Module polars::chunked_array::object
source · [−]Modules
Macros
Structs
Represents Arrow’s metadata of a “column”.
ChunkedArray
A contiguous growable collection of Series that have the same length.
Indexes of the groups, the first index is stored separately. this make sorting fast.
Maps a logical type to a a chunked array implementation of the physical type. This saves a lot of compiler bloat and allows us to reuse functionality.
Arguments for [DataFrame::melt] function
Series
This is logical type StructChunked that
dispatches most logic to the fields implementations
Enums
The set of supported logical types in this crate.
The time units defined in Arrow.
One of the three arguments allowed in unchecked_take
Constants
Traits
Argmin/ Argmax
Aggregation operations
Aggregations that return Series of unit length. Those can be used in broadcasting operations.
Fastest way to do elementwise operations on a ChunkedArray
Apply kernels on the arrow array chunks in a ChunkedArray.
Cast ChunkedArray<T> to ChunkedArray<N>
Compare Series
and ChunkedArray’s and get a boolean mask that
can be used to filter rows.
Create a new ChunkedArray filled with values at that index.
Explode/ flatten a
Replace None values with various strategies
Replace None values with a value
Filter values by a boolean mask.
Fill a ChunkedArray with one value.
Find local minima/ maxima
Quantile and median aggregation
Reverse a ChunkedArray
This differs from ChunkWindowCustom and ChunkWindow
by not using a fold aggregator, but reusing a Series wrapper and calling Series aggregators.
This likely is a bit slower than ChunkWindow
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.
Shift the values of a ChunkedArray by a number of periods.
Sort operations on ChunkedArray.
Fast access by index.
Traverse and collect every nth element
Get unique values in a ChunkedArray
Variance and standard deviation aggregation.
Combine 2 ChunkedArrays based on some predicate.
This trait exists to be unify the API of polars Schema and arrows Schema
Create a type that implements a faster TakeRandom.
Mask the first unique values as true
Check if element is member of list array
Mask the last unique values as true
A PolarsIterator is an iterator over a ChunkedArray which contains polars types. A PolarsIterator
must implement ExactSizeIterator and DoubleEndedIterator.
Values need to implement this so that they can be stored into a Series and DataFrame
Trimmed down object safe polars object
Any type that is not nested
Repeat the values n times.
Concat the values into a string array.
Random access
Functions
Type Definitions
Dummy type, we need to instantiate all generic types, so we fill one with a dummy.
Every group is indicated by an array where the
The type used by polars to index data.