Module polars::prelude [−][src]
Modules
| datatypes | Data types supported by Polars. |
Structs
| AlignedVec | A |
| 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. |
| BooleanChunkedBuilder | |
| BooleanType | |
| CategoricalType | |
| ChunkedArray | ChunkedArray |
| CsvExec | |
| CsvReader | Create a new DataFrame by reading a csv file. |
| CsvWriter | Write a DataFrame to csv. |
| DataFrame | |
| DataFrameExec | Producer of an in memory DataFrame |
| Date32Type | |
| Date64Type | |
| DefaultPlanner | |
| DurationMicrosecondType | |
| DurationMillisecondType | |
| DurationNanosecondType | |
| DurationSecondType | |
| Field | |
| FilterExec | |
| Float32Type | |
| Float64Type | |
| GroupByExec | Take an input Executor and a multiple expressions |
| Int8Type | |
| Int16Type | |
| Int32Type | |
| Int64Type | |
| IntervalDayTimeType | |
| IntervalYearMonthType | |
| IpcReader | Read Arrows IPC format into a DataFrame |
| IpcWriter | Write a DataFrame to Arrow’s IPC format |
| JoinOptions | |
| JsonReader | |
| LazyCsvReader | |
| LazyFrame | Lazy abstraction over an eager |
| LazyGroupBy | Utility struct for lazy groupby operation. |
| ListBooleanChunkedBuilder | |
| ListPrimitiveChunkedBuilder | |
| ListType | |
| ListUtf8ChunkedBuilder | |
| LogicalPlanBuilder | |
| NoEq | Wrapper type that indicates that the inner type is not equal to anything |
| NoNull | |
| NoNull | Just a wrapper structure. Useful for certain impl specializations
This is for instance use to implement
|
| Node | |
| Null | The literal Null |
| NumTakeRandomChunked | |
| NumTakeRandomCont | |
| ObjectType | |
| OptState | State of the allowed optimizations |
| ParquetReader | Read Apache parquet format into a DataFrame. |
| ParquetWriter | Write a DataFrame to parquet format |
| PhysicalIoHelper | Wrapper struct that allow us to use a PhysicalExpr in polars-io. |
| PrimitiveChunkedBuilder | |
| ReaderBuilder | JSON file reader builder |
| Schema | |
| Series | Series |
| 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 painful because the lack of Generic Associated Type implies that you would require complex lifetime propagation when returning such a cursor. |
| StandardExec | Take an input Executor (creates the input DataFrame) and a multiple PhysicalExpressions (create the output Series) |
| Time32MillisecondType | |
| Time32SecondType | |
| Time64MicrosecondType | |
| Time64NanosecondType | |
| TimestampMicrosecondType | |
| TimestampMillisecondType | |
| TimestampNanosecondType | |
| TimestampSecondType | |
| TypeCoercionRule | |
| UInt8Type | |
| UInt16Type | |
| UInt32Type | |
| UInt64Type | |
| Utf8ChunkedBuilder | |
| Utf8Type | |
| When | |
| WhenThen | |
| WriterBuilder | A CSV writer builder |
Enums
| AggExpr | |
| AnyValue | |
| ArrowDataType | The set of datatypes that are supported by this implementation of Apache Arrow. |
| CsvEncoding | |
| DataType | |
| Expr | Queries consists of multiple expressions. |
| FillNoneStrategy | |
| InitFold | |
| IntervalUnit | YEAR_MONTH or DAY_TIME interval in SQL style. |
| JoinType | |
| LiteralValue | |
| LogicalPlan | |
| Operator | |
| PolarsError | |
| TakeIdx | |
| TimeUnit | An absolute length of time in seconds, milliseconds, microseconds or nanoseconds. |
Traits
| ArgAgg | Argmin/ Argmax |
| ArrowNumericType | |
| ArrowPrimitiveType | Trait bridging the dynamic-typed nature of Arrow (via |
| AsDuration | |
| AsNaiveDate | |
| AsNaiveDateTime | |
| AsNaiveTime | |
| AsTakeIndex | |
| BinaryUdfOutputField | |
| ChunkAgg | Aggregation operations |
| ChunkAggSeries | Aggregations that return Series of unit length. Those can be used in broadcasting 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 |
| ChunkCompare | Compare Series
and ChunkedArray’s and get a |
| ChunkCumAgg | |
| ChunkExpandAtIndex | Create a new ChunkedArray filled with values at that index. |
| ChunkExplode | Explode/ flatten a |
| 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 | |
| ChunkPeaks | Find local minima/ maxima |
| ChunkReverse | Reverse a ChunkedArray |
| ChunkSet | Create a |
| ChunkShift | |
| ChunkShiftFill | Shift the values of a ChunkedArray by a number of periods. |
| ChunkSort | Sort operations on |
| ChunkTake | Fast access by index. |
| ChunkTakeEvery | Traverse and collect every nth element |
| ChunkUnique | Get unique values in a |
| ChunkVar | Variance and standard deviation aggregation. |
| ChunkWindow | Rolling window functions |
| ChunkWindowCustom | Custom rolling window functions |
| ChunkZip | Combine 2 ChunkedArrays based on some predicate. |
| ChunkedBuilder | |
| DataFrameUdf | |
| 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 |
| IntoSeries | |
| IntoTakeRandom | Create a type that implements a faster |
| IsIn | Check if element is member of list array |
| LhsNumOps | |
| ListBuilderTrait | |
| Literal | |
| NamedFrom | |
| NewChunkedArray | |
| NumComp | |
| NumOpsDispatch | |
| Optimize | |
| PhysicalAggregation | |
| PhysicalExpr | Take a DataFrame and evaluate the expressions. Implement this for Column, lt, eq, etc |
| PhysicalPlanner | A type that implements this transforms a LogicalPlan to a physical plan. |
| PolarsDataType | |
| PolarsFloatType | |
| PolarsIntegerType | |
| PolarsIterator | A |
| PolarsNumericType | |
| PolarsPrimitiveType | |
| PolarsSingleType | Any type that is not nested |
| Pow | |
| Range | |
| SerReader | |
| SerWriter | |
| SeriesBinaryUdf | |
| SeriesTrait | |
| SeriesUdf | |
| TakeRandom | Random access |
| TakeRandomUtf8 | |
| ToDummies | |
| VarAggSeries | |
| 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. |
| except | Exclude a column from selection. |
| fold_exprs | Accumulate over multiple columns horizontally / row wise. |
| is_not_null | IsNotNull expression. |
| is_null | IsNull expression |
| lit | Create a Literal Expression from |
| map_binary | Apply a closure on the two columns that are evaluated from |
| 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 | |
| naive_datetime_to_date32 | |
| naive_datetime_to_date64 | |
| 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. |
| range | Create a range literal. |
| 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 |