Format seconds into a human readable form. >>> format_time(10.4) # doctest: +SKIP '10.4s' >>> format_time(1000.4) # doctest: +SKIP

* Convert YAML style key to environment variable style key * * @param {string} str - YAML style key * @return {string} Environment variable style k

Create a Dask DataFrame from a Dask Array. Converts a 2d array into a DataFrame and a 1d array into a Series. Parameters ----------

Return a full array with the same shape and type as a given array. Parameters ---------- a : array_like The shape and data-t

Return a full array with the same shape and type as a given array. Parameters ---------- a : array_like The shape and data-t

Fuse a set of tasks into a single task. The tasks are fused into a single task that will execute the tasks in a subgraph. The interna

Return new dask graph with linear sequence of tasks fused together. If specified, the keys in ``keys`` keyword argument are *not* fused. Supp

Fuse nearby layers if they don't have dependencies Often Blockwise sections of the graph fill out all of the computation except for the

Get current annotations. Returns ------- Dict of all current annotations See Also -------- annotate

Convert categorical variable into dummy/indicator variables. Data must have category dtype to infer result's ``columns``. Parameters

Helper function for finding shapes and chunks of end pads.

Handle out parameters If out is a dask.DataFrame, dask.Series or dask.Scalar then this overwrites the contents of it with the result. The met

Returns True if the task has sub tasks

Blocked variant of :func:`numpy.histogramdd`. Chunking of the input data (``sample``) is only allowed along the 0th (row) axis (the axis corr

Get the first layer from a HighLevelGraph whose name starts with a prefix

Expand docstring by adding disclaimer and extra text

Summarized representation of an Index.

Implements NumPy's ``indices`` for Dask Arrays. Generates a grid of indices covering the dimensions provided. The final array has the s

Perform engine-specific initialization steps for this dataset Parameters ---------- df: dask.dataframe.DataFrame fs:

>>> interleave_none([0, None, 2, None], [1, 3]) (0, 1, 2, 3)

This Series is broadcastable against another dataframe in the sequence

>>> is_integer(6) True >>> is_integer(42.0) True >>> is_integer('abc') False

pandas.isnull for dask arrays

>>> keyname('x', 3, [None, None, 0, 2]) ('x', 3, 0, 2)

.loc for known divisions

Allows callbacks to work with nested schedulers. Callbacks will only be used by the first started scheduler they encounter. This means that o

Compute the lu decomposition of a matrix. Examples -------- >>> p, l, u = da.linalg.lu(x) # doctest: +SKIP Returns ------

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

Iterate over the nested list, applying: * ``f_map`` (T -> U) to items * ``f_reduce`` (Iterable[U] -> U) to mapped items