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Pandas DataFrame | duplicated method

schedule Aug 10, 2023
Last updated
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PythonPandas
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Pandas DataFrame.duplicated(~) method returns a Series of booleans where True represents duplicate rows.

Parameters

1. subset | string or array-like of string | optional

The label of the columns to consider. By default, all columns are considered.

2. keep | boolean or string | optional

The marking rule for duplicates:

Value

Description

"first"

All duplicates are marked as True except the first one.

"last"

All duplicates are marked as True except the last one.

False

All duplicates are marked as True.

By default, keep="first".

Return value

A Series where True represents duplicate rows.

Examples

Consider the following DataFrame:

df = pd.DataFrame({"A":[1,2,1], "B":[3,4,3]})
df
A B
0 1 3
1 2 4
2 1 3

Here, the 1st and 3rd rows are duplicate.

Specifying the keep parameter

first

To mark all duplicate rows except the first one:

df.duplicated() # or explicitly set keep="first"
0 False
1 False
2 True
dtype: bool

last

To mark all duplicate rows except the last one:

df.duplicated(keep="last")
0 True
1 False
2 False
dtype: bool

False

To mark all duplicate rows as True:

df.duplicated(keep=False)
0 True
1 False
2 True
dtype: bool
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Published by Isshin Inada
Edited by 0 others
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