Enum polars_lazy::dsl::Expr

pub enum Expr {
Show 26 variants Alias(Arc<Expr>, Arc<str>), Column(Arc<str>), Columns(Vec<String>), DtypeColumn(Vec<DataType>), Literal(LiteralValue), BinaryExpr { left: Arc<Expr>, op: Operator, right: Arc<Expr>, }, Cast { expr: Arc<Expr>, data_type: DataType, strict: bool, }, Sort { expr: Arc<Expr>, options: SortOptions, }, Gather { expr: Arc<Expr>, idx: Arc<Expr>, returns_scalar: bool, }, SortBy { expr: Arc<Expr>, by: Vec<Expr>, sort_options: SortMultipleOptions, }, Agg(AggExpr), Ternary { predicate: Arc<Expr>, truthy: Arc<Expr>, falsy: Arc<Expr>, }, Function { input: Vec<Expr>, function: FunctionExpr, options: FunctionOptions, }, Explode(Arc<Expr>), Filter { input: Arc<Expr>, by: Arc<Expr>, }, Window { function: Arc<Expr>, partition_by: Vec<Expr>, options: WindowType, }, Wildcard, Slice { input: Arc<Expr>, offset: Arc<Expr>, length: Arc<Expr>, }, Exclude(Arc<Expr>, Vec<Excluded>), KeepName(Arc<Expr>), Len, Nth(i64), RenameAlias { function: SpecialEq<Arc<dyn RenameAliasFn>>, expr: Arc<Expr>, }, AnonymousFunction { input: Vec<Expr>, function: SpecialEq<Arc<dyn SeriesUdf>>, output_type: SpecialEq<Arc<dyn FunctionOutputField>>, options: FunctionOptions, }, SubPlan(SpecialEq<Arc<LogicalPlan>>, Vec<String>), Selector(Selector),
}
Expand description

Expressions that can be used in various contexts. Queries consist of multiple expressions. When using the polars lazy API, don’t construct an Expr directly; instead, create one using the functions in the polars_lazy::dsl module. See that module’s docs for more info.

Variants§

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Alias(Arc<Expr>, Arc<str>)

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Column(Arc<str>)

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Columns(Vec<String>)

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DtypeColumn(Vec<DataType>)

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Literal(LiteralValue)

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BinaryExpr

Fields

§left: Arc<Expr>
§right: Arc<Expr>
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Cast

Fields

§expr: Arc<Expr>
§data_type: DataType
§strict: bool
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Sort

Fields

§expr: Arc<Expr>
§options: SortOptions
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Gather

Fields

§expr: Arc<Expr>
§idx: Arc<Expr>
§returns_scalar: bool
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SortBy

Fields

§expr: Arc<Expr>
§by: Vec<Expr>
§sort_options: SortMultipleOptions
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Agg(AggExpr)

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Ternary

A ternary operation if true then “foo” else “bar”

Fields

§predicate: Arc<Expr>
§truthy: Arc<Expr>
§falsy: Arc<Expr>
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Function

Fields

§input: Vec<Expr>

function arguments

§function: FunctionExpr

function to apply

§options: FunctionOptions
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Explode(Arc<Expr>)

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Filter

Fields

§input: Arc<Expr>
§by: Arc<Expr>
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Window

See postgres window functions

Fields

§function: Arc<Expr>

Also has the input. i.e. avg(“foo”)

§partition_by: Vec<Expr>
§options: WindowType
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Wildcard

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Slice

Fields

§input: Arc<Expr>
§offset: Arc<Expr>

length is not yet known so we accept negative offsets

§length: Arc<Expr>
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Exclude(Arc<Expr>, Vec<Excluded>)

Can be used in a select statement to exclude a column from selection

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KeepName(Arc<Expr>)

Set root name as Alias

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Len

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Nth(i64)

Take the nth column in the DataFrame

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RenameAlias

Fields

§function: SpecialEq<Arc<dyn RenameAliasFn>>
§expr: Arc<Expr>
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AnonymousFunction

Fields

§input: Vec<Expr>

function arguments

§function: SpecialEq<Arc<dyn SeriesUdf>>

function to apply

§output_type: SpecialEq<Arc<dyn FunctionOutputField>>

output dtype of the function

§options: FunctionOptions
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SubPlan(SpecialEq<Arc<LogicalPlan>>, Vec<String>)

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Selector(Selector)

Expressions in this node should only be expanding e.g. Expr::Columns Expr::Dtypes Expr::Wildcard Expr::Exclude

Implementations§

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impl Expr

pub fn to_dot(&self) -> Result<String, PolarsError>

Get a dot language representation of the Expression.

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impl Expr

pub fn floor_div(self, rhs: Expr) -> Expr

Floor divide self by rhs.

pub fn pow<E>(self, exponent: E) -> Expr
where E: Into<Expr>,

Raise expression to the power exponent

pub fn sqrt(self) -> Expr

Compute the square root of the given expression

pub fn cbrt(self) -> Expr

Compute the cube root of the given expression

pub fn cos(self) -> Expr

Available on crate feature trigonometry only.

Compute the cosine of the given expression

pub fn cot(self) -> Expr

Available on crate feature trigonometry only.

Compute the cotangent of the given expression

pub fn sin(self) -> Expr

Available on crate feature trigonometry only.

Compute the sine of the given expression

pub fn tan(self) -> Expr

Available on crate feature trigonometry only.

Compute the tangent of the given expression

pub fn arccos(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse cosine of the given expression

pub fn arcsin(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse sine of the given expression

pub fn arctan(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse tangent of the given expression

pub fn arctan2(self, x: Expr) -> Expr

Available on crate feature trigonometry only.

Compute the inverse tangent of the given expression, with the angle expressed as the argument of a complex number

pub fn cosh(self) -> Expr

Available on crate feature trigonometry only.

Compute the hyperbolic cosine of the given expression

pub fn sinh(self) -> Expr

Available on crate feature trigonometry only.

Compute the hyperbolic sine of the given expression

pub fn tanh(self) -> Expr

Available on crate feature trigonometry only.

Compute the hyperbolic tangent of the given expression

pub fn arccosh(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse hyperbolic cosine of the given expression

pub fn arcsinh(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse hyperbolic sine of the given expression

pub fn arctanh(self) -> Expr

Available on crate feature trigonometry only.

Compute the inverse hyperbolic tangent of the given expression

pub fn degrees(self) -> Expr

Available on crate feature trigonometry only.

Convert from radians to degrees

pub fn radians(self) -> Expr

Available on crate feature trigonometry only.

Convert from degrees to radians

pub fn sign(self) -> Expr

Available on crate feature sign only.

Compute the sign of the given expression

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impl Expr

pub fn to_field( &self, schema: &Schema, ctxt: Context ) -> Result<Field, PolarsError>

Get Field result of the expression. The schema is the input data.

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impl Expr

pub fn map_python(self, func: PythonUdfExpression, agg_list: bool) -> Expr

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impl Expr

pub fn shuffle(self, seed: Option<u64>) -> Expr

pub fn sample_n( self, n: Expr, with_replacement: bool, shuffle: bool, seed: Option<u64> ) -> Expr

pub fn sample_frac( self, frac: Expr, with_replacement: bool, shuffle: bool, seed: Option<u64> ) -> Expr

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impl Expr

pub fn std(self, ddof: u8) -> Expr

Standard deviation of the values of the Series.

pub fn var(self, ddof: u8) -> Expr

Variance of the values of the Series.

pub fn min(self) -> Expr

Reduce groups to minimal value.

pub fn max(self) -> Expr

Reduce groups to maximum value.

pub fn nan_min(self) -> Expr

Reduce groups to minimal value.

pub fn nan_max(self) -> Expr

Reduce groups to maximum value.

pub fn mean(self) -> Expr

Reduce groups to the mean value.

pub fn median(self) -> Expr

Reduce groups to the median value.

pub fn sum(self) -> Expr

Reduce groups to the sum of all the values.

pub fn hist( self, bins: Option<Expr>, bin_count: Option<usize>, include_category: bool, include_breakpoint: bool ) -> Expr

Available on crate feature hist only.

Compute the histogram of a dataset.

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impl Expr

pub fn eq<E>(self, other: E) -> Expr
where E: Into<Expr>,

Compare Expr with other Expr on equality.

pub fn eq_missing<E>(self, other: E) -> Expr
where E: Into<Expr>,

Compare Expr with other Expr on equality where None == None.

pub fn neq<E>(self, other: E) -> Expr
where E: Into<Expr>,

Compare Expr with other Expr on non-equality.

pub fn neq_missing<E>(self, other: E) -> Expr
where E: Into<Expr>,

Compare Expr with other Expr on non-equality where None == None.

pub fn lt<E>(self, other: E) -> Expr
where E: Into<Expr>,

Check if Expr < Expr.

pub fn gt<E>(self, other: E) -> Expr
where E: Into<Expr>,

Check if Expr > Expr.

pub fn gt_eq<E>(self, other: E) -> Expr
where E: Into<Expr>,

Check if Expr >= Expr.

pub fn lt_eq<E>(self, other: E) -> Expr
where E: Into<Expr>,

Check if Expr <= Expr.

pub fn not(self) -> Expr

Negate Expr.

pub fn alias(self, name: &str) -> Expr

Rename Column.

pub fn is_null(self) -> Expr

Run is_null operation on Expr.

pub fn is_not_null(self) -> Expr

Run is_not_null operation on Expr.

pub fn drop_nulls(self) -> Expr

Drop null values.

pub fn drop_nans(self) -> Expr

Drop NaN values.

pub fn n_unique(self) -> Expr

Get the number of unique values in the groups.

pub fn first(self) -> Expr

Get the first value in the group.

pub fn last(self) -> Expr

Get the last value in the group.

pub fn implode(self) -> Expr

GroupBy the group to a Series.

pub fn quantile(self, quantile: Expr, interpol: QuantileInterpolOptions) -> Expr

Compute the quantile per group.

pub fn agg_groups(self) -> Expr

Get the group indexes of the group by operation.

pub fn flatten(self) -> Expr

Alias for explode.

pub fn explode(self) -> Expr

Explode the String/List column.

pub fn slice<E, F>(self, offset: E, length: F) -> Expr
where E: Into<Expr>, F: Into<Expr>,

Slice the Series. offset may be negative.

pub fn append<E>(self, other: E, upcast: bool) -> Expr
where E: Into<Expr>,

Append expressions. This is done by adding the chunks of other to this Series.

pub fn head(self, length: Option<usize>) -> Expr

Get the first n elements of the Expr result.

pub fn tail(self, length: Option<usize>) -> Expr

Get the last n elements of the Expr result.

pub fn unique(self) -> Expr

Get unique values of this expression.

pub fn unique_stable(self) -> Expr

Get unique values of this expression, while maintaining order. This requires more work than Expr::unique.

pub fn arg_unique(self) -> Expr

Get the first index of unique values of this expression.

pub fn arg_min(self) -> Expr

Get the index value that has the minimum value.

pub fn arg_max(self) -> Expr

Get the index value that has the maximum value.

pub fn arg_sort(self, sort_options: SortOptions) -> Expr

Get the index values that would sort this expression.

pub fn search_sorted<E>(self, element: E, side: SearchSortedSide) -> Expr
where E: Into<Expr>,

Available on crate feature search_sorted only.

Find indices where elements should be inserted to maintain order.

pub fn strict_cast(self, data_type: DataType) -> Expr

Cast expression to another data type. Throws an error if conversion had overflows.

pub fn cast(self, data_type: DataType) -> Expr

Cast expression to another data type.

pub fn gather<E>(self, idx: E) -> Expr
where E: Into<Expr>,

Take the values by idx.

pub fn get<E>(self, idx: E) -> Expr
where E: Into<Expr>,

Take the values by a single index.

pub fn sort(self, options: SortOptions) -> Expr

Sort with given options.

§Example
let lf = df! {
   "a" => [Some(5), Some(4), Some(3), Some(2), None]
}?
.lazy();

let sorted = lf
    .select(
        vec![col("a").sort(SortOptions::default())],
    )
    .collect()?;

assert_eq!(
    sorted,
    df! {
        "a" => [None, Some(2), Some(3), Some(4), Some(5)]
    }?
);

See SortOptions for more options.

pub fn top_k(self, k: Expr) -> Expr

Available on crate feature top_k only.

Returns the k largest elements.

This has time complexity O(n + k log(n)).

pub fn bottom_k(self, k: Expr) -> Expr

Available on crate feature top_k only.

Returns the k smallest elements.

This has time complexity O(n + k log(n)).

pub fn reverse(self) -> Expr

Reverse column

pub fn map<F>( self, function: F, output_type: SpecialEq<Arc<dyn FunctionOutputField>> ) -> Expr
where F: Fn(Series) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

Apply a function/closure once the logical plan get executed.

This function is very similar to Expr::apply, but differs in how it handles aggregations.

  • map should be used for operations that are independent of groups, e.g. multiply * 2, or raise to the power
  • apply should be used for operations that work on a group of data. e.g. sum, count, etc.

It is the responsibility of the caller that the schema is correct by giving the correct output_type. If None given the output type of the input expr is used.

pub fn map_many<F>( self, function: F, arguments: &[Expr], output_type: SpecialEq<Arc<dyn FunctionOutputField>> ) -> Expr
where F: Fn(&mut [Series]) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

Apply a function/closure once the logical plan get executed with many arguments.

See the Expr::map function for the differences between map and apply.

pub fn map_list<F>( self, function: F, output_type: SpecialEq<Arc<dyn FunctionOutputField>> ) -> Expr
where F: Fn(Series) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

Apply a function/closure once the logical plan get executed.

This function is very similar to apply, but differs in how it handles aggregations.

  • map should be used for operations that are independent of groups, e.g. multiply * 2, or raise to the power
  • apply should be used for operations that work on a group of data. e.g. sum, count, etc.
  • map_list should be used when the function expects a list aggregated series.

pub fn function_with_options<F>( self, function: F, output_type: SpecialEq<Arc<dyn FunctionOutputField>>, options: FunctionOptions ) -> Expr
where F: Fn(Series) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

A function that cannot be expressed with map or apply and requires extra settings.

pub fn apply<F>( self, function: F, output_type: SpecialEq<Arc<dyn FunctionOutputField>> ) -> Expr
where F: Fn(Series) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

Apply a function/closure over the groups. This should only be used in a group_by aggregation.

It is the responsibility of the caller that the schema is correct by giving the correct output_type. If None given the output type of the input expr is used.

This difference with map is that apply will create a separate Series per group.

  • map should be used for operations that are independent of groups, e.g. multiply * 2, or raise to the power
  • apply should be used for operations that work on a group of data. e.g. sum, count, etc.

pub fn apply_many<F>( self, function: F, arguments: &[Expr], output_type: SpecialEq<Arc<dyn FunctionOutputField>> ) -> Expr
where F: Fn(&mut [Series]) -> Result<Option<Series>, PolarsError> + 'static + Send + Sync,

Apply a function/closure over the groups with many arguments. This should only be used in a group_by aggregation.

See the Expr::apply function for the differences between map and apply.

pub fn apply_many_private( self, function_expr: FunctionExpr, arguments: &[Expr], returns_scalar: bool, cast_to_supertypes: bool ) -> Expr

pub fn map_many_private( self, function_expr: FunctionExpr, arguments: &[Expr], returns_scalar: bool, cast_to_supertypes: bool ) -> Expr

pub fn is_finite(self) -> Expr

Get mask of finite values if dtype is Float.

pub fn is_infinite(self) -> Expr

Get mask of infinite values if dtype is Float.

pub fn is_nan(self) -> Expr

Get mask of NaN values if dtype is Float.

pub fn is_not_nan(self) -> Expr

Get inverse mask of NaN values if dtype is Float.

pub fn shift(self, n: Expr) -> Expr

Shift the values in the array by some period. See the eager implementation.

pub fn shift_and_fill<E, IE>(self, n: E, fill_value: IE) -> Expr
where E: Into<Expr>, IE: Into<Expr>,

Shift the values in the array by some period and fill the resulting empty values.

pub fn cum_count(self, reverse: bool) -> Expr

Available on crate feature cum_agg only.

Cumulatively count values from 0 to len.

pub fn cum_sum(self, reverse: bool) -> Expr

Available on crate feature cum_agg only.

Get an array with the cumulative sum computed at every element.

pub fn cum_prod(self, reverse: bool) -> Expr

Available on crate feature cum_agg only.

Get an array with the cumulative product computed at every element.

pub fn cum_min(self, reverse: bool) -> Expr

Available on crate feature cum_agg only.

Get an array with the cumulative min computed at every element.

pub fn cum_max(self, reverse: bool) -> Expr

Available on crate feature cum_agg only.

Get an array with the cumulative max computed at every element.

pub fn product(self) -> Expr

Get the product aggregation of an expression.

pub fn backward_fill(self, limit: Option<u64>) -> Expr

Fill missing value with next non-null.

pub fn forward_fill(self, limit: Option<u64>) -> Expr

Fill missing value with previous non-null.

pub fn round(self, decimals: u32) -> Expr

Available on crate feature round_series only.

Round underlying floating point array to given decimal numbers.

pub fn round_sig_figs(self, digits: i32) -> Expr

Available on crate feature round_series only.

Round to a number of significant figures.

pub fn floor(self) -> Expr

Available on crate feature round_series only.

Floor underlying floating point array to the lowest integers smaller or equal to the float value.

pub fn pi() -> Expr

Available on crate feature round_series only.

Constant Pi

pub fn ceil(self) -> Expr

Available on crate feature round_series only.

Ceil underlying floating point array to the highest integers smaller or equal to the float value.

pub fn clip(self, min: Expr, max: Expr) -> Expr

Available on crate feature round_series only.

Clip underlying values to a set boundary.

pub fn clip_max(self, max: Expr) -> Expr

Available on crate feature round_series only.

Clip underlying values to a set boundary.

pub fn clip_min(self, min: Expr) -> Expr

Available on crate feature round_series only.

Clip underlying values to a set boundary.

pub fn abs(self) -> Expr

Available on crate feature abs only.

Convert all values to their absolute/positive value.

pub fn over<E, IE>(self, partition_by: E) -> Expr
where E: AsRef<[IE]>, IE: Into<Expr> + Clone,

Apply window function over a subgroup. This is similar to a group_by + aggregation + self join. Or similar to window functions in Postgres.

§Example
#[macro_use] extern crate polars_core;
use polars_core::prelude::*;
use polars_lazy::prelude::*;

fn example() -> PolarsResult<()> {
    let df = df! {
            "groups" => &[1, 1, 2, 2, 1, 2, 3, 3, 1],
            "values" => &[1, 2, 3, 4, 5, 6, 7, 8, 8]
        }?;

    let out = df
     .lazy()
     .select(&[
         col("groups"),
         sum("values").over([col("groups")]),
     ])
     .collect()?;
    println!("{}", &out);
    Ok(())
}

Outputs:

╭────────┬────────╮
│ groups ┆ values │
│ ---    ┆ ---    │
│ i32    ┆ i32    │
╞════════╪════════╡
│ 1      ┆ 16     │
│ 1      ┆ 16     │
│ 2      ┆ 13     │
│ 2      ┆ 13     │
│ …      ┆ …      │
│ 1      ┆ 16     │
│ 2      ┆ 13     │
│ 3      ┆ 15     │
│ 3      ┆ 15     │
│ 1      ┆ 16     │
╰────────┴────────╯

pub fn over_with_options<E, IE>( self, partition_by: E, options: WindowMapping ) -> Expr
where E: AsRef<[IE]>, IE: Into<Expr> + Clone,

pub fn rolling(self, options: RollingGroupOptions) -> Expr

Available on crate feature dynamic_group_by only.

pub fn fill_null<E>(self, fill_value: E) -> Expr
where E: Into<Expr>,

Replace the null values by a value.

pub fn fill_null_with_strategy(self, strategy: FillNullStrategy) -> Expr

pub fn fill_nan<E>(self, fill_value: E) -> Expr
where E: Into<Expr>,

Replace the floating point NaN values by a value.

pub fn count(self) -> Expr

Count the values of the Series or Get counts of the group by operation.

pub fn len(self) -> Expr

pub fn is_duplicated(self) -> Expr

Available on crate feature is_unique only.

Get a mask of duplicated values.

pub fn is_between<E>(self, lower: E, upper: E, closed: ClosedInterval) -> Expr
where E: Into<Expr>,

Available on crate feature is_between only.

pub fn is_unique(self) -> Expr

Available on crate feature is_unique only.

Get a mask of unique values.

pub fn approx_n_unique(self) -> Expr

Available on crate feature approx_unique only.

Get the approximate count of unique values.

pub fn and<E>(self, expr: E) -> Expr
where E: Into<Expr>,

“and” operation.

pub fn xor<E>(self, expr: E) -> Expr
where E: Into<Expr>,

“xor” operation.

pub fn or<E>(self, expr: E) -> Expr
where E: Into<Expr>,

“or” operation.

pub fn logical_or<E>(self, expr: E) -> Expr
where E: Into<Expr>,

“or” operation.

pub fn logical_and<E>(self, expr: E) -> Expr
where E: Into<Expr>,

“or” operation.

pub fn filter<E>(self, predicate: E) -> Expr
where E: Into<Expr>,

Filter a single column.

Should be used in aggregation context. If you want to filter on a DataFrame level, use LazyFrame::filter.

pub fn is_in<E>(self, other: E) -> Expr
where E: Into<Expr>,

Available on crate feature is_in only.

Check if the values of the left expression are in the lists of the right expr.

pub fn sort_by<E, IE>(self, by: E, sort_options: SortMultipleOptions) -> Expr
where E: AsRef<[IE]>, IE: Into<Expr> + Clone,

Sort this column by the ordering of another column evaluated from given expr. Can also be used in a group_by context to sort the groups.

§Example
let lf = df! {
    "a" => [1, 2, 3, 4, 5],
    "b" => [5, 4, 3, 2, 1]
}?.lazy();

let sorted = lf
    .select(
        vec![col("a").sort_by(col("b"), SortOptions::default())],
    )
    .collect()?;

assert_eq!(
    sorted,
    df! { "a" => [5, 4, 3, 2, 1] }?
);

pub fn repeat_by<E>(self, by: E) -> Expr
where E: Into<Expr>,

Available on crate feature repeat_by only.

Repeat the column n times, where n is determined by the values in by. This yields an Expr of dtype List.

pub fn is_first_distinct(self) -> Expr

Available on crate feature is_first_distinct only.

Get a mask of the first unique value.

pub fn is_last_distinct(self) -> Expr

Available on crate feature is_last_distinct only.

Get a mask of the last unique value.

pub fn dot<E>(self, other: E) -> Expr
where E: Into<Expr>,

Compute the dot/inner product between two expressions.

pub fn mode(self) -> Expr

Available on crate feature mode only.

Compute the mode(s) of this column. This is the most occurring value.

pub fn exclude(self, columns: impl IntoVec<String>) -> Expr

Exclude a column from a wildcard/regex selection.

You may also use regexes in the exclude as long as they start with ^ and end with $/

pub fn exclude_dtype<D>(self, dtypes: D) -> Expr
where D: AsRef<[DataType]>,

pub fn interpolate(self, method: InterpolationMethod) -> Expr

Available on crate feature interpolate only.

Fill null values using interpolation.

pub fn rolling_min(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling minimum.

See: [RollingAgg::rolling_min]

pub fn rolling_max(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling maximum.

See: [RollingAgg::rolling_max]

pub fn rolling_mean(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling mean.

See: [RollingAgg::rolling_mean]

pub fn rolling_sum(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling sum.

See: [RollingAgg::rolling_sum]

pub fn rolling_median(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling median.

See: [RollingAgg::rolling_median]

pub fn rolling_quantile( self, interpol: QuantileInterpolOptions, quantile: f64, options: RollingOptions ) -> Expr

Available on crate feature rolling_window only.

Apply a rolling quantile.

See: [RollingAgg::rolling_quantile]

pub fn rolling_var(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling variance.

pub fn rolling_std(self, options: RollingOptions) -> Expr

Available on crate feature rolling_window only.

Apply a rolling std-dev.

pub fn rolling_skew(self, window_size: usize, bias: bool) -> Expr

Available on crate features rolling_window and moment only.

Apply a rolling skew.

pub fn rolling_map( self, f: Arc<dyn Fn(&Series) -> Series + Send + Sync>, output_type: SpecialEq<Arc<dyn FunctionOutputField>>, options: RollingOptionsFixedWindow ) -> Expr

Available on crate feature rolling_window only.

Apply a custom function over a rolling/ moving window of the array. This has quite some dynamic dispatch, so prefer rolling_min, max, mean, sum over this.

pub fn rolling_map_float<F>(self, window_size: usize, f: F) -> Expr
where F: 'static + FnMut(&mut ChunkedArray<Float64Type>) -> Option<f64> + Send + Sync + Copy,

Available on crate feature rolling_window only.

Apply a custom function over a rolling/ moving window of the array. Prefer this over rolling_apply in case of floating point numbers as this is faster. This has quite some dynamic dispatch, so prefer rolling_min, max, mean, sum over this.

pub fn peak_min(self) -> Expr

Available on crate feature peaks only.

pub fn peak_max(self) -> Expr

Available on crate feature peaks only.

pub fn rank(self, options: RankOptions, seed: Option<u64>) -> Expr

Available on crate feature rank only.

Assign ranks to data, dealing with ties appropriately.

pub fn replace<E>( self, old: E, new: E, default: Option<E>, return_dtype: Option<DataType> ) -> Expr
where E: Into<Expr>,

Available on crate feature replace only.

Replace the given values with other values.

pub fn cut( self, breaks: Vec<f64>, labels: Option<Vec<String>>, left_closed: bool, include_breaks: bool ) -> Expr

Available on crate feature cutqcut only.

Bin continuous values into discrete categories.

pub fn qcut( self, probs: Vec<f64>, labels: Option<Vec<String>>, left_closed: bool, allow_duplicates: bool, include_breaks: bool ) -> Expr

Available on crate feature cutqcut only.

Bin continuous values into discrete categories based on their quantiles.

pub fn qcut_uniform( self, n_bins: usize, labels: Option<Vec<String>>, left_closed: bool, allow_duplicates: bool, include_breaks: bool ) -> Expr

Available on crate feature cutqcut only.

Bin continuous values into discrete categories using uniform quantile probabilities.

pub fn rle(self) -> Expr

Available on crate feature rle only.

Get the lengths of runs of identical values.

pub fn rle_id(self) -> Expr

Available on crate feature rle only.

Similar to rle, but maps values to run IDs.

pub fn diff(self, n: i64, null_behavior: NullBehavior) -> Expr

Available on crate feature diff only.

Calculate the n-th discrete difference between values.

pub fn pct_change(self, n: Expr) -> Expr

Available on crate feature pct_change only.

Computes percentage change between values.

pub fn skew(self, bias: bool) -> Expr

Available on crate feature moment only.

Compute the sample skewness of a data set.

For normally distributed data, the skewness should be about zero. For uni-modal continuous distributions, a skewness value greater than zero means that there is more weight in the right tail of the distribution. The function skewtest can be used to determine if the skewness value is close enough to zero, statistically speaking.

see: scipy

pub fn kurtosis(self, fisher: bool, bias: bool) -> Expr

Available on crate feature moment only.

Compute the kurtosis (Fisher or Pearson).

Kurtosis is the fourth central moment divided by the square of the variance. If Fisher’s definition is used, then 3.0 is subtracted from the result to give 0.0 for a normal distribution. If bias is False then the kurtosis is calculated using k statistics to eliminate bias coming from biased moment estimators.

pub fn upper_bound(self) -> Expr

Get maximal value that could be hold by this dtype.

pub fn lower_bound(self) -> Expr

Get minimal value that could be hold by this dtype.

pub fn reshape(self, dimensions: &[i64]) -> Expr

pub fn ewm_mean(self, options: EWMOptions) -> Expr

Available on crate feature ewma only.

Calculate the exponentially-weighted moving average.

pub fn ewm_mean_by( self, times: Expr, half_life: Duration, check_sorted: bool ) -> Expr

Available on crate feature ewma_by only.

Calculate the exponentially-weighted moving average by a time column.

pub fn ewm_std(self, options: EWMOptions) -> Expr

Available on crate feature ewma only.

Calculate the exponentially-weighted moving standard deviation.

pub fn ewm_var(self, options: EWMOptions) -> Expr

Available on crate feature ewma only.

Calculate the exponentially-weighted moving variance.

pub fn any(self, ignore_nulls: bool) -> Expr

Returns whether any of the values in the column are true.

If ignore_nulls is False, Kleene logic is used to deal with nulls: if the column contains any null values and no true values, the output is null.

pub fn all(self, ignore_nulls: bool) -> Expr

Returns whether all values in the column are true.

If ignore_nulls is False, Kleene logic is used to deal with nulls: if the column contains any null values and no true values, the output is null.

pub fn shrink_dtype(self) -> Expr

Shrink numeric columns to the minimal required datatype needed to fit the extrema of this Series. This can be used to reduce memory pressure.

pub fn value_counts(self, sort: bool, parallel: bool) -> Expr

Available on crate feature dtype-struct only.

Count all unique values and create a struct mapping value to count. (Note that it is better to turn parallel off in the aggregation context).

pub fn unique_counts(self) -> Expr

Available on crate feature unique_counts only.

Returns a count of the unique values in the order of appearance. This method differs from [Expr::value_counts] in that it does not return the values, only the counts and might be faster.

pub fn log(self, base: f64) -> Expr

Available on crate feature log only.

Compute the logarithm to a given base.

pub fn log1p(self) -> Expr

Available on crate feature log only.

Compute the natural logarithm of all elements plus one in the input array.

pub fn exp(self) -> Expr

Available on crate feature log only.

Calculate the exponential of all elements in the input array.

pub fn entropy(self, base: f64, normalize: bool) -> Expr

Available on crate feature log only.

Compute the entropy as -sum(pk * log(pk). where pk are discrete probabilities.

pub fn null_count(self) -> Expr

Get the null count of the column/group.

pub fn set_sorted_flag(self, sorted: IsSorted) -> Expr

Set this Series as sorted so that downstream code can use fast paths for sorted arrays.

§Warning

This can lead to incorrect results if this Series is not sorted!! Use with care!

pub fn hash(self, k0: u64, k1: u64, k2: u64, k3: u64) -> Expr

Available on crate feature row_hash only.

Compute the hash of every element.

pub fn to_physical(self) -> Expr

pub fn gather_every(self, n: usize, offset: usize) -> Expr

pub fn reinterpret(self, signed: bool) -> Expr

Available on crate feature reinterpret only.

pub fn extend_constant(self, value: Expr, n: Expr) -> Expr

pub fn str(self) -> StringNameSpace

Available on crate feature strings only.

pub fn binary(self) -> BinaryNameSpace

pub fn dt(self) -> DateLikeNameSpace

Available on crate feature temporal only.

pub fn list(self) -> ListNameSpace

pub fn name(self) -> ExprNameNameSpace

pub fn arr(self) -> ArrayNameSpace

Available on crate feature dtype-array only.

pub fn cat(self) -> CategoricalNameSpace

Available on crate feature dtype-categorical only.

pub fn struct_(self) -> StructNameSpace

Available on crate feature dtype-struct only.

pub fn meta(self) -> MetaNameSpace

Available on crate feature meta only.
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impl Expr

pub fn nodes<'a>(&'a self, container: &mut UnitVec<&'a Expr>)

pub fn nodes_owned(self, container: &mut UnitVec<Expr>)

pub fn map_expr<F>(self, f: F) -> Expr
where F: FnMut(Expr) -> Expr,

pub fn try_map_expr<F>(self, f: F) -> Result<Expr, PolarsError>
where F: FnMut(Expr) -> Result<Expr, PolarsError>,

Trait Implementations§

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impl Add for Expr

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type Output = Expr

The resulting type after applying the + operator.
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fn add(self, rhs: Expr) -> <Expr as Add>::Output

Performs the + operation. Read more
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impl AsRef<Expr> for AggExpr

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fn as_ref(&self) -> &Expr

Converts this type into a shared reference of the (usually inferred) input type.
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impl Clone for Expr

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fn clone(&self) -> Expr

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for Expr

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter. Read more
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impl Default for Expr

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fn default() -> Expr

Returns the “default value” for a type. Read more
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impl<'de> Deserialize<'de> for Expr

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fn deserialize<__D>( __deserializer: __D ) -> Result<Expr, <__D as Deserializer<'de>>::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl Display for Expr

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter. Read more
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impl Div for Expr

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type Output = Expr

The resulting type after applying the / operator.
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fn div(self, rhs: Expr) -> <Expr as Div>::Output

Performs the / operation. Read more
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impl ExprEvalExtension for Expr

Available on crate features cumulative_eval or list_eval only.
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fn cumulative_eval(self, expr: Expr, min_periods: usize, parallel: bool) -> Expr

Run an expression over a sliding window that increases 1 slot every iteration. Read more
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impl From<&str> for Expr

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fn from(s: &str) -> Expr

Converts to this type from the input type.
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impl From<AggExpr> for Expr

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fn from(agg: AggExpr) -> Expr

Converts to this type from the input type.
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impl From<bool> for Expr

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fn from(val: bool) -> Expr

Converts to this type from the input type.
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impl From<f32> for Expr

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fn from(val: f32) -> Expr

Converts to this type from the input type.
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impl From<f64> for Expr

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fn from(val: f64) -> Expr

Converts to this type from the input type.
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impl From<i16> for Expr

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fn from(val: i16) -> Expr

Converts to this type from the input type.
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impl From<i32> for Expr

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fn from(val: i32) -> Expr

Converts to this type from the input type.
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impl From<i64> for Expr

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fn from(val: i64) -> Expr

Converts to this type from the input type.
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impl From<i8> for Expr

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fn from(val: i8) -> Expr

Converts to this type from the input type.
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impl From<u16> for Expr

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fn from(val: u16) -> Expr

Converts to this type from the input type.
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impl From<u32> for Expr

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fn from(val: u32) -> Expr

Converts to this type from the input type.
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impl From<u64> for Expr

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fn from(val: u64) -> Expr

Converts to this type from the input type.
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impl From<u8> for Expr

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fn from(val: u8) -> Expr

Converts to this type from the input type.
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impl Hash for Expr

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fn hash<H>(&self, state: &mut H)
where H: Hasher,

Feeds this value into the given Hasher. Read more
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fn hash_slice<H>(data: &[Self], state: &mut H)
where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher. Read more
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impl<'a> IntoIterator for &'a Expr

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type Item = &'a Expr

The type of the elements being iterated over.
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type IntoIter = ExprIter<'a>

Which kind of iterator are we turning this into?
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fn into_iter(self) -> <&'a Expr as IntoIterator>::IntoIter

Creates an iterator from a value. Read more
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impl Mul for Expr

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type Output = Expr

The resulting type after applying the * operator.
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fn mul(self, rhs: Expr) -> <Expr as Mul>::Output

Performs the * operation. Read more
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impl Neg for Expr

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type Output = Expr

The resulting type after applying the - operator.
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fn neg(self) -> <Expr as Neg>::Output

Performs the unary - operation. Read more
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impl PartialEq for Expr

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fn eq(&self, other: &Expr) -> bool

This method tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl Rem for Expr

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type Output = Expr

The resulting type after applying the % operator.
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fn rem(self, rhs: Expr) -> <Expr as Rem>::Output

Performs the % operation. Read more
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impl Serialize for Expr

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fn serialize<__S>( &self, __serializer: __S ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more
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impl Sub for Expr

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type Output = Expr

The resulting type after applying the - operator.
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fn sub(self, rhs: Expr) -> <Expr as Sub>::Output

Performs the - operation. Read more
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impl TreeWalker for Expr

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type Arena = ()

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fn apply_children<F>( &self, op: &mut F, arena: &<Expr as TreeWalker>::Arena ) -> Result<VisitRecursion, PolarsError>
where F: FnMut(&Expr, &<Expr as TreeWalker>::Arena) -> Result<VisitRecursion, PolarsError>,

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fn map_children<F>( self, f: &mut F, _arena: &mut <Expr as TreeWalker>::Arena ) -> Result<Expr, PolarsError>
where F: FnMut(Expr, &mut <Expr as TreeWalker>::Arena) -> Result<Expr, PolarsError>,

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fn visit<V>( &self, visitor: &mut V, arena: &Self::Arena ) -> Result<VisitRecursion, PolarsError>
where V: Visitor<Node = Self, Arena = Self::Arena>,

Walks all nodes in depth-first-order.
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fn rewrite<R>( self, rewriter: &mut R, arena: &mut Self::Arena ) -> Result<Self, PolarsError>
where R: RewritingVisitor<Node = Self, Arena = Self::Arena>,

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impl Eq for Expr

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impl StructuralPartialEq for Expr

Auto Trait Implementations§

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impl Freeze for Expr

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impl !RefUnwindSafe for Expr

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impl Send for Expr

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impl Sync for Expr

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impl Unpin for Expr

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impl !UnwindSafe for Expr

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more
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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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impl<T> DynClone for T
where T: Clone,

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fn __clone_box(&self, _: Private) -> *mut ()

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impl<Q, K> Equivalent<K> for Q
where Q: Eq + ?Sized, K: Borrow<Q> + ?Sized,

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fn equivalent(&self, key: &K) -> bool

Checks if this value is equivalent to the given key. Read more
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impl<Q, K> Equivalent<K> for Q
where Q: Eq + ?Sized, K: Borrow<Q> + ?Sized,

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fn equivalent(&self, key: &K) -> bool

Compare self to key and return true if they are equal.
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into<U> for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> Pointable for T

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const ALIGN: usize = _

The alignment of pointer.
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type Init = T

The type for initializers.
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unsafe fn init(init: <T as Pointable>::Init) -> usize

Initializes a with the given initializer. Read more
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unsafe fn deref<'a>(ptr: usize) -> &'a T

Dereferences the given pointer. Read more
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unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

Mutably dereferences the given pointer. Read more
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unsafe fn drop(ptr: usize)

Drops the object pointed to by the given pointer. Read more
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T> ToString for T
where T: Display + ?Sized,

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default fn to_string(&self) -> String

Converts the given value to a String. Read more
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<V, T> VZip<V> for T
where V: MultiLane<T>,

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fn vzip(self) -> V

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impl<T> DeserializeOwned for T
where T: for<'de> Deserialize<'de>,

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impl<T, Rhs, Output> NumOps<Rhs, Output> for T
where T: Sub<Rhs, Output = Output> + Mul<Rhs, Output = Output> + Div<Rhs, Output = Output> + Add<Rhs, Output = Output> + Rem<Rhs, Output = Output>,

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impl<T> Ungil for T
where T: Send,