2    False
3     True
4    False
dtype: bool

Displaying Only duplicate data

Showing data having duplicate value.

print(my_data[my_data.duplicated()])

Output

3    Two
dtype: object

Displaying unique data

Let us remove data having duplidate vlaues.

print(my_data[~my_data.duplicated()])

Output

0      One
1      Two
2    Three
4     Four
dtype: object

We can use unique()

print(my_data.unique())

Output

['One' 'Two' 'Three' 'Four']

Data Cleaning

Pandas dataframe.duplicated() Series.drop_duplicates() dataframe.drop_duplicates()

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duplicated() : getting duplicate values

Using Series

Displaying Only duplicate data

Displaying unique data

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