pi/polars.exceptions.DuplicateError.html)
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  * [ __ ](../../../index.html)
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  * __
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  * polars.LazyF... 

#  polars.LazyFrame.unique  #

LazyFrame.  unique  (

     _ subset  :  ColumnNameOrSelector  |  Collection  [  ColumnNameOrSelector  ]  |  [ None  ](https://docs.python.org/3/library/constants.html#None "\(in Python v3.12\)") =  None  _ , 
     _ *  _ , 
     _ keep  :  UniqueKeepStrategy  =  'any'  _ , 
     _ maintain_order  :  [ bool  ](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.12\)") =  False  _ , 
)  →  Self  [ [source]  ](https://github.com/pola-rs/polars/blob/main/py-
polars/polars/lazyframe/frame.py#L5374-L5456) #

    

Drop duplicate rows from this DataFrame.

Parameters  :

    

**subset**

    

Column name(s) or selector(s), to consider when identifying duplicate rows. If
set to ` None  ` (default), use all columns.

**keep** {‘first’, ‘last’, ‘any’, ‘none’}

    

Which of the duplicate rows to keep.

  * ‘any’: Does not give any guarantee of which row is kept. 
    

This allows more optimizations.

  * ‘none’: Don’t keep duplicate rows. 

  * ‘first’: Keep first unique row. 

  * ‘last’: Keep last unique row. 

**maintain_order**

    

Keep the same order as the original DataFrame. This is more expensive to
compute. Settings this to ` Tru