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  * polars.Expr.... 

#  polars.Expr.str.to_lowercase  #

Expr.str.  to_lowercase  (  )  →  Expr  [ [source]  ](https://github.com/pola-
rs/polars/blob/main/py-polars/polars/expr/string.py#L532-L550) #

    

Transform to lowercase variant.

Examples

    
    
    >>> df = pl.DataFrame({"foo": ["CAT", "DOG"]})
    >>> df.with_columns(foo_lower=pl.col("foo").str.to_lowercase())
    shape: (2, 2)
    ┌─────┬───────────┐
    │ foo ┆ foo_lower │
    │ --- ┆ ---       │
    │ str ┆ str       │
    ╞═════╪═══════════╡
    │ CAT ┆ cat       │
    │ DOG ┆ dog       │
    └─────┴───────────┘
    

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  * [ Aggregation ](../aggregation.html)
  * polars.Expr.arg_max 

#  polars.Expr.arg_max  #

Expr.  arg_max  (  )  →  Self  [ [source]  ](https://github.com/pola-
rs/polars/blob/main/py-polars/polars/expr/expr.py#L2421-L2442) #

    

Get the index of the maximal value.

Examples

    
    
    >>> df = pl.DataFrame(
    ...     {
    ...         "a": [20, 10, 30],
    ...     }
    ... )
    >>> df.select(pl.col("a").arg_max())
    shape: (1, 1)
    ┌─────┐
    │ a   │
    │ --- │
    │ u32 │
    ╞═════╡
    │ 2   │
    └─────┘
    

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  * polars.Expr.tanh 

#  polars.Expr.tanh  #

Expr.  tanh  (  )  →  Self  [ [source]  ](https://github.com/pola-
rs/polars/blob/main/py-polars/polars/expr/expr.py#L8613-L8635) #

    

Compute the element-wise value for the hyperbolic tangent.

Returns  :

    

Expr

    

Expression of data type ` Float64  ` .

Examples

    
    
    >>> df = pl.DataFrame({"a": [1.0]})
    >>> df.select(pl.col("a").tanh())
    shape: (1, 1)
    ┌──────────┐
    │ a        │
    │ ---      │
    │ f64      │
    ╞══════════╡
    │ 0.761594 │
    └──────────┘
    

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  * polars.Serie... 

#  polars.Series.list.drop_nulls  #

Series.list.  drop_nulls  (  )  →  Series  [ [source]
](https://github.com/pola-rs/polars/blob/py-0.20.23/py-
polars/polars/series/list.py#L114-L131) #

    

Drop all null values in the list.

The original order of the remaining elements is preserved.

Examples

    
    
    >>> s = pl.Series("values", [[None, 1, None, 2], [None], [3, 4]])
    >>> s.list.drop_nulls()
    shape: (3,)
    Series: 'values' [list[i64]]
    [
        [1, 2]
        []
        [3, 4]
    ]
    

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  * polars.Serie... 

#  polars.Series.list.head  #

Series.list.  head  (  _ n  :  [ int  ](https://docs.python.org/3/library/functions.html#int "\(in Python v3.12\)") |  Expr  =  5  _ )  →  Series  [ [source]  ](https://github.com/pola-rs/polars/blob/py-0.20.23/py-polars/polars/series/list.py#L739-L758) # 
    

Slice the first ` n  ` values of every sublist.

Parameters  :

    

**n**

    

Number of values to return for each sublist.

Examples

    
    
    >>> s = pl.Series("a", [[1, 2, 3, 4], [10, 2, 1]])
    >>> s.list.head(2)
    shape: (2,)
    Series: 'a' [list[i64]]
    [
        [1, 2]
        [10, 2]
    ]
    

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#  polars.Series.list.count_matches  #

Series.list.  count_matches  (  _ element  :  IntoExpr  _ )  →  Series  [
[source]  ](https://github.com/pola-rs/polars/blob/py-0.20.23/py-
polars/polars/series/list.py#L810-L832) #

    

Count how often the value produced by ` element  ` occurs.

Parameters  :

    

**element**

    

An expression that produces a single value

Examples

    
    
    >>> s = pl.Series("a", [[0], [1], [1, 2, 3, 2], [1, 2, 1], [4, 4]])
    >>> s.list.count_matches(1)
    shape: (5,)
    Series: 'a' [u32]
    [
        0
        1
        1
        2
        0
    ]
    

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  * polars.Expr.is_first 

#  polars.Expr.is_first  #

Expr.  is_first  (  )  →  Self  [ [source]  ](https://github.com/pola-
rs/polars/blob/main/py-polars/polars/expr/expr.py#L9985-L9998) #

    

Return a boolean mask indicating the first occurrence of each distinct value.

Deprecated since version 0.19.3:  This method has been renamed to [ `
Expr.is_first_distinct()  `
](polars.Expr.is_first_distinct.html#polars.Expr.is_first_distinct
"polars.Expr.is_first_distinct") .

Returns  :

    

Expr

    

Expression of data type ` Boolean  ` .

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  * __
  * [ Temporal ](../temporal.html)
  * polars.Expr.dt.epoch 

#  polars.Expr.dt.epoch  #

Expr.dt.  epoch  (  _ time_unit  :  EpochTimeUnit  =  'us'  _ )  →  Expr  [
[source]  ](https://github.com/pola-rs/polars/blob/main/py-
polars/polars/expr/datetime.py#L1523-L1563) #

    

Get the time passed since the Unix EPOCH in the give time unit.

Parameters  :

    

**time_unit** {‘ns’, ‘us’, ‘ms’, ‘s’, ‘d’}

    

Time unit.

Examples

    
    
    >>> from datetime import date
    >>> df = (
    ...     pl.date_range(date(2001, 1, 1), date(2001, 1, 3), eager=True)
    ...     .alias("date")
    ...     .to_frame()
    ... )
    >>> df.with_columns(
    ...     pl.col("date").dt.epoch().alias("epoch_ns"),
    ...     pl.col("date").dt.epoch(time_unit="s").alias("epoch_s"),
    ... )
    shape: (3, 3)
    ┌────────────┬─────────────────┬───────────┐
    │ date       ┆ epoch_ns        ┆ epoch_s   │
    │ ---        ┆ ---             ┆ ---       │
    │ date       ┆ i64             ┆ i64       │
    ╞════════════╪═════════════════╪═══════════╡
    │ 2001-01-01 ┆ 978307200000000 ┆ 978307200 │
    │ 2001-01-02 ┆ 978393600000000 ┆ 978393600 │
    │ 2001-01-03 ┆ 978480000000000 ┆ 978480000 │
    └────────────┴─────────────────┴───────────┘
    

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