(../../api/polars.exceptions.SchemaError.html)
    * [ polars.exceptions.SchemaFieldNotFoundError ](../../api/polars.exceptions.SchemaFieldNotFoundError.html)
    * [ polars.exceptions.ShapeError ](../../api/polars.exceptions.ShapeError.html)
    * [ polars.exceptions.StructFieldNotFoundError ](../../api/polars.exceptions.StructFieldNotFoundError.html)
    * [ polars.exceptions.TooManyRowsReturnedError ](../../api/polars.exceptions.TooManyRowsReturnedError.html)

  * [ Testing ](../../testing.html) __
    * [ polars.testing.assert_frame_equal ](../../api/polars.testing.assert_frame_equal.html)
    * [ polars.testing.assert_frame_not_equal ](../../api/polars.testing.assert_frame_not_equal.html)
    * [ polars.testing.assert_series_equal ](../../api/polars.testing.assert_series_equal.html)
    * [ polars.testing.assert_series_not_equal ](../../api/polars.testing.assert_series_not_equal.html)
    * [ polars.testing.parametric.dataframes ](../../api/polars.testing.parametric.dataframes.html)
    * [ polars.testing.parametric.series ](../../api/polars.testing.parametric.series.html)
    * [ polars.testing.parametric.column ](../../api/polars.testing.parametric.column.html)
    * [ polars.testing.parametric.columns ](../../api/polars.testing.parametric.columns.html)
    * [ polars.testing.parametric.create_list_strategy ](../../api/polars.testing.parametric.create_list_strategy.html)
    * [ polars.testing.parametric.load_profile ](../../api/polars.testing.parametric.load_profile.html)
    * [ polars.testing.parametric.set_profile ](../../api/polars.testing.parametric.set_profile.html)

  * [ Metadata ](../../metadata.html) __
    * [ polars.build_info ](../../api/polars.build_info.html)
    * [ polars.get_index_type ](../../api/polars.get_index_type.html)
    * [ polars.show_versions ](../../api/polars.show_versions.html)
    * [ polars.thread_pool_size ](../../api/polars.thread_pool_size.html)
    * [ polars.threadpool_size ](../../api/polars.threadpool_size.html)

  * [ __ ](../../../index.html)
  * [ Python API reference ](../../index.html)
  * __
  * [ List ](../list.html)
  * polars.Serie... 

#  polars.Series.list.eval  #

Series.list.  eval  (  _ expr  :  Expr  _ , _ *  _ , _ parallel  :  [ bool
](https://docs.python.org/3/library/functions.html#bool "\(in Python v3.12\)")
=  False  _ )  →  Series  [ [source]  ](https://github.com/pola-
rs/polars/blob/py-0.20.23/py-polars/polars/series/list.py#L932-L959) #

    

Run any polars expression against the lists’ elements.

Parameters  :

    

**expr**

    

Expression to run. Note that you can select an element with ` pl.first()  ` ,
or ` pl.col()  `

**parallel**

    

Run all expression parallel. Don’t activate this blindly. Parallelism is worth
it if there is enough work to do per thread.

This likely should not be use in the group by context, because we already
parallel execution per group

Examples

    
    
    >>> s = pl.Series("a", [[1, 4], [8, 5], [3, 2]])
    >>> s.list.eval(pl.element().rank())
    shape: (3,)
    Series: 'a' [list[f64]]
    [
        [1.0, 2.0]
        [2.0, 1.0]
        [2.0, 1.0]
    ]
    

[ __ previous  polars.Series.list.diff  ](polars.Series.list.diff.html
"previous page") [ next  polars.Series.list.explode  __
](polars.Series.list.explode.html "next page")

__ On this page

  * ` Series.list.eval()  `

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