Struct DataFrame 

pub struct DataFrame(/* private fields */);

Root-owned DataFrame; delegates to the Polars backend.

Implementations

impl DataFrame

pub fn from_polars(df: PlDataFrame) -> Self

Create from a Polars DataFrame (via backend).

pub fn from_polars_with_options(df: PlDataFrame, case_sensitive: bool) -> Self

Create from a Polars DataFrame with options.

pub fn from_lazy(lf: LazyFrame) -> Self

Create from a LazyFrame (via backend).

pub fn from_lazy_with_options(lf: LazyFrame, case_sensitive: bool) -> Self

Create from a LazyFrame with options.

pub fn empty() -> Self

Create an empty DataFrame.

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

Return a DataFrame with the given alias.

pub fn filter_expr_ir( &self, condition: &ExprIr, ) -> Result<DataFrame, EngineError>

Filter rows using an engine-agnostic expression (ExprIr).

pub fn select_expr_ir(&self, exprs: &[ExprIr]) -> Result<DataFrame, EngineError>

Select columns/expressions using ExprIr.

pub fn with_column_expr_ir( &self, name: &str, expr: &ExprIr, ) -> Result<DataFrame, EngineError>

Add or replace a column using ExprIr.

pub fn collect_rows(&self) -> Result<CollectedRows, EngineError>

Collect as engine-agnostic rows (column name -> JSON value per row).

pub fn resolve_expr_column_names(&self, expr: Expr) -> Result<Expr, PolarsError>

pub fn coerce_string_numeric_comparisons( &self, expr: Expr, ) -> Result<Expr, PolarsError>

pub fn resolve_column_name(&self, name: &str) -> Result<String, PolarsError>

pub fn schema(&self) -> Result<StructType, PolarsError>

pub fn schema_engine(&self) -> Result<StructType, EngineError>

pub fn get_column_dtype(&self, name: &str) -> Option<PlDataType>

pub fn get_column_data_type(&self, name: &str) -> Option<DataType>

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

pub fn columns_engine(&self) -> Result<Vec<String>, EngineError>

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

pub fn count_engine(&self) -> Result<usize, EngineError>

pub fn show(&self, n: Option<usize>) -> Result<(), PolarsError>

pub fn collect(&self) -> Result<Arc<PlDataFrame>, PolarsError>

pub fn collect_as_json_rows_engine( &self, ) -> Result<Vec<HashMap<String, JsonValue>>, EngineError>

pub fn collect_as_json_rows( &self, ) -> Result<Vec<HashMap<String, JsonValue>>, PolarsError>

pub fn to_json_rows(&self) -> Result<String, EngineError>

pub fn select_exprs(&self, exprs: Vec<Expr>) -> Result<DataFrame, PolarsError>

pub fn select(&self, cols: Vec<&str>) -> Result<DataFrame, PolarsError>

pub fn select_engine(&self, cols: Vec<&str>) -> Result<DataFrame, EngineError>

pub fn select_items( &self, items: Vec<SelectItem<'_>>, ) -> Result<DataFrame, PolarsError>

pub fn filter(&self, condition: Expr) -> Result<DataFrame, PolarsError>

pub fn filter_engine(&self, condition: Expr) -> Result<DataFrame, EngineError>

pub fn column(&self, name: &str) -> Result<Column, PolarsError>

pub fn with_column( &self, column_name: &str, col: &Column, ) -> Result<DataFrame, PolarsError>

pub fn with_column_engine( &self, column_name: &str, col: &Column, ) -> Result<DataFrame, EngineError>

pub fn with_column_expr( &self, column_name: &str, expr: Expr, ) -> Result<DataFrame, PolarsError>

pub fn group_by( &self, column_names: Vec<&str>, ) -> Result<GroupedData, PolarsError>

pub fn group_by_engine( &self, column_names: Vec<&str>, ) -> Result<GroupedData, EngineError>

pub fn group_by_exprs( &self, exprs: Vec<Expr>, grouping_col_names: Vec<String>, ) -> Result<GroupedData, PolarsError>

pub fn cube( &self, column_names: Vec<&str>, ) -> Result<CubeRollupData, PolarsError>

pub fn rollup( &self, column_names: Vec<&str>, ) -> Result<CubeRollupData, PolarsError>

pub fn agg(&self, aggregations: Vec<Expr>) -> Result<DataFrame, PolarsError>

pub fn join( &self, other: &DataFrame, on: Vec<&str>, how: JoinType, ) -> Result<DataFrame, PolarsError>

pub fn order_by( &self, column_names: Vec<&str>, ascending: Vec<bool>, ) -> Result<DataFrame, PolarsError>

pub fn order_by_exprs( &self, sort_orders: Vec<SortOrder>, ) -> Result<DataFrame, PolarsError>

pub fn union(&self, other: &DataFrame) -> Result<DataFrame, PolarsError>

pub fn union_all(&self, other: &DataFrame) -> Result<DataFrame, PolarsError>

pub fn union_by_name( &self, other: &DataFrame, allow_missing_columns: bool, ) -> Result<DataFrame, PolarsError>

pub fn distinct( &self, subset: Option<Vec<&str>>, ) -> Result<DataFrame, PolarsError>

pub fn drop(&self, columns: Vec<&str>) -> Result<DataFrame, PolarsError>

pub fn dropna( &self, subset: Option<Vec<&str>>, how: &str, thresh: Option<usize>, ) -> Result<DataFrame, PolarsError>

pub fn fillna( &self, value: Expr, subset: Option<Vec<&str>>, ) -> Result<DataFrame, PolarsError>

pub fn limit(&self, n: usize) -> Result<DataFrame, PolarsError>

pub fn limit_engine(&self, n: usize) -> Result<DataFrame, EngineError>

pub fn with_column_renamed( &self, old_name: &str, new_name: &str, ) -> Result<DataFrame, PolarsError>

pub fn replace( &self, column_name: &str, old_value: Expr, new_value: Expr, ) -> Result<DataFrame, PolarsError>

pub fn cross_join(&self, other: &DataFrame) -> Result<DataFrame, PolarsError>

pub fn describe(&self) -> Result<DataFrame, PolarsError>

pub fn cache(&self) -> Result<DataFrame, PolarsError>

pub fn persist(&self) -> Result<DataFrame, PolarsError>

pub fn unpersist(&self) -> Result<DataFrame, PolarsError>

pub fn subtract(&self, other: &DataFrame) -> Result<DataFrame, PolarsError>

pub fn intersect(&self, other: &DataFrame) -> Result<DataFrame, PolarsError>

pub fn sample( &self, with_replacement: bool, fraction: f64, seed: Option<u64>, ) -> Result<DataFrame, PolarsError>

pub fn random_split( &self, weights: &[f64], seed: Option<u64>, ) -> Result<Vec<DataFrame>, PolarsError>

pub fn sample_by( &self, col_name: &str, fractions: &[(Expr, f64)], seed: Option<u64>, ) -> Result<DataFrame, PolarsError>

pub fn first(&self) -> Result<DataFrame, PolarsError>

pub fn head(&self, n: usize) -> Result<DataFrame, PolarsError>

pub fn take(&self, n: usize) -> Result<DataFrame, PolarsError>

pub fn tail(&self, n: usize) -> Result<DataFrame, PolarsError>

pub fn is_empty(&self) -> bool

pub fn to_df(&self, names: Vec<&str>) -> Result<DataFrame, PolarsError>

pub fn stat(&self) -> DataFrameStat<'_>

pub fn corr(&self) -> Result<DataFrame, PolarsError>

pub fn corr_cols(&self, col1: &str, col2: &str) -> Result<f64, PolarsError>

pub fn cov_cols(&self, col1: &str, col2: &str) -> Result<f64, PolarsError>

pub fn summary(&self) -> Result<DataFrame, PolarsError>

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

pub fn explain(&self) -> String

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

pub fn checkpoint(&self) -> Result<DataFrame, PolarsError>

pub fn local_checkpoint(&self) -> Result<DataFrame, PolarsError>

pub fn repartition( &self, num_partitions: usize, ) -> Result<DataFrame, PolarsError>

pub fn repartition_by_range( &self, num_partitions: usize, columns: Vec<&str>, ) -> Result<DataFrame, PolarsError>

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

pub fn sort_within_partitions( &self, cols: &[SortOrder], ) -> Result<DataFrame, PolarsError>

pub fn coalesce(&self, num_partitions: usize) -> Result<DataFrame, PolarsError>

pub fn hint(&self, name: &str, params: &[i32]) -> Result<DataFrame, PolarsError>

pub fn is_local(&self) -> bool

pub fn input_files(&self) -> Vec<String>

pub fn same_semantics(&self, other: &DataFrame) -> bool

pub fn semantic_hash(&self) -> u64

pub fn observe(&self, name: &str, expr: Expr) -> Result<DataFrame, PolarsError>

pub fn with_watermark( &self, event_time: &str, delay_threshold: &str, ) -> Result<DataFrame, PolarsError>

pub fn select_expr(&self, exprs: &[String]) -> Result<DataFrame, PolarsError>

pub fn col_regex(&self, pattern: &str) -> Result<DataFrame, PolarsError>

pub fn with_columns( &self, exprs: &[(String, Column)], ) -> Result<DataFrame, PolarsError>

pub fn with_columns_renamed( &self, renames: &[(String, String)], ) -> Result<DataFrame, PolarsError>

pub fn na(&self) -> DataFrameNa<'_>

pub fn offset(&self, n: usize) -> Result<DataFrame, PolarsError>

pub fn transform<F>(&self, f: F) -> Result<DataFrame, PolarsError>

where F: FnOnce(DataFrame) -> Result<DataFrame, PolarsError>,

pub fn freq_items( &self, columns: &[&str], support: f64, ) -> Result<DataFrame, PolarsError>

pub fn approx_quantile( &self, column: &str, probabilities: &[f64], ) -> Result<DataFrame, PolarsError>

pub fn crosstab(&self, col1: &str, col2: &str) -> Result<DataFrame, PolarsError>

pub fn write(&self) -> DataFrameWriter<'_>

Write this DataFrame to path (returns root-owned writer).

pub fn write_delta( &self, _path: impl AsRef<Path>, _overwrite: bool, ) -> Result<(), PolarsError>

pub fn save_as_delta_table(&self, session: &SparkSession, name: &str)

Register as delta table by name.

Trait Implementations

impl Clone for DataFrame

fn clone(&self) -> DataFrame

Returns a duplicate of the value.

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

Performs copy-assignment from source.