Struct spark_connect_rs::group::GroupedData

pub struct GroupedData { /* private fields */ }

Implementations

impl GroupedData

pub fn new( df: DataFrame, group_type: GroupType, grouping_cols: Vec<Expression>, pivot_col: Option<Expression>, pivot_vals: Option<Vec<Literal>> ) -> GroupedData

pub fn agg<T>(self, exprs: T) -> DataFrame

where T: ToVecExpr,

Compute aggregates and returns the result as a DataFrame

pub fn avg<T>(self, cols: T) -> DataFrame

where T: ToVecExpr,

Computes average values for each numeric columns for each group.

pub fn min<T>(self, cols: T) -> DataFrame

where T: ToVecExpr,

Computes the min value for each numeric column for each group.

pub fn max<T>(self, cols: T) -> DataFrame

where T: ToVecExpr,

Computes the max value for each numeric columns for each group.

pub fn sum<T>(self, cols: T) -> DataFrame

where T: ToVecExpr,

Computes the sum for each numeric columns for each group.

pub fn count(self) -> DataFrame

Counts the number of records for each group.

pub fn pivot(self, col: &str, values: Option<Vec<&str>>) -> GroupedData

Pivots a column of the current DataFrame and perform the specified aggregation

Trait Implementations

impl Clone for GroupedData

fn clone(&self) -> GroupedData

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for GroupedData

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

Formats the value using the given formatter.