Enum Expr

pub enum Expr {
    Alias(Arc<Expr>, PlSmallStr),
    Column(PlSmallStr),
    Columns(Arc<[PlSmallStr]>),
    DtypeColumn(Vec<DataType>),
    IndexColumn(Arc<[i64]>),
    Literal(LiteralValue),
    BinaryExpr {
        left: Arc<Expr>,
        op: Operator,
        right: Arc<Expr>,
    },
    Cast {
        expr: Arc<Expr>,
        dtype: DataType,
        options: CastOptions,
    },
    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>,
        order_by: Option<(Arc<Expr>, SortOptions)>,
        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>,
    },
    Field(Arc<[PlSmallStr]>),
    AnonymousFunction {
        input: Vec<Expr>,
        function: LazySerde<SpecialEq<Arc<dyn ColumnsUdf>>>,
        output_type: SpecialEq<Arc<dyn FunctionOutputField>>,
        options: FunctionOptions,
    },
    SubPlan(SpecialEq<Arc<DslPlan>>, Vec<String>),
    Selector(Selector),
}

Available on crate feature lazy only.

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

Alias(Arc<Expr>, PlSmallStr)

Column(PlSmallStr)

Columns(Arc<[PlSmallStr]>)

DtypeColumn(Vec<DataType>)

IndexColumn(Arc<[i64]>)

Literal(LiteralValue)

BinaryExpr

Fields

left: Arc<Expr>

op: Operator

right: Arc<Expr>

Cast

Fields

expr: Arc<Expr>

dtype: DataType

options: CastOptions

Sort

Fields

expr: Arc<Expr>

options: SortOptions

Gather

Fields

expr: Arc<Expr>

idx: Arc<Expr>

returns_scalar: bool

SortBy

Fields

expr: Arc<Expr>

by: Vec<Expr>

sort_options: SortMultipleOptions

Agg(AggExpr)

Ternary

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

Fields

predicate: Arc<Expr>

truthy: Arc<Expr>

falsy: Arc<Expr>

Function

Fields

input: Vec<Expr>

function arguments

function: FunctionExpr

function to apply

options: FunctionOptions

Explode(Arc<Expr>)

Filter

Fields

input: Arc<Expr>

by: Arc<Expr>

Window

Polars flavored window functions.

Fields

function: Arc<Expr>

Also has the input. i.e. avg(“foo”)

partition_by: Vec<Expr>

order_by: Option<(Arc<Expr>, SortOptions)>

options: WindowType

Wildcard

Slice

Fields

input: Arc<Expr>

offset: Arc<Expr>

length is not yet known so we accept negative offsets

length: Arc<Expr>

Exclude(Arc<Expr>, Vec<Excluded>)

Can be used in a select statement to exclude a column from selection TODO: See if we can replace Vec<Excluded> with Arc<Excluded>

KeepName(Arc<Expr>)

Set root name as Alias

Len

Nth(i64)

Take the nth column in the DataFrame

RenameAlias

Fields

function: SpecialEq<Arc<dyn RenameAliasFn>>

expr: Arc<Expr>

Field(Arc<[PlSmallStr]>)

AnonymousFunction

Fields

input: Vec<Expr>

function arguments

function: LazySerde<SpecialEq<Arc<dyn ColumnsUdf>>>

function to apply

output_type: SpecialEq<Arc<dyn FunctionOutputField>>

output dtype of the function

options: FunctionOptions

SubPlan(SpecialEq<Arc<DslPlan>>, Vec<String>)

Selector(Selector)

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

Implementations

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

impl Expr

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

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

pub fn extract_usize(&self) -> Result<usize, PolarsError>

Extract a constant usize from an expression.

pub fn map_unary(self, function: impl Into<FunctionExpr>) -> Expr

pub fn map_binary(self, function: impl Into<FunctionExpr>, rhs: Expr) -> Expr

pub fn map_ternary( self, function: impl Into<FunctionExpr>, arg1: Expr, arg2: Expr, ) -> Expr

pub fn try_map_n_ary( self, function: impl Into<FunctionExpr>, exprs: impl IntoIterator<Item = Result<Expr, PolarsError>>, ) -> Result<Expr, PolarsError>

pub fn map_n_ary( self, function: impl Into<FunctionExpr>, exprs: impl IntoIterator<Item = Expr>, ) -> Expr

pub fn n_ary(function: impl Into<FunctionExpr>, input: Vec<Expr>) -> Expr

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

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.

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<S>(self, name: S) -> Expr

where S: Into<PlSmallStr>,

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, method: QuantileMethod) -> 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 strict_cast(self, dtype: DataType) -> Expr

Cast expression to another data type. Throws an error if conversion had overflows. Returns an Error if cast is invalid on rows after predicates are pushed down.

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

Cast expression to another data type.

pub fn cast_with_options( self, dtype: DataType, cast_options: CastOptions, ) -> 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 reverse(self) -> Expr

Reverse column

pub fn map<F>( self, function: F, output_type: SpecialEq<Arc<dyn FunctionOutputField>>, ) -> Expr

where F: Fn(Column) -> Result<Option<Column>, 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 [Column]) -> Result<Option<Column>, 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(Column) -> Result<Option<Column>, 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(Column) -> Result<Option<Column>, 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(Column) -> Result<Option<Column>, 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 [Column]) -> Result<Option<Column>, 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 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

Cumulatively count values from 0 to len.

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

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

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

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

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

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

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

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 round(self, decimals: u32) -> Expr

Round underlying floating point array to given decimal numbers.

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

Round to a number of significant figures.

pub fn floor(self) -> Expr

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

pub fn pi() -> Expr

Constant Pi

pub fn ceil(self) -> Expr

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

Clip underlying values to a set boundary.

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

Clip underlying values to a set boundary.

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

Clip underlying values to a set boundary.

pub fn abs(self) -> Expr

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, order_by: Option<(E, SortOptions)>, options: WindowMapping, ) -> Expr

where E: AsRef<[IE]>, IE: Into<Expr> + Clone,

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

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_between<E>(self, lower: E, upper: E, closed: ClosedInterval) -> Expr

where E: Into<Expr>,

pub fn approx_n_unique(self) -> Expr

Get the approximate count of unique values.

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

where E: Into<Expr>,

Bitwise “and” operation.

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

where E: Into<Expr>,

Bitwise “xor” operation.

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

where E: Into<Expr>,

Bitwise “or” operation.

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

where E: Into<Expr>,

Logical “or” operation.

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

where E: Into<Expr>,

Logical “and” 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, nulls_equal: bool) -> Expr

where E: Into<Expr>,

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>,

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

Get a mask of the first unique value.

pub fn is_last_distinct(self) -> Expr

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

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

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

Interpolate intermediate values. Nulls at the beginning and end of the series remain null.

pub fn interpolate_by(self, by: Expr) -> Expr

Interpolate intermediate values. Nulls at the beginning and end of the series remain null. The by column provides the x-coordinates for interpolation and must not contain nulls.

pub fn rolling_min_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling minimum based on another column.

pub fn rolling_max_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling maximum based on another column.

pub fn rolling_mean_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling mean based on another column.

pub fn rolling_sum_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling sum based on another column.

pub fn rolling_quantile_by( self, by: Expr, method: QuantileMethod, quantile: f64, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling quantile based on another column.

pub fn rolling_var_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling variance based on another column.

pub fn rolling_std_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling std-dev based on another column.

pub fn rolling_median_by( self, by: Expr, options: RollingOptionsDynamicWindow, ) -> Expr

Apply a rolling median based on another column.

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

Apply a rolling minimum.

See: [RollingAgg::rolling_min]

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

Apply a rolling maximum.

See: [RollingAgg::rolling_max]

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

Apply a rolling mean.

See: [RollingAgg::rolling_mean]

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

Apply a rolling sum.

See: [RollingAgg::rolling_sum]

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

Apply a rolling median.

See: [RollingAgg::rolling_median]

pub fn rolling_quantile( self, method: QuantileMethod, quantile: f64, options: RollingOptionsFixedWindow, ) -> Expr

Apply a rolling quantile.

See: [RollingAgg::rolling_quantile]

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

Apply a rolling variance.

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

Apply a rolling std-dev.

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

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,

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

Assign ranks to data, dealing with ties appropriately.

pub fn replace<E>(self, old: E, new: E) -> Expr

where E: Into<Expr>,

Replace the given values with other values.

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

where E: Into<Expr>,

Replace the given values with other values.

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

Calculate the n-th discrete difference between values.

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 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 false 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, name: &str, normalize: bool, ) -> Expr

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). The name of the struct field with the counts is given by the parameter name.

pub fn unique_counts(self) -> Expr

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 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 to_physical(self) -> Expr

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

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

pub fn str(self) -> StringNameSpace

Get the [string::StringNameSpace]

pub fn binary(self) -> BinaryNameSpace

Get the binary::BinaryNameSpace

pub fn dt(self) -> DateLikeNameSpace

Get the dt::DateLikeNameSpace

pub fn list(self) -> ListNameSpace

Get the list::ListNameSpace

pub fn name(self) -> ExprNameNameSpace

Get the name::ExprNameNameSpace

pub fn arr(self) -> ArrayNameSpace

Get the array::ArrayNameSpace.

pub fn cat(self) -> CategoricalNameSpace

Get the CategoricalNameSpace.

pub fn struct_(self) -> StructNameSpace

Get the struct_::StructNameSpace.

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

impl Add for Expr

type Output = Expr

The resulting type after applying the + operator.

fn add(self, rhs: Expr) -> <Expr as Add>::Output

Performs the + operation.

impl AsRef<Expr> for AggExpr

fn as_ref(&self) -> &Expr

Converts this type into a shared reference of the (usually inferred) input type.

impl Clone for Expr

fn clone(&self) -> Expr

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Expr

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

Formats the value using the given formatter.

impl Default for Expr

fn default() -> Expr

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Expr

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Expr

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

Formats the value using the given formatter.

impl Div for Expr

type Output = Expr

The resulting type after applying the / operator.

fn div(self, rhs: Expr) -> <Expr as Div>::Output

Performs the / operation.

impl ExprEvalExtension for Expr

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.

impl From<&str> for Expr

fn from(s: &str) -> Expr

Converts to this type from the input type.

impl From<AggExpr> for Expr

fn from(agg: AggExpr) -> Expr

Converts to this type from the input type.

impl From<Expr> for Selector

fn from(value: Expr) -> Selector

Converts to this type from the input type.

impl From<bool> for Expr

fn from(val: bool) -> Expr

Converts to this type from the input type.

impl From<f32> for Expr

fn from(val: f32) -> Expr

Converts to this type from the input type.

impl From<f64> for Expr

fn from(val: f64) -> Expr

Converts to this type from the input type.

impl From<i16> for Expr

fn from(val: i16) -> Expr

Converts to this type from the input type.

impl From<i32> for Expr

fn from(val: i32) -> Expr

Converts to this type from the input type.

impl From<i64> for Expr

fn from(val: i64) -> Expr

Converts to this type from the input type.

impl From<i8> for Expr

fn from(val: i8) -> Expr

Converts to this type from the input type.

impl From<u16> for Expr

fn from(val: u16) -> Expr

Converts to this type from the input type.

impl From<u32> for Expr

fn from(val: u32) -> Expr

Converts to this type from the input type.

impl From<u64> for Expr

fn from(val: u64) -> Expr

Converts to this type from the input type.

impl From<u8> for Expr

fn from(val: u8) -> Expr

Converts to this type from the input type.

impl Hash for Expr

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

where H: Hasher,

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl<'a> IntoIterator for &'a Expr

type Item = &'a Expr

The type of the elements being iterated over.

type IntoIter = ExprIter<'a>

Which kind of iterator are we turning this into?

fn into_iter(self) -> <&'a Expr as IntoIterator>::IntoIter

Creates an iterator from a value.

impl Mul for Expr

type Output = Expr

The resulting type after applying the * operator.

fn mul(self, rhs: Expr) -> <Expr as Mul>::Output

Performs the * operation.

impl Neg for Expr

type Output = Expr

The resulting type after applying the - operator.

fn neg(self) -> <Expr as Neg>::Output

Performs the unary - operation.

impl PartialEq for Expr

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

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Rem for Expr

type Output = Expr

The resulting type after applying the % operator.

fn rem(self, rhs: Expr) -> <Expr as Rem>::Output

Performs the % operation.

impl Serialize for Expr

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.

impl Sub for Expr

type Output = Expr

The resulting type after applying the - operator.

fn sub(self, rhs: Expr) -> <Expr as Sub>::Output

Performs the - operation.

impl TreeWalker for Expr

type Arena = ()

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>,

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>,

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.

fn rewrite<R>( self, rewriter: &mut R, arena: &mut Self::Arena, ) -> Result<Self, PolarsError>

where R: RewritingVisitor<Node = Self, Arena = Self::Arena>,

impl Eq for Expr

impl StructuralPartialEq for Expr