Create an ascending or descending array Returns evenly spaced values within the half-open interval ``[start, stop)`` as a one-dimensi

Construct a Dask DataFrame from a Pandas DataFrame This splits an in-memory Pandas dataframe into several parts and constructs a dask.da

Create an array of ones Returns a new array having a specified shape and filled with ones.

Reshape array to new shape Refer to :func:`dask.array.reshape` for full documentation. See Also -------- dask.array.

Create a new collection from an expr

Set the DataFrame index (row labels) using an existing column. If ``sort=False``, this function operates exactly like ``pandas.set_index``

Read Parquet files into a DataFrame collection Parameters ---------- path : str or list Source path(s). *

Wraps a function or object to produce a ``Delayed``. ``Delayed`` objects act as proxies for the object they wrap, but all operations on them

Joins collection with another collection. Other collection must be one of the following: 1. An iterable. We recommend tuples over

Mapping function from task -> consistent name. Parameters ---------- args : object Python objects that summarize the task. pu

Known inconsistencies: ``expand=True`` with unknown ``n`` will raise a ``NotImplementedError``.

Repartition a collection Exactly one of `divisions`, `npartitions` or `partition_size` should be specified. A ``ValueError`` will be

Make a copy of the dataframe This is strictly a shallow copy of the underlying computational graph. It does not affect the underlying

Construct a HighLevelGraph from a new layer and a set of collections This constructs a HighLevelGraph in the common case where we have a sing

Create an array of zeros Returns a new array having a specified shape and filled with zeros.

Return a dask.array of the values of this dataframe Warning: This creates a dask.array without precise shape information. Operations

Merge the DataFrame with another DataFrame This will merge the two datasets, either on the indices, a certain column in each dataset

Apply a Python function to each partition Parameters ---------- func : function Function applied to each partitio

Wrap numpy random function to produce dask.array random function extra_chunks should be a chunks tuple to append to the end of chunks

Sort the dataset by a single column. Sorting a parallel dataset requires expensive shuffles and is generally not recommended. See ``s

Read CSV files into a DataFrame collection Parameters ---------- urlpath : str or list Source path(s). **

Copy of the array, cast to a specified type. Parameters ---------- dtype : str or dtype Typecode or data-type to

Looks like a Pandas Series

Return the sum of the array elements over the given axis. Refer to :func:`dask.array.sum` for full documentation. See Also

Reset the index to the default index. Note that unlike in ``pandas``, the reset index for a Dask DataFrame will not be monotonically

extra docstring

Function to create and return a unique temporary directory. Parameters ---------- dir : str If ``dir`` is not None, the dire

BlockwiseDep ``__getitem__`` Wrapper

Get the name of a function.

Function to create and return a unique temporary file with the given extension, if provided. Parameters ---------- extension : str

Returns ``True`` if ``x`` is a dask collection. Parameters ---------- x : Any Object to test. Returns ------- result

Normalize an array to appropriate meta object Parameters ---------- x: array-like, callable Either an object that looks sufficien

Copy array. This is a no-op for dask.arrays, which are immutable

Copy of the array, cast to a specified type. Parameters ---------- dtype : str or dtype Typecode or data-type to

Dumps a number of textfiles to disk Parameters ---------- d : dict a mapping from filename to text like {'a.csv': '1,1\n2,2'}

>>> list(flatten([1])) [1] >>> list(flatten([[1, 2], [1, 2]])) [1, 2, 1, 2] >>> list(flatten([[[1], [2]], [[1], [2]]])) [1

This method creates meta-data based on the type of ``x``, and ``parent_meta`` if supplied. Parameters ---------- x : Object of a

Looks like a Pandas DataFrame

Apply an elementwise ufunc-like function blockwise across arguments. Like numpy ufuncs, broadcasting rules are respected. Parameters ---

Returns True if all elements evaluate to True. Refer to :func:`dask.array.all` for full documentation. See Also --------

Dot product of self and other. Refer to :func:`dask.array.tensordot` for full documentation. See Also -------- dask.

Add a rule to the RuleSet. Parameters ---------- rule : RewriteRule

Config setting to convert objects to pyarrow strings

Return Series of unique values in the object. Includes NA values. Returns ------- uniques : Series

Apply a generalized ufunc or similar python function to arrays. ``signature`` determines if the function consumes or produces core dimen

Convert the input to a dask array. Parameters ---------- a : array-like Input data, in any form that can be converted to a dask a

Apply an elementwise ufunc-like function blockwise across arguments. Like numpy ufuncs, broadcasting rules are respected. Parameters ---

Normalize chunks to tuple of tuples This takes in a variety of input types and information and produces a full tuple-of-tuples result for chu

Deterministic token >>> tokenize([1, 2, '3']) # doctest: +SKIP '06961e8de572e73c2e74b51348177918' >>> tokenize('Hello') == tokenize('He

Concatenate DataFrames along rows. - When axis=0 (default), concatenate DataFrames row-wise: - If all divisions are known and ordered, con

Alter Series index labels or name Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be lef