Perform the tree reduction step of a reduction. Lower level, users should use ``reduction`` or ``arg_reduction`` directly.

A wrapper around pandas' union_categoricals that handles some dtype issues. union_categoricals requires that the dtype of each array's categ

Validates logic of `axes`/`axis`/`keepdims` arguments and normalize them. Refer to [1]_ for details Arguments --------- axes: Li

Point wise indexing with broadcasting. >>> x = np.arange(56).reshape((7, 8)) >>> x array([[ 0, 1, 2, 3, 4, 5, 6, 7], [

Point wise indexing with only NumPy Arrays.

>>> locations = [0], [2, 1] >>> values = [np.array([[1, 2, 3]]), ... np.array([[10, 20, 30], [40, 50, 60]])] >>> _vindex_

Add method operators to Series or DataFrame like DataFrame.add. _wrap_expr_method_operator("add", DataFrame)

Write dask array to existing zarr store. Parameters ---------- url: zarr.Array The zarr array. arr: The dask array to

Write table to a partitioned dataset with pyarrow. Logic copied from pyarrow.parquet. (arrow/python/pyarrow/parquet.py::write_to_dataset)

Returns a new chunking aligned with the coarsening multiple. Any excess is at the end of the array. Examples -------- >>> aligne

Outputs statistics about every node in the expression. analyze optimizes the expression and triggers a computation. It records statistics

This is a blocked variant of :func:`numpy.apply_along_axis` implemented via :func:`dask.array.map_blocks` Notes ----- If either

Apply a function, and enforce the output to match meta Ensures the output has the same columns, even if empty.

Apply filters onto parts/statistics pairs Parameters ---------- parts: list Tokens corresponding to row groups to read in the fut

Return an approximation of a single files statistics. This is determined by sampling a few files and averaging their statistics. Fie

Extract the indices of the k largest elements from a on the given axis, and return them sorted from largest to smallest. If k is negative, extract

Chunk and combine function of argtopk Extract the indices of the k largest elements from a on the given axis. If k is negative, extract the i

The indices of the top k elements of an array. Refer to :func:`dask.array.argtopk` for full documentation. See Also --------

Convert the input to a dask array. Subclasses of ``np.ndarray`` will be passed through as chunks unchanged. Parameters ---------- a

left and right are equal, treating index and array as equivalent

Check that the dask metadata matches the result. If `numeric_equal`, integer and floating dtypes compare equal. This is useful due to the imp

Determine automatic chunks This takes in a chunks value that contains ``"auto"`` values in certain dimensions and replaces those values with

Apply a function elementwise across one or more bags. Note that all ``Bag`` arguments must be partitioned identically. Parameters ------

The positions of index elements in the range values loc0 and loc1. The index is the input assignment index that is defined in the nam

Number of True index elements between positions loc0 and loc1. The index is the input assignment index that is defined in the namespa

Yields a flat iterable of booleans to mark the last element of the nested input ``block_lists`` in a flattened output. >>> list(block_ma

Create a Blockwise symbolic mutable mapping Applies a function, ``func``, across blocks from many different input collections. We arrange th

Add boundary conditions to an array before overlapping See Also -------- periodic constant

Check if the provided value has been renamed or removed Parameters ---------- key : str The configuration key to check deprec