Module polars::prelude[][src]

Modules

datatypes

Data types supported by Polars.

Structs

ALogicalPlanBuilder
AggQuantileExpr
AliasExpr
AlignedVec

A Vec wrapper with a memory alignment equal to Arrow's primitive arrays. Can be useful in creating a new ChunkedArray or Arrow Primitive array without copying.

ApplyExpr
Arc

A thread-safe reference-counting pointer. 'Arc' stands for 'Atomically Reference Counted'.

Arena
ArrowField

Contains the meta-data for a single relative type.

ArrowSchema

Describes the meta-data of an ordered sequence of relative types.

BinaryExpr
BooleanChunkedBuilder
BooleanType
CastExpr
CategoricalType
ChunkedArray

ChunkedArray

ColumnExpr
CsvExec
CsvReader

Create a new DataFrame by reading a csv file.

CsvWriter

Write a DataFrame to csv.

DataFrame
DataFrameExec
Date32Type
Date64Type
DefaultPlanner
DurationMicrosecondType
DurationMillisecondType
DurationNanosecondType
DurationSecondType
Field
FilterExec
Float32Type
Float64Type
GroupByExec

Take an input Executor and a multiple expressions

IPCReader

Read Arrows IPC format into a DataFrame

IPCWriter

Write a DataFrame to Arrow's IPC format

Int8Type
Int16Type
Int32Type
Int64Type
IntervalDayTimeType
IntervalYearMonthType
IsNotNullExpr
IsNullExpr
JoinOptions
JsonReader
LazyCsvReader
LazyFrame

Lazy abstraction over an eager DataFrame. It really is an abstraction over a logical plan. The methods of this struct will incrementally modify a logical plan until output is requested (via collect)

LazyGroupBy

Utility struct for lazy groupby operation.

ListBooleanChunkedBuilder
ListPrimitiveChunkedBuilder
ListType
ListUtf8ChunkedBuilder
LiteralExpr
LogicalPlanBuilder
NoNull
Node
NotExpr
NumTakeRandomChunked
NumTakeRandomCont
ObjectTypeobject
OptState

State of the allowed optimizations

ParquetReader

Read Apache parquet format into a DataFrame.

ParquetWriter

Write a DataFrame to parquet format

PredicatePushDown
PrimitiveChunkedBuilder
ProjectionPushDown
ReaderBuilder

JSON file reader builder

Schema
Series

Series

SliceExpr
SliceableCursor

This is object to use if your file is already in memory. The sliceable cursor is similar to std::io::Cursor, except that it makes it easy to create "cursor slices". To achieve this, it uses Arc instead of shared references. Indeed reference fields are painfull because the lack of Generic Associated Type implies that you would require complex lifetime propagation when returning such a cursor.

SortExpr
StackOptimizer

Optimizer that uses a stack and memory arenas in favor of recursion

StandardExec

Take an input Executor (creates the input DataFrame) and a multiple PhysicalExpressions (create the output Series)

TernaryExpr
Time32MillisecondType
Time32SecondType
Time64MicrosecondType
Time64NanosecondType
TimestampMicrosecondType
TimestampMillisecondType
TimestampNanosecondType
TimestampSecondType
TypeCoercionRule
UInt8Type
UInt16Type
UInt32Type
UInt64Type
Utf8ChunkedBuilder
Utf8Type
When
WhenThen
WindowExpr
WriterBuilder

A CSV writer builder

Enums

AAggExpr
AExpr
ALogicalPlan
AggExpr
AnyValue
ArrowDataType

The set of datatypes that are supported by this implementation of Apache Arrow.

CsvEncoding
DataType
DateUnit

Date is either a 32-bit or 64-bit type representing elapsed time since UNIX epoch (1970-01-01) in days or milliseconds.

Expr

Queries consists of multiple expressions.

FillNoneStrategy
InitFold
IntervalUnit

YEAR_MONTH or DAY_TIME interval in SQL style.

JoinType
LogicalPlan
Operator
PolarsError
ScalarValue
TimeUnit

An absolute length of time in seconds, milliseconds, microseconds or nanoseconds.

Traits

ArrowNumericType
ArrowPrimitiveType

Trait indicating a primitive fixed-width type (bool, ints and floats).

AsDuration
AsNaiveDate
AsNaiveDateTime
AsNaiveTime
AsTakeIndex
BinaryUdfOutputField
ChunkAgg

Aggregation operations

ChunkApply

Fastest way to do elementwise operations on a ChunkedArray

ChunkApplyKernel

Apply kernels on the arrow array chunks in a ChunkedArray.

ChunkBytes
ChunkCast

Cast ChunkedArray<T> to ChunkedArray<N>

ChunkCompare

Compare Series and ChunkedArray's and get a boolean mask that can be used to filter rows.

ChunkCumAgg
ChunkExpandAtIndex

Create a new ChunkedArray filled with values at that index.

ChunkExplode
ChunkFillNone

Replace None values with various strategies

ChunkFillNoneValue

Replace None values with a value

ChunkFilter

Filter values by a boolean mask.

ChunkFull

Fill a ChunkedArray with one value.

ChunkFullNull
ChunkOps
ChunkReverse

Reverse a ChunkedArray

ChunkSet

Create a ChunkedArray with new values by index or by boolean mask. Note that these operations clone data. This is however the only way we can modify at mask or index level as the underlying Arrow arrays are immutable.

ChunkShift
ChunkShiftFill

Shift the values of a ChunkedArray by a number of periods.

ChunkSort

Sort operations on ChunkedArray.

ChunkTake

Fast access by index.

ChunkTakeEvery
ChunkUnique

Get unique values in a ChunkedArray

ChunkVar

Variance and standard deviation aggregation.

ChunkWindow
ChunkWindowCustom
ChunkZip

Combine 2 ChunkedArrays based on some predicate.

ChunkedBuilder
CompToSeries
DataFrameUdf
Downcast
Executor

Executors will evaluate physical expressions and collect them in a DataFrame.

FromNaiveDate
FromNaiveDateTime
FromNaiveTime
IntoLazy
IntoNoNullIterator

Trait for ChunkedArrays that don't have null values. The result is the most efficient implementation Iterator, according to the number of chunks.

IntoSeries
IntoTakeRandom

Create a type that implements a faster TakeRandom.

LhsNumOps
ListBuilderTrait
Literal
NamedFrom
NewChunkedArray
NumComp
NumOpsDispatch
OptimizationRule
Optimize
PhysicalExpr

Take a DataFrame and evaluate the expressions. Implement this for Column, lt, eq, etc

PhysicalPlanner
PolarsDataType
PolarsFloatType
PolarsIntegerType
PolarsIterator

A PolarsIterator is an iterator over a ChunkedArray which contains polars types. A PolarsIterator must implement ExactSizeIterator and DoubleEndedIterator.

PolarsNumericType
PolarsPrimitiveType
PolarsSingleType

Any type that is not nested

Pow
SerReader
SerWriter
SeriesBinaryUdf
SeriesTrait
SeriesUdf
TakeRandom

Random access

TakeRandomUtf8
ToDummies
VecHash

Functions

all_exprs

Evaluate all the expressions with a bitwise and

any_exprs

Evaluate all the expressions with a bitwise or

avg

Find the mean of all the values in this Expression.

binary_expr
cast

Cast expression.

col

Create a Column Expression based on a column name.

count

Count the number of values in this Expression.

fold_exprs

Accumulate over multiple columns horizontally / row wise.

is_not_null

IsNotNull expression.

is_null

IsNull expression

lit

Create a Literal Expression from L

map_binary

Apply a closure on the two columns that are evaluated from Expr a and Expr b.

map_binary_lazy_field

Binary function where the output type is determined at runtime when the schema is known.

max

Find the maximum of all the values in this Expression.

max_exprs

Get the the minimum value per row

mean

Find the mean of all the values in this Expression.

median

Find the median of all the values in this Expression.

min

Find the minimum of all the values in this Expression.

min_exprs

Get the the minimum value per row

naive_date_to_date32
not

Not expression.

parse_naive_date_from_str
parse_naive_datetime_from_str
quantile

Find a specific quantile of all the values in this Expression.

sum

Sum all the values in this Expression.

sum_exprs

Get the the sum of the values per row

ternary_expr
when

Start a when-then-otherwise expression

Type Definitions

AllowedOptimizations

AllowedOptimizations

BooleanChunked
CategoricalChunked
Date32Chunked
Date64Chunked
DurationMillisecondChunked
DurationNanosecondChunked
Float32Chunked
Float64Chunked
Int8Chunked
Int16Chunked
Int32Chunked
Int64Chunked
ListChunked
ObjectChunked
Result
SchemaRef
Time64NanosecondChunked
UInt8Chunked
UInt16Chunked
UInt32Chunked
UInt64Chunked
Utf8Chunked