# Dask

> Dask
> ====
> 
> |Build Status| |Coverage| |Doc Status| |Discourse| |Version Status| |NumFOCUS|
> 
> Dask is a flexible parallel computing library for analytics.  See
> documentation_ for more information.
> 
> 
> LICENSE
> -------
> 
> New BSD. See `License File <https://github.com/dask/dask/blob/main/LICENSE.txt>`__.
> 
> .. _documentation: https://dask.org
> .. |Build Status| image:: https://github.com/dask/dask/actions/workflows/tests.yml/badge.svg
>    :target: https://github.com/dask/dask/actions/workflows/tests.yml
> .. |Coverage| image:: https://codecov.io/gh/dask/dask/branch/main/graph/badge.svg
>    :target: https://codecov.io/gh/dask/dask/branch/main
>    :alt: Coverage status
> .. |Doc Status| image:: https://readthedocs.org/projects/dask/badge/?version=latest
>    :target: https://dask.org
>    :alt: Documentation Status
> .. |Discourse| image:: https://img.shields.io/discourse/users?logo=discourse&server=https%3A%2F%2Fdask.discourse.group
>    :alt: Discuss Dask-related things and ask for help
>    :target: https://dask.discourse.group
> .. |Version Status| image:: https://img.shields.io/pypi/v/dask.svg
>    :target: https://pypi.python.org/pypi/dask/
> .. |NumFOCUS| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
>    :target: https://www.numfocus.org/


2026

## Pages

- [Dask](index.html.md): *Dask is a Python library for parallel and distributed computing.*  Dask is:
- [How To…](how-to/index.html.md): This section contains snippets and suggestions about how to perform different actions
- [10 Minutes to Dask](10-minutes-to-dask.html.md): This is a short overview of Dask geared towards new users. Additional Dask information can be found in the rest of the Dask documentation.
- [Adaptive deployments](adaptive.html.md): Most Dask deployments are static with a single scheduler and a fixed number of
- [API Reference](api.html.md): Dask APIs generally follow from upstream APIs:
- [API](array-api.html.md): | [`abs`](generated/dask.array.abs.md#dask.array.abs)(x, /[, out, where, casting, order, ...])      ...
- [Assignment](array-assignment.html.md): Dask Array supports most of the NumPy assignment indexing syntax. In
- [Best Practices](array-best-practices.html.md): It is easy to get started with Dask arrays, but using them *well* does require
- [Chunks](array-chunks.html.md): Dask arrays are composed of many NumPy (or NumPy-like) arrays. How these arrays
- [Create Dask Arrays](array-creation.html.md): You can load or store Dask arrays from a variety of common sources like HDF5,
- [Internal Design](array-design.html.md): ![12 rectangular blocks arranged as a 4-row, 3-column layout. Each block includes 'x' and its locati...
- [Generalized UFuncs](array-gufunc.html.md): [NumPy](https://www.numpy.org) provides the concept of [generalized ufuncs](https://docs.scipy.org/d...
- [Compatibility with numpy functions](array-numpy-compatibility.html.md): The following table describes the compatibilities between numpy and dask.array
- [Overlapping Computations](array-overlap.html.md): Some array operations require communication of borders between neighboring
- [Random Number Generation](array-random.html.md): Dask’s random number routines produce pseudo random numbers using combinations
- [Slicing](array-slicing.html.md): Dask Array supports most of the NumPy slicing syntax.  In particular, it
- [Sparse Arrays](array-sparse.html.md): By swapping out in-memory NumPy arrays with in-memory sparse arrays, we can
- [Stack, Concatenate, and Block](array-stack.html.md): Often we have many arrays stored on disk that we want to stack together and
- [Stats](array-stats.html.md): Dask Array implements a subset of the [scipy.stats](https://docs.scipy.org/doc/scipy-0.19.0/referenc...
- [Array](array.html.md): Dask Array implements a subset of the NumPy ndarray interface using blocked
- [API](bag-api.html.md): | [`from_sequence`](generated/dask.bag.from_sequence.md#dask.bag.from_sequence)(seq[, partition_size...
- [Create Dask Bags](bag-creation.html.md): There are several ways to create Dask bags around your data:
- [Bag](bag.html.md): Dask Bag implements operations like `map`, `filter`, `fold`, and
- [Dask Best Practices](best-practices.html.md): This is a short overview of Dask best practices. This document specifically focuses on best practices that are shared among all of the Dask APIs. Readers may first want to investigate one of the API-specific Best Practices documents first.
- [Opportunistic Caching](caching.html.md): Dask usually removes intermediate values as quickly as possible in order to
- [Changelog](changelog.html.md): This is not exhaustive. For an exhaustive list of changes, see the git log.
- [Dask Cheat Sheet](cheatsheet.html.md): The 300KB PDF [`Dask cheat sheet`](daskcheatsheet.pdf)
- [Command Line Interface](cli.html.md): Dask provides a `dask` executable for a command line interface.
- [Configuration](configuration.html.md): Taking full advantage of Dask sometimes requires user configuration.
- [Connect to remote data](how-to/connect-to-remote-data.html.md): Dask can read data from a variety of data stores including local file systems,
- [Custom Collections](custom-collections.html.md): For many problems, the built-in Dask collections (`dask.array`,
- [Custom Graphs](custom-graphs.html.md): There may be times when you want to do parallel computing but your application
- [Customize Initialization](customize-initialization.html.md): Often we want to run custom code when we start up or tear down a scheduler or
- [Dashboard Diagnostics](dashboard.html.md): The interactive Dask dashboard provides numerous diagnostic plots for live monitoring of your Dask computation. It includes information about task runtimes, communication, statistical profiling, load balancing, memory use, and much more.
- [dask.array.Array.all](generated/dask.array.Array.all.html.md): Returns True if all elements evaluate to True.
- [dask.array.Array.any](generated/dask.array.Array.any.html.md): Returns True if any of the elements evaluate to True.
- [dask.array.Array.argmax](generated/dask.array.Array.argmax.html.md): Return indices of the maximum values along the given axis.
- [dask.array.Array.argmin](generated/dask.array.Array.argmin.html.md): Return indices of the minimum values along the given axis.
- [dask.array.Array.argtopk](generated/dask.array.Array.argtopk.html.md): The indices of the top k elements of an array.
- [dask.array.Array.astype](generated/dask.array.Array.astype.html.md): Copy of the array, cast to a specified type.
- [dask.array.Array.blocks](generated/dask.array.Array.blocks.html.md): An array-like interface to the blocks of an array.
- [dask.array.Array.choose](generated/dask.array.Array.choose.html.md): Use an index array to construct a new array from a set of choices.
- [dask.array.Array.chunks](generated/dask.array.Array.chunks.html.md): Chunks property.
- [dask.array.Array.chunksize](generated/dask.array.Array.chunksize.html.md): Page content
- [dask.array.Array.clip](generated/dask.array.Array.clip.html.md): Return an array whose values are limited to `[min, max]`.
- [dask.array.Array.compute](generated/dask.array.Array.compute.html.md): Compute this dask collection
- [dask.array.Array.compute_chunk_sizes](generated/dask.array.Array.compute_chunk_sizes.html.md): Compute the chunk sizes for a Dask array. This is especially useful
- [dask.array.Array.conj](generated/dask.array.Array.conj.html.md): Complex-conjugate all elements.
- [dask.array.Array.copy](generated/dask.array.Array.copy.html.md): Copy array.  This is a no-op for dask.arrays, which are immutable
- [dask.array.Array.cumprod](generated/dask.array.Array.cumprod.html.md): Return the cumulative product of the elements along the given axis.
- [dask.array.Array.cumsum](generated/dask.array.Array.cumsum.html.md): Return the cumulative sum of the elements along the given axis.
- [dask.array.Array.dask](generated/dask.array.Array.dask.html.md): Page content
- [dask.array.Array.dot](generated/dask.array.Array.dot.html.md): Dot product of self and other.
- [dask.array.Array.dtype](generated/dask.array.Array.dtype.html.md): Page content
- [dask.array.Array.flatten](generated/dask.array.Array.flatten.html.md): Return a flattened array.
- [dask.array.Array](generated/dask.array.Array.html.md): Parallel Dask Array
- [dask.array.Array.imag](generated/dask.array.Array.imag.html.md): Page content
- [dask.array.Array.itemsize](generated/dask.array.Array.itemsize.html.md): Length of one array element in bytes
- [dask.array.Array.map_blocks](generated/dask.array.Array.map_blocks.html.md): Map a function across all blocks of a dask array.
- [dask.array.Array.map_overlap](generated/dask.array.Array.map_overlap.html.md): Map a function over blocks of the array with some overlap
- [dask.array.Array.max](generated/dask.array.Array.max.html.md): Return the maximum along a given axis.
- [dask.array.Array.mean](generated/dask.array.Array.mean.html.md): Returns the average of the array elements along given axis.
- [dask.array.Array.min](generated/dask.array.Array.min.html.md): Return the minimum along a given axis.
- [dask.array.Array.moment](generated/dask.array.Array.moment.html.md): Calculate the nth centralized moment.
- [dask.array.Array.name](generated/dask.array.Array.name.html.md): Page content
- [dask.array.Array.nbytes](generated/dask.array.Array.nbytes.html.md): Number of bytes in array
- [dask.array.Array.ndim](generated/dask.array.Array.ndim.html.md): Page content
- [dask.array.Array.nonzero](generated/dask.array.Array.nonzero.html.md): Return the indices of the elements that are non-zero.
- [dask.array.Array.npartitions](generated/dask.array.Array.npartitions.html.md): Page content
- [dask.array.Array.numblocks](generated/dask.array.Array.numblocks.html.md): Page content
- [dask.array.Array.partitions](generated/dask.array.Array.partitions.html.md): Slice an array by partitions. Alias of dask array .blocks attribute.
- [dask.array.Array.persist](generated/dask.array.Array.persist.html.md): Persist this dask collection into memory
- [dask.array.Array.prod](generated/dask.array.Array.prod.html.md): Return the product of the array elements over the given axis
- [dask.array.Array.ravel](generated/dask.array.Array.ravel.html.md): Return a flattened array.
- [dask.array.Array.real](generated/dask.array.Array.real.html.md): Page content
- [dask.array.Array.rechunk](generated/dask.array.Array.rechunk.html.md): Convert blocks in dask array x for new chunks.
- [dask.array.Array.repeat](generated/dask.array.Array.repeat.html.md): Repeat elements of an array.
- [dask.array.Array.reshape](generated/dask.array.Array.reshape.html.md): Reshape array to new shape
- [dask.array.Array.round](generated/dask.array.Array.round.html.md): Return array with each element rounded to the given number of decimals.
- [dask.array.Array.shape](generated/dask.array.Array.shape.html.md): Page content
- [dask.array.Array.shuffle](generated/dask.array.Array.shuffle.html.md): Reorders one dimensions of a Dask Array based on an indexer.
- [dask.array.Array.size](generated/dask.array.Array.size.html.md): Number of elements in array
- [dask.array.Array.squeeze](generated/dask.array.Array.squeeze.html.md): Remove axes of length one from array.
- [dask.array.Array.std](generated/dask.array.Array.std.html.md): Returns the standard deviation of the array elements along given axis.
- [dask.array.Array.store](generated/dask.array.Array.store.html.md): Store dask arrays in array-like objects, overwrite data in target
- [dask.array.Array.sum](generated/dask.array.Array.sum.html.md): Return the sum of the array elements over the given axis.
- [dask.array.Array.swapaxes](generated/dask.array.Array.swapaxes.html.md): Return a view of the array with `axis1` and `axis2` interchanged.
- [dask.array.Array.to_backend](generated/dask.array.Array.to_backend.html.md): Move to a new Array backend
- [dask.array.Array.to_dask_dataframe](generated/dask.array.Array.to_dask_dataframe.html.md): Convert dask Array to dask Dataframe
- [dask.array.Array.to_delayed](generated/dask.array.Array.to_delayed.html.md): Convert into an array of [`dask.delayed.Delayed`](../delayed-api.md#dask.delayed.Delayed) objects, o...
- [dask.array.Array.to_hdf5](generated/dask.array.Array.to_hdf5.html.md): Store array in HDF5 file
- [dask.array.Array.to_svg](generated/dask.array.Array.to_svg.html.md): Convert chunks from Dask Array into an SVG Image
- [dask.array.Array.to_tiledb](generated/dask.array.Array.to_tiledb.html.md): Save array to the TileDB storage manager
- [dask.array.Array.to_zarr](generated/dask.array.Array.to_zarr.html.md): Save array to the zarr storage format
- [dask.array.Array.topk](generated/dask.array.Array.topk.html.md): The top k elements of an array.
- [dask.array.Array.trace](generated/dask.array.Array.trace.html.md): Return the sum along diagonals of the array.
- [dask.array.Array.transpose](generated/dask.array.Array.transpose.html.md): Reverse or permute the axes of an array. Return the modified array.
- [dask.array.Array.var](generated/dask.array.Array.var.html.md): Returns the variance of the array elements, along given axis.
- [dask.array.Array.view](generated/dask.array.Array.view.html.md): Get a view of the array as a new data type
- [dask.array.Array.vindex](generated/dask.array.Array.vindex.html.md): Vectorized indexing with broadcasting.
- [dask.array.Array.visualize](generated/dask.array.Array.visualize.html.md): Render the computation of this object’s task graph using graphviz.
- [dask.array.abs](generated/dask.array.abs.html.md): This docstring was copied from numpy.absolute.
- [dask.array.absolute](generated/dask.array.absolute.html.md): This docstring was copied from numpy.absolute.
- [dask.array.add](generated/dask.array.add.html.md): This docstring was copied from numpy.add.
- [dask.array.all](generated/dask.array.all.html.md): Test whether all array elements along a given axis evaluate to True.
- [dask.array.allclose](generated/dask.array.allclose.html.md): Returns True if two arrays are element-wise equal within a tolerance.
- [dask.array.angle](generated/dask.array.angle.html.md): Return the angle of the complex argument.
- [dask.array.any](generated/dask.array.any.html.md): Test whether any array element along a given axis evaluates to True.
- [dask.array.api.normalize_chunks](generated/dask.array.api.normalize_chunks.html.md): Normalize chunks to tuple of tuples
- [dask.array.api.normalize_chunks_cached](generated/dask.array.api.normalize_chunks_cached.html.md): Cached version of normalize_chunks.
- [dask.array.append](generated/dask.array.append.html.md): Append values to the end of an array.
- [dask.array.apply_along_axis](generated/dask.array.apply_along_axis.html.md): Apply a function to 1-D slices along the given axis.
- [dask.array.apply_over_axes](generated/dask.array.apply_over_axes.html.md): Apply a function repeatedly over multiple axes.
- [dask.array.arange](generated/dask.array.arange.html.md): Return evenly spaced values from start to stop with step size step.
- [dask.array.arccos](generated/dask.array.arccos.html.md): This docstring was copied from numpy.arccos.
- [dask.array.arccosh](generated/dask.array.arccosh.html.md): This docstring was copied from numpy.arccosh.
- [dask.array.arcsin](generated/dask.array.arcsin.html.md): This docstring was copied from numpy.arcsin.
- [dask.array.arcsinh](generated/dask.array.arcsinh.html.md): This docstring was copied from numpy.arcsinh.
- [dask.array.arctan](generated/dask.array.arctan.html.md): This docstring was copied from numpy.arctan.
- [dask.array.arctan2](generated/dask.array.arctan2.html.md): This docstring was copied from numpy.arctan2.
- [dask.array.arctanh](generated/dask.array.arctanh.html.md): This docstring was copied from numpy.arctanh.
- [dask.array.argmax](generated/dask.array.argmax.html.md): Returns the indices of the maximum values along an axis.
- [dask.array.argmin](generated/dask.array.argmin.html.md): Returns the indices of the minimum values along an axis.
- [dask.array.argtopk](generated/dask.array.argtopk.html.md): Extract the indices of the k largest elements from a on the given axis,
- [dask.array.argwhere](generated/dask.array.argwhere.html.md): Find the indices of array elements that are non-zero, grouped by element.
- [dask.array.around](generated/dask.array.around.html.md): Round an array to the given number of decimals.
- [dask.array.array](generated/dask.array.array.html.md): This docstring was copied from numpy.array.
- [dask.array.asanyarray](generated/dask.array.asanyarray.html.md): Convert the input to a dask array.
- [dask.array.asarray](generated/dask.array.asarray.html.md): Convert the input to a dask array.
- [dask.array.atleast_1d](generated/dask.array.atleast_1d.html.md): Convert inputs to arrays with at least one dimension.
- [dask.array.atleast_2d](generated/dask.array.atleast_2d.html.md): View inputs as arrays with at least two dimensions.
- [dask.array.atleast_3d](generated/dask.array.atleast_3d.html.md): View inputs as arrays with at least three dimensions.
- [dask.array.average](generated/dask.array.average.html.md): Compute the weighted average along the specified axis.
- [dask.array.bincount](generated/dask.array.bincount.html.md): This docstring was copied from numpy.bincount.
- [dask.array.bitwise_and](generated/dask.array.bitwise_and.html.md): This docstring was copied from numpy.bitwise_and.
- [dask.array.bitwise_not](generated/dask.array.bitwise_not.html.md): This docstring was copied from numpy.invert.
- [dask.array.bitwise_or](generated/dask.array.bitwise_or.html.md): This docstring was copied from numpy.bitwise_or.
- [dask.array.bitwise_xor](generated/dask.array.bitwise_xor.html.md): This docstring was copied from numpy.bitwise_xor.
- [dask.array.block](generated/dask.array.block.html.md): Assemble an nd-array from nested lists of blocks.
- [dask.array.blockwise](generated/dask.array.blockwise.html.md): Tensor operation: Generalized inner and outer products
- [dask.array.broadcast_arrays](generated/dask.array.broadcast_arrays.html.md): Broadcast any number of arrays against each other.
- [dask.array.broadcast_to](generated/dask.array.broadcast_to.html.md): Broadcast an array to a new shape.
- [dask.array.cbrt](generated/dask.array.cbrt.html.md): This docstring was copied from numpy.cbrt.
- [dask.array.ceil](generated/dask.array.ceil.html.md): This docstring was copied from numpy.ceil.
- [dask.array.choose](generated/dask.array.choose.html.md): Construct an array from an index array and a list of arrays to choose from.
- [dask.array.clip](generated/dask.array.clip.html.md): Clip (limit) the values in an array.
- [dask.array.coarsen](generated/dask.array.coarsen.html.md): Coarsen array by applying reduction to fixed size neighborhoods
- [dask.array.compress](generated/dask.array.compress.html.md): Return selected slices of an array along given axis.
- [dask.array.concatenate](generated/dask.array.concatenate.html.md): Concatenate arrays along an existing axis
- [dask.array.conj](generated/dask.array.conj.html.md): This docstring was copied from numpy.conjugate.
- [dask.array.copysign](generated/dask.array.copysign.html.md): This docstring was copied from numpy.copysign.
- [dask.array.core.PerformanceWarning](generated/dask.array.core.PerformanceWarning.html.md): A warning given when bad chunking may cause poor performance
- [dask.array.core.blockwise](generated/dask.array.core.blockwise.html.md): Tensor operation: Generalized inner and outer products
- [dask.array.core.normalize_chunks](generated/dask.array.core.normalize_chunks.html.md): Normalize chunks to tuple of tuples
- [dask.array.core.unify_chunks](generated/dask.array.core.unify_chunks.html.md): Unify chunks across a sequence of arrays
- [dask.array.corrcoef](generated/dask.array.corrcoef.html.md): Return Pearson product-moment correlation coefficients.
- [dask.array.cos](generated/dask.array.cos.html.md): This docstring was copied from numpy.cos.
- [dask.array.cosh](generated/dask.array.cosh.html.md): This docstring was copied from numpy.cosh.
- [dask.array.count_nonzero](generated/dask.array.count_nonzero.html.md): Counts the number of non-zero values in the array `a`.
- [dask.array.cov](generated/dask.array.cov.html.md): Estimate a covariance matrix, given data and weights.
- [dask.array.cumprod](generated/dask.array.cumprod.html.md): Return the cumulative product of elements along a given axis.
- [dask.array.cumsum](generated/dask.array.cumsum.html.md): Return the cumulative sum of the elements along a given axis.
- [dask.array.deg2rad](generated/dask.array.deg2rad.html.md): This docstring was copied from numpy.deg2rad.
- [dask.array.degrees](generated/dask.array.degrees.html.md): This docstring was copied from numpy.degrees.
- [dask.array.delete](generated/dask.array.delete.html.md): Return a new array with sub-arrays along an axis deleted. For a one
- [dask.array.diag](generated/dask.array.diag.html.md): Extract a diagonal or construct a diagonal array.
- [dask.array.diagonal](generated/dask.array.diagonal.html.md): Return specified diagonals.
- [dask.array.diff](generated/dask.array.diff.html.md): Calculate the n-th discrete difference along the given axis.
- [dask.array.digitize](generated/dask.array.digitize.html.md): Return the indices of the bins to which each value in input array belongs.
- [dask.array.divide](generated/dask.array.divide.html.md): This docstring was copied from numpy.divide.
- [dask.array.divmod](generated/dask.array.divmod.html.md): This docstring was copied from numpy.divmod.
- [dask.array.dot](generated/dask.array.dot.html.md): This docstring was copied from numpy.dot.
- [dask.array.dstack](generated/dask.array.dstack.html.md): Stack arrays in sequence depth wise (along third axis).
- [dask.array.ediff1d](generated/dask.array.ediff1d.html.md): The differences between consecutive elements of an array.
- [dask.array.einsum](generated/dask.array.einsum.html.md): This docstring was copied from numpy.einsum.
- [dask.array.empty](generated/dask.array.empty.html.md): > Blocked variant of empty_like
- [dask.array.empty_like](generated/dask.array.empty_like.html.md): Return a new array with the same shape and type as a given array.
- [dask.array.equal](generated/dask.array.equal.html.md): This docstring was copied from numpy.equal.
- [dask.array.exp](generated/dask.array.exp.html.md): This docstring was copied from numpy.exp.
- [dask.array.exp2](generated/dask.array.exp2.html.md): This docstring was copied from numpy.exp2.
- [dask.array.expand_dims](generated/dask.array.expand_dims.html.md): Expand the shape of an array.
- [dask.array.expm1](generated/dask.array.expm1.html.md): This docstring was copied from numpy.expm1.
- [dask.array.extract](generated/dask.array.extract.html.md): Return the elements of an array that satisfy some condition.
- [dask.array.eye](generated/dask.array.eye.html.md): Return a 2-D Array with ones on the diagonal and zeros elsewhere.
- [dask.array.fabs](generated/dask.array.fabs.html.md): This docstring was copied from numpy.fabs.
- [dask.array.fft.fft](generated/dask.array.fft.fft.html.md): > Wrapping of numpy.fft.fft
- [dask.array.fft.fft2](generated/dask.array.fft.fft2.html.md): > Wrapping of numpy.fft.fft2
- [dask.array.fft.fft_wrap](generated/dask.array.fft.fft_wrap.html.md): Wrap 1D, 2D, and ND real and complex FFT functions
- [dask.array.fft.fftfreq](generated/dask.array.fft.fftfreq.html.md): Return the Discrete Fourier Transform sample frequencies.
- [dask.array.fft.fftn](generated/dask.array.fft.fftn.html.md): > Wrapping of numpy.fft.fftn
- [dask.array.fft.fftshift](generated/dask.array.fft.fftshift.html.md): Shift the zero-frequency component to the center of the spectrum.
- [dask.array.fft.hfft](generated/dask.array.fft.hfft.html.md): > Wrapping of numpy.fft.hfft
- [dask.array.fft.ifft](generated/dask.array.fft.ifft.html.md): > Wrapping of numpy.fft.ifft
- [dask.array.fft.ifft2](generated/dask.array.fft.ifft2.html.md): > Wrapping of numpy.fft.ifft2
- [dask.array.fft.ifftn](generated/dask.array.fft.ifftn.html.md): > Wrapping of numpy.fft.ifftn
- [dask.array.fft.ifftshift](generated/dask.array.fft.ifftshift.html.md): The inverse of fftshift. Although identical for even-length x, the
- [dask.array.fft.ihfft](generated/dask.array.fft.ihfft.html.md): > Wrapping of numpy.fft.ihfft
- [dask.array.fft.irfft](generated/dask.array.fft.irfft.html.md): > Wrapping of numpy.fft.irfft
- [dask.array.fft.irfft2](generated/dask.array.fft.irfft2.html.md): > Wrapping of numpy.fft.irfft2
- [dask.array.fft.irfftn](generated/dask.array.fft.irfftn.html.md): > Wrapping of numpy.fft.irfftn
- [dask.array.fft.rfft](generated/dask.array.fft.rfft.html.md): > Wrapping of numpy.fft.rfft
- [dask.array.fft.rfft2](generated/dask.array.fft.rfft2.html.md): > Wrapping of numpy.fft.rfft2
- [dask.array.fft.rfftfreq](generated/dask.array.fft.rfftfreq.html.md): Return the Discrete Fourier Transform sample frequencies
- [dask.array.fft.rfftn](generated/dask.array.fft.rfftn.html.md): > Wrapping of numpy.fft.rfftn
- [dask.array.fix](generated/dask.array.fix.html.md): Round to nearest integer towards zero.
- [dask.array.flatnonzero](generated/dask.array.flatnonzero.html.md): Return indices that are non-zero in the flattened version of a.
- [dask.array.flip](generated/dask.array.flip.html.md): Reverse element order along axis.
- [dask.array.fliplr](generated/dask.array.fliplr.html.md): Reverse the order of elements along axis 1 (left/right).
- [dask.array.flipud](generated/dask.array.flipud.html.md): Reverse the order of elements along axis 0 (up/down).
- [dask.array.float_power](generated/dask.array.float_power.html.md): This docstring was copied from numpy.float_power.
- [dask.array.floor](generated/dask.array.floor.html.md): This docstring was copied from numpy.floor.
- [dask.array.floor_divide](generated/dask.array.floor_divide.html.md): This docstring was copied from numpy.floor_divide.
- [dask.array.fmax](generated/dask.array.fmax.html.md): This docstring was copied from numpy.fmax.
- [dask.array.fmin](generated/dask.array.fmin.html.md): This docstring was copied from numpy.fmin.
- [dask.array.fmod](generated/dask.array.fmod.html.md): This docstring was copied from numpy.fmod.
- [dask.array.frexp](generated/dask.array.frexp.html.md): This docstring was copied from numpy.frexp.
- [dask.array.from_array](generated/dask.array.from_array.html.md): Create dask array from something that looks like an array.
- [dask.array.from_delayed](generated/dask.array.from_delayed.html.md): Create a dask array from a dask delayed value
- [dask.array.from_npy_stack](generated/dask.array.from_npy_stack.html.md): Load dask array from stack of npy files
- [dask.array.from_tiledb](generated/dask.array.from_tiledb.html.md): Load array from the TileDB storage format
- [dask.array.from_zarr](generated/dask.array.from_zarr.html.md): Load array from the zarr storage format
- [dask.array.fromfunction](generated/dask.array.fromfunction.html.md): Construct an array by executing a function over each coordinate.
- [dask.array.frompyfunc](generated/dask.array.frompyfunc.html.md): This docstring was copied from numpy.frompyfunc.
- [dask.array.full](generated/dask.array.full.html.md): > Blocked variant of full_like
- [dask.array.full_like](generated/dask.array.full_like.html.md): Return a full array with the same shape and type as a given array.
- [dask.array.gradient](generated/dask.array.gradient.html.md): Return the gradient of an N-dimensional array.
- [dask.array.greater](generated/dask.array.greater.html.md): This docstring was copied from numpy.greater.
- [dask.array.greater_equal](generated/dask.array.greater_equal.html.md): This docstring was copied from numpy.greater_equal.
- [dask.array.gufunc.apply_gufunc](generated/dask.array.gufunc.apply_gufunc.html.md): Apply a generalized ufunc or similar python function to arrays.
- [dask.array.gufunc.as_gufunc](generated/dask.array.gufunc.as_gufunc.html.md): Decorator for `dask.array.gufunc`.
- [dask.array.gufunc.gufunc](generated/dask.array.gufunc.gufunc.html.md): Binds pyfunc into `dask.array.apply_gufunc` when called.
- [dask.array.histogram](generated/dask.array.histogram.html.md): Blocked variant of [`numpy.histogram()`](https://numpy.org/doc/stable/reference/generated/numpy.hist...
- [dask.array.histogram2d](generated/dask.array.histogram2d.html.md): Blocked variant of [`numpy.histogram2d()`](https://numpy.org/doc/stable/reference/generated/numpy.hi...
- [dask.array.histogramdd](generated/dask.array.histogramdd.html.md): Blocked variant of [`numpy.histogramdd()`](https://numpy.org/doc/stable/reference/generated/numpy.hi...
- [dask.array.hstack](generated/dask.array.hstack.html.md): Stack arrays in sequence horizontally (column wise).
- [dask.array.hypot](generated/dask.array.hypot.html.md): This docstring was copied from numpy.hypot.
- [dask.array.i0](generated/dask.array.i0.html.md): Modified Bessel function of the first kind, order 0.
- [dask.array.imag](generated/dask.array.imag.html.md): Return the imaginary part of the complex argument.
- [dask.array.image.imread](generated/dask.array.image.imread.html.md): Read a stack of images into a dask array
- [dask.array.indices](generated/dask.array.indices.html.md): Implements NumPy’s `indices` for Dask Arrays.
- [dask.array.insert](generated/dask.array.insert.html.md): Insert values along the given axis before the given indices.
- [dask.array.invert](generated/dask.array.invert.html.md): This docstring was copied from numpy.invert.
- [dask.array.isclose](generated/dask.array.isclose.html.md): Returns a boolean array where two arrays are element-wise equal within a
- [dask.array.iscomplex](generated/dask.array.iscomplex.html.md): Returns a bool array, where True if input element is complex.
- [dask.array.isfinite](generated/dask.array.isfinite.html.md): This docstring was copied from numpy.isfinite.
- [dask.array.isin](generated/dask.array.isin.html.md): Calculates `element in test_elements`, broadcasting over element only.
- [dask.array.isinf](generated/dask.array.isinf.html.md): This docstring was copied from numpy.isinf.
- [dask.array.isnan](generated/dask.array.isnan.html.md): This docstring was copied from numpy.isnan.
- [dask.array.isneginf](generated/dask.array.isneginf.html.md): This docstring was copied from numpy.equal.
- [dask.array.isnull](generated/dask.array.isnull.html.md): pandas.isnull for dask arrays
- [dask.array.isposinf](generated/dask.array.isposinf.html.md): This docstring was copied from numpy.equal.
- [dask.array.isreal](generated/dask.array.isreal.html.md): Returns a bool array, where True if input element is real.
- [dask.array.ldexp](generated/dask.array.ldexp.html.md): This docstring was copied from numpy.ldexp.
- [dask.array.left_shift](generated/dask.array.left_shift.html.md): This docstring was copied from numpy.left_shift.
- [dask.array.less](generated/dask.array.less.html.md): This docstring was copied from numpy.less.
- [dask.array.less_equal](generated/dask.array.less_equal.html.md): This docstring was copied from numpy.less_equal.
- [dask.array.lib.stride_tricks.sliding_window_view](generated/dask.array.lib.stride_tricks.sliding_window_view.html.md): Create a sliding window view into the array with the given window shape.
- [dask.array.linalg.cholesky](generated/dask.array.linalg.cholesky.html.md): Returns the Cholesky decomposition, $A = L L^*$ or
- [dask.array.linalg.inv](generated/dask.array.linalg.inv.html.md): Compute the inverse of a matrix with LU decomposition and
- [dask.array.linalg.lstsq](generated/dask.array.linalg.lstsq.html.md): Return the least-squares solution to a linear matrix equation using
- [dask.array.linalg.lu](generated/dask.array.linalg.lu.html.md): Compute the lu decomposition of a matrix.
- [dask.array.linalg.norm](generated/dask.array.linalg.norm.html.md): Matrix or vector norm.
- [dask.array.linalg.qr](generated/dask.array.linalg.qr.html.md): Compute the qr factorization of a matrix.
- [dask.array.linalg.sfqr](generated/dask.array.linalg.sfqr.html.md): Direct Short-and-Fat QR
- [dask.array.linalg.solve](generated/dask.array.linalg.solve.html.md): Solve the equation `a x = b` for `x`. By default, use LU
- [dask.array.linalg.solve_triangular](generated/dask.array.linalg.solve_triangular.html.md): Solve the equation a x = b for x, assuming a is a triangular matrix.
- [dask.array.linalg.svd](generated/dask.array.linalg.svd.html.md): Compute the singular value decomposition of a matrix.
- [dask.array.linalg.svd_compressed](generated/dask.array.linalg.svd_compressed.html.md): Randomly compressed rank-k thin Singular Value Decomposition.
- [dask.array.linalg.tsqr](generated/dask.array.linalg.tsqr.html.md): Direct Tall-and-Skinny QR algorithm
- [dask.array.linspace](generated/dask.array.linspace.html.md): Return num evenly spaced values over the closed interval [start,
- [dask.array.log](generated/dask.array.log.html.md): This docstring was copied from numpy.log.
- [dask.array.log10](generated/dask.array.log10.html.md): This docstring was copied from numpy.log10.
- [dask.array.log1p](generated/dask.array.log1p.html.md): This docstring was copied from numpy.log1p.
- [dask.array.log2](generated/dask.array.log2.html.md): This docstring was copied from numpy.log2.
- [dask.array.logaddexp](generated/dask.array.logaddexp.html.md): This docstring was copied from numpy.logaddexp.
- [dask.array.logaddexp2](generated/dask.array.logaddexp2.html.md): This docstring was copied from numpy.logaddexp2.
- [dask.array.logical_and](generated/dask.array.logical_and.html.md): This docstring was copied from numpy.logical_and.
- [dask.array.logical_not](generated/dask.array.logical_not.html.md): This docstring was copied from numpy.logical_not.
- [dask.array.logical_or](generated/dask.array.logical_or.html.md): This docstring was copied from numpy.logical_or.
- [dask.array.logical_xor](generated/dask.array.logical_xor.html.md): This docstring was copied from numpy.logical_xor.
- [dask.array.ma.average](generated/dask.array.ma.average.html.md): Return the weighted average of array over the given axis.
- [dask.array.ma.empty_like](generated/dask.array.ma.empty_like.html.md): Return a new array with the same shape and type as a given array.
- [dask.array.ma.filled](generated/dask.array.ma.filled.html.md): Return input as an ~numpy.ndarray, with masked values replaced by
- [dask.array.ma.fix_invalid](generated/dask.array.ma.fix_invalid.html.md): Return input with invalid data masked and replaced by a fill value.
- [dask.array.ma.getdata](generated/dask.array.ma.getdata.html.md): Return the data of a masked array as an ndarray.
- [dask.array.ma.getmaskarray](generated/dask.array.ma.getmaskarray.html.md): Return the mask of a masked array, or full boolean array of False.
- [dask.array.ma.masked_array](generated/dask.array.ma.masked_array.html.md): An array class with possibly masked values.
- [dask.array.ma.masked_equal](generated/dask.array.ma.masked_equal.html.md): Mask an array where equal to a given value.
- [dask.array.ma.masked_greater](generated/dask.array.ma.masked_greater.html.md): Mask an array where greater than a given value.
- [dask.array.ma.masked_greater_equal](generated/dask.array.ma.masked_greater_equal.html.md): Mask an array where greater than or equal to a given value.
- [dask.array.ma.masked_inside](generated/dask.array.ma.masked_inside.html.md): Mask an array inside a given interval.
- [dask.array.ma.masked_invalid](generated/dask.array.ma.masked_invalid.html.md): Mask an array where invalid values occur (NaNs or infs).
- [dask.array.ma.masked_less](generated/dask.array.ma.masked_less.html.md): Mask an array where less than a given value.
- [dask.array.ma.masked_less_equal](generated/dask.array.ma.masked_less_equal.html.md): Mask an array where less than or equal to a given value.
- [dask.array.ma.masked_not_equal](generated/dask.array.ma.masked_not_equal.html.md): Mask an array where *not* equal to a given value.
- [dask.array.ma.masked_outside](generated/dask.array.ma.masked_outside.html.md): Mask an array outside a given interval.
- [dask.array.ma.masked_values](generated/dask.array.ma.masked_values.html.md): Mask using floating point equality.
- [dask.array.ma.masked_where](generated/dask.array.ma.masked_where.html.md): Mask an array where a condition is met.
- [dask.array.ma.nonzero](generated/dask.array.ma.nonzero.html.md): This docstring was copied from numpy.ma.core.nonzero.
- [dask.array.ma.ones_like](generated/dask.array.ma.ones_like.html.md): Return an array of ones with the same shape and type as a given array.
- [dask.array.ma.set_fill_value](generated/dask.array.ma.set_fill_value.html.md): Set the filling value of a, if a is a masked array.
- [dask.array.ma.where](generated/dask.array.ma.where.html.md): Return a masked array with elements from x or y, depending on condition.
- [dask.array.ma.zeros_like](generated/dask.array.ma.zeros_like.html.md): Return an array of zeros with the same shape and type as a given array.
- [dask.array.map_blocks](generated/dask.array.map_blocks.html.md): Map a function across all blocks of a dask array.
- [dask.array.map_overlap](generated/dask.array.map_overlap.html.md): Map a function over blocks of arrays with some overlap
- [dask.array.matmul](generated/dask.array.matmul.html.md): This docstring was copied from numpy.matmul.
- [dask.array.max](generated/dask.array.max.html.md): Return the maximum of an array or maximum along an axis.
- [dask.array.maximum](generated/dask.array.maximum.html.md): This docstring was copied from numpy.maximum.
- [dask.array.mean](generated/dask.array.mean.html.md): Compute the arithmetic mean along the specified axis.
- [dask.array.median](generated/dask.array.median.html.md): Compute the median along the specified axis.
- [dask.array.meshgrid](generated/dask.array.meshgrid.html.md): Return a tuple of coordinate matrices from coordinate vectors.
- [dask.array.min](generated/dask.array.min.html.md): Return the minimum of an array or minimum along an axis.
- [dask.array.minimum](generated/dask.array.minimum.html.md): This docstring was copied from numpy.minimum.
- [dask.array.mod](generated/dask.array.mod.html.md): This docstring was copied from numpy.remainder.
- [dask.array.modf](generated/dask.array.modf.html.md): This docstring was copied from numpy.modf.
- [dask.array.moment](generated/dask.array.moment.html.md): Calculate the nth centralized moment.
- [dask.array.moveaxis](generated/dask.array.moveaxis.html.md): Move axes of an array to new positions.
- [dask.array.multiply](generated/dask.array.multiply.html.md): This docstring was copied from numpy.multiply.
- [dask.array.nan_to_num](generated/dask.array.nan_to_num.html.md): Replace NaN with zero and infinity with large finite numbers (default
- [dask.array.nanargmax](generated/dask.array.nanargmax.html.md): Return the indices of the maximum values in the specified axis ignoring
- [dask.array.nanargmin](generated/dask.array.nanargmin.html.md): Return the indices of the minimum values in the specified axis ignoring
- [dask.array.nancumprod](generated/dask.array.nancumprod.html.md): Return the cumulative product of array elements over a given axis treating Not a
- [dask.array.nancumsum](generated/dask.array.nancumsum.html.md): Return the cumulative sum of array elements over a given axis treating Not a
- [dask.array.nanmax](generated/dask.array.nanmax.html.md): Return the maximum of an array or maximum along an axis, ignoring any
- [dask.array.nanmean](generated/dask.array.nanmean.html.md): Compute the arithmetic mean along the specified axis, ignoring NaNs.
- [dask.array.nanmedian](generated/dask.array.nanmedian.html.md): Compute the median along the specified axis, while ignoring NaNs.
- [dask.array.nanmin](generated/dask.array.nanmin.html.md): Return minimum of an array or minimum along an axis, ignoring any NaNs.
- [dask.array.nanpercentile](generated/dask.array.nanpercentile.html.md): Compute the qth percentile of the data along the specified axis,
- [dask.array.nanprod](generated/dask.array.nanprod.html.md): Return the product of array elements over a given axis treating Not a
- [dask.array.nanquantile](generated/dask.array.nanquantile.html.md): Compute the qth quantile of the data along the specified axis,
- [dask.array.nanstd](generated/dask.array.nanstd.html.md): Compute the standard deviation along the specified axis, while
- [dask.array.nansum](generated/dask.array.nansum.html.md): Return the sum of array elements over a given axis treating Not a
- [dask.array.nanvar](generated/dask.array.nanvar.html.md): Compute the variance along the specified axis, while ignoring NaNs.
- [dask.array.negative](generated/dask.array.negative.html.md): This docstring was copied from numpy.negative.
- [dask.array.nextafter](generated/dask.array.nextafter.html.md): This docstring was copied from numpy.nextafter.
- [dask.array.nonzero](generated/dask.array.nonzero.html.md): Return the indices of the elements that are non-zero.
- [dask.array.not_equal](generated/dask.array.not_equal.html.md): This docstring was copied from numpy.not_equal.
- [dask.array.notnull](generated/dask.array.notnull.html.md): pandas.notnull for dask arrays
- [dask.array.ones](generated/dask.array.ones.html.md): > Blocked variant of ones_like
- [dask.array.ones_like](generated/dask.array.ones_like.html.md): Return an array of ones with the same shape and type as a given array.
- [dask.array.outer](generated/dask.array.outer.html.md): Compute the outer product of two vectors.
- [dask.array.overlap.map_overlap](generated/dask.array.overlap.map_overlap.html.md): Map a function over blocks of arrays with some overlap
- [dask.array.overlap.overlap](generated/dask.array.overlap.overlap.html.md): Share boundaries between neighboring blocks
- [dask.array.overlap.trim_internal](generated/dask.array.overlap.trim_internal.html.md): Trim sides from each block
- [dask.array.overlap.trim_overlap](generated/dask.array.overlap.trim_overlap.html.md): Trim sides from each block.
- [dask.array.pad](generated/dask.array.pad.html.md): Pad an array.
- [dask.array.percentile](generated/dask.array.percentile.html.md): Approximate percentile of 1-D array
- [dask.array.piecewise](generated/dask.array.piecewise.html.md): Evaluate a piecewise-defined function.
- [dask.array.positive](generated/dask.array.positive.html.md): This docstring was copied from numpy.positive.
- [dask.array.power](generated/dask.array.power.html.md): This docstring was copied from numpy.power.
- [dask.array.prod](generated/dask.array.prod.html.md): Return the product of array elements over a given axis.
- [dask.array.ptp](generated/dask.array.ptp.html.md): Range of values (maximum - minimum) along an axis.
- [dask.array.push](generated/dask.array.push.html.md): Dask-version of bottleneck.push
- [dask.array.quantile](generated/dask.array.quantile.html.md): Compute the q-th quantile of the data along the specified axis.
- [dask.array.rad2deg](generated/dask.array.rad2deg.html.md): This docstring was copied from numpy.rad2deg.
- [dask.array.radians](generated/dask.array.radians.html.md): This docstring was copied from numpy.radians.
- [dask.array.random.beta](generated/dask.array.random.beta.html.md): Draw samples from a Beta distribution.
- [dask.array.random.binomial](generated/dask.array.random.binomial.html.md): Draw samples from a binomial distribution.
- [dask.array.random.chisquare](generated/dask.array.random.chisquare.html.md): Draw samples from a chi-square distribution.
- [dask.array.random.choice](generated/dask.array.random.choice.html.md): Generates a random sample from a given 1-D array
- [dask.array.random.default_rng](generated/dask.array.random.default_rng.html.md): Construct a new Generator with the default BitGenerator (PCG64).
- [dask.array.random.exponential](generated/dask.array.random.exponential.html.md): Draw samples from an exponential distribution.
- [dask.array.random.f](generated/dask.array.random.f.html.md): Draw samples from an F distribution.
- [dask.array.random.gamma](generated/dask.array.random.gamma.html.md): Draw samples from a Gamma distribution.
- [dask.array.random.geometric](generated/dask.array.random.geometric.html.md): Draw samples from the geometric distribution.
- [dask.array.random.gumbel](generated/dask.array.random.gumbel.html.md): Draw samples from a Gumbel distribution.
- [dask.array.random.hypergeometric](generated/dask.array.random.hypergeometric.html.md): Draw samples from a Hypergeometric distribution.
- [dask.array.random.laplace](generated/dask.array.random.laplace.html.md): Draw samples from the Laplace or double exponential distribution with
- [dask.array.random.logistic](generated/dask.array.random.logistic.html.md): Draw samples from a logistic distribution.
- [dask.array.random.lognormal](generated/dask.array.random.lognormal.html.md): Draw samples from a log-normal distribution.
- [dask.array.random.logseries](generated/dask.array.random.logseries.html.md): Draw samples from a logarithmic series distribution.
- [dask.array.random.multinomial](generated/dask.array.random.multinomial.html.md): Draw samples from a multinomial distribution.
- [dask.array.random.negative_binomial](generated/dask.array.random.negative_binomial.html.md): Draw samples from a negative binomial distribution.
- [dask.array.random.noncentral_chisquare](generated/dask.array.random.noncentral_chisquare.html.md): Draw samples from a noncentral chi-square distribution.
- [dask.array.random.noncentral_f](generated/dask.array.random.noncentral_f.html.md): Draw samples from the noncentral F distribution.
- [dask.array.random.normal](generated/dask.array.random.normal.html.md): Draw random samples from a normal (Gaussian) distribution.
- [dask.array.random.pareto](generated/dask.array.random.pareto.html.md): Draw samples from a Pareto II or Lomax distribution with
- [dask.array.random.permutation](generated/dask.array.random.permutation.html.md): Randomly permute a sequence, or return a permuted range.
- [dask.array.random.poisson](generated/dask.array.random.poisson.html.md): Draw samples from a Poisson distribution.
- [dask.array.random.power](generated/dask.array.random.power.html.md): Draws samples in [0, 1] from a power distribution with positive
- [dask.array.random.randint](generated/dask.array.random.randint.html.md): Return random integers from low (inclusive) to high (exclusive).
- [dask.array.random.random](generated/dask.array.random.random.html.md): Return random floats in the half-open interval [0.0, 1.0).
- [dask.array.random.random_integers](generated/dask.array.random.random_integers.html.md): Random integers of type numpy.int_ between low and high, inclusive.
- [dask.array.random.random_sample](generated/dask.array.random.random_sample.html.md): Return random floats in the half-open interval [0.0, 1.0).
- [dask.array.random.rayleigh](generated/dask.array.random.rayleigh.html.md): Draw samples from a Rayleigh distribution.
- [dask.array.random.standard_cauchy](generated/dask.array.random.standard_cauchy.html.md): Draw samples from a standard Cauchy distribution with mode = 0.
- [dask.array.random.standard_exponential](generated/dask.array.random.standard_exponential.html.md): Draw samples from the standard exponential distribution.
- [dask.array.random.standard_gamma](generated/dask.array.random.standard_gamma.html.md): Draw samples from a standard Gamma distribution.
- [dask.array.random.standard_normal](generated/dask.array.random.standard_normal.html.md): Draw samples from a standard Normal distribution (mean=0, stdev=1).
- [dask.array.random.standard_t](generated/dask.array.random.standard_t.html.md): Draw samples from a standard Student’s t distribution with df degrees
- [dask.array.random.triangular](generated/dask.array.random.triangular.html.md): Draw samples from the triangular distribution over the
- [dask.array.random.uniform](generated/dask.array.random.uniform.html.md): Draw samples from a uniform distribution.
- [dask.array.random.vonmises](generated/dask.array.random.vonmises.html.md): Draw samples from a von Mises distribution.
- [dask.array.random.wald](generated/dask.array.random.wald.html.md): Draw samples from a Wald, or inverse Gaussian, distribution.
- [dask.array.random.weibull](generated/dask.array.random.weibull.html.md): Draw samples from a Weibull distribution.
- [dask.array.random.zipf](generated/dask.array.random.zipf.html.md): Draw samples from a Zipf distribution.
- [dask.array.ravel](generated/dask.array.ravel.html.md): Return a contiguous flattened array.
- [dask.array.ravel_multi_index](generated/dask.array.ravel_multi_index.html.md): Converts a tuple of index arrays into an array of flat
- [dask.array.real](generated/dask.array.real.html.md): Return the real part of the complex argument.
- [dask.array.rechunk](generated/dask.array.rechunk.html.md): Convert blocks in dask array x for new chunks.
- [dask.array.reciprocal](generated/dask.array.reciprocal.html.md): This docstring was copied from numpy.reciprocal.
- [dask.array.reduction](generated/dask.array.reduction.html.md): General version of reductions
- [dask.array.register_chunk_type](generated/dask.array.register_chunk_type.html.md): Register the given type as a valid chunk and downcast array type
- [dask.array.remainder](generated/dask.array.remainder.html.md): This docstring was copied from numpy.remainder.
- [dask.array.repeat](generated/dask.array.repeat.html.md): Repeat each element of an array after themselves
- [dask.array.reshape](generated/dask.array.reshape.html.md): Reshape array to new shape
- [dask.array.reshape_blockwise](generated/dask.array.reshape_blockwise.html.md): Blockwise-reshape into a new shape.
- [dask.array.result_type](generated/dask.array.result_type.html.md): This docstring was copied from numpy.result_type.
- [dask.array.right_shift](generated/dask.array.right_shift.html.md): This docstring was copied from numpy.right_shift.
- [dask.array.rint](generated/dask.array.rint.html.md): This docstring was copied from numpy.rint.
- [dask.array.roll](generated/dask.array.roll.html.md): Roll array elements along a given axis.
- [dask.array.rollaxis](generated/dask.array.rollaxis.html.md): Page content
- [dask.array.rot90](generated/dask.array.rot90.html.md): Rotate an array by 90 degrees in the plane specified by axes.
- [dask.array.round](generated/dask.array.round.html.md): Evenly round to the given number of decimals.
- [dask.array.searchsorted](generated/dask.array.searchsorted.html.md): Find indices where elements should be inserted to maintain order.
- [dask.array.select](generated/dask.array.select.html.md): Return an array drawn from elements in choicelist, depending on conditions.
- [dask.array.shape](generated/dask.array.shape.html.md): Return the shape of an array.
- [dask.array.shuffle](generated/dask.array.shuffle.html.md): Reorders one dimensions of a Dask Array based on an indexer.
- [dask.array.sign](generated/dask.array.sign.html.md): This docstring was copied from numpy.sign.
- [dask.array.signbit](generated/dask.array.signbit.html.md): This docstring was copied from numpy.signbit.
- [dask.array.sin](generated/dask.array.sin.html.md): This docstring was copied from numpy.sin.
- [dask.array.sinc](generated/dask.array.sinc.html.md): Return the normalized sinc function.
- [dask.array.sinh](generated/dask.array.sinh.html.md): This docstring was copied from numpy.sinh.
- [dask.array.spacing](generated/dask.array.spacing.html.md): This docstring was copied from numpy.spacing.
- [dask.array.sqrt](generated/dask.array.sqrt.html.md): This docstring was copied from numpy.sqrt.
- [dask.array.square](generated/dask.array.square.html.md): This docstring was copied from numpy.square.
- [dask.array.squeeze](generated/dask.array.squeeze.html.md): Remove axes of length one from a.
- [dask.array.stack](generated/dask.array.stack.html.md): Stack arrays along a new axis
- [dask.array.stats.chisquare](generated/dask.array.stats.chisquare.html.md): Calculate a one-way chi-square test.
- [dask.array.stats.f_oneway](generated/dask.array.stats.f_oneway.html.md): Perform one-way ANOVA.
- [dask.array.stats.kurtosis](generated/dask.array.stats.kurtosis.html.md): Compute the kurtosis (Fisher or Pearson) of a dataset.
- [dask.array.stats.kurtosistest](generated/dask.array.stats.kurtosistest.html.md): Test whether a dataset has normal kurtosis.
- [dask.array.stats.moment](generated/dask.array.stats.moment.html.md): Calculate the nth moment about the mean for a sample.
- [dask.array.stats.normaltest](generated/dask.array.stats.normaltest.html.md): Test whether a sample differs from a normal distribution.
- [dask.array.stats.power_divergence](generated/dask.array.stats.power_divergence.html.md): Cressie-Read power divergence statistic and goodness of fit test.
- [dask.array.stats.skew](generated/dask.array.stats.skew.html.md): Compute the sample skewness of a data set.
- [dask.array.stats.skewtest](generated/dask.array.stats.skewtest.html.md): Test whether the skew is different from the normal distribution.
- [dask.array.stats.ttest_1samp](generated/dask.array.stats.ttest_1samp.html.md): Calculate the T-test for the mean of ONE group of scores.
- [dask.array.stats.ttest_ind](generated/dask.array.stats.ttest_ind.html.md): Calculate the T-test for the means of *two independent* samples of scores.
- [dask.array.stats.ttest_rel](generated/dask.array.stats.ttest_rel.html.md): Calculate the t-test on TWO RELATED samples of scores, a and b.
- [dask.array.std](generated/dask.array.std.html.md): Compute the standard deviation along the specified axis.
- [dask.array.store](generated/dask.array.store.html.md): Store dask arrays in array-like objects, overwrite data in target
- [dask.array.subtract](generated/dask.array.subtract.html.md): This docstring was copied from numpy.subtract.
- [dask.array.sum](generated/dask.array.sum.html.md): Sum of array elements over a given axis.
- [dask.array.swapaxes](generated/dask.array.swapaxes.html.md): Interchange two axes of an array.
- [dask.array.take](generated/dask.array.take.html.md): Take elements from an array along an axis.
- [dask.array.tan](generated/dask.array.tan.html.md): This docstring was copied from numpy.tan.
- [dask.array.tanh](generated/dask.array.tanh.html.md): This docstring was copied from numpy.tanh.
- [dask.array.tensordot](generated/dask.array.tensordot.html.md): Compute tensor dot product along specified axes.
- [dask.array.tile](generated/dask.array.tile.html.md): Construct an array by repeating A the number of times given by reps.
- [dask.array.to_hdf5](generated/dask.array.to_hdf5.html.md): Store arrays in HDF5 file
- [dask.array.to_npy_stack](generated/dask.array.to_npy_stack.html.md): Write dask array to a stack of .npy files
- [dask.array.to_tiledb](generated/dask.array.to_tiledb.html.md): Save array to the TileDB storage format
- [dask.array.to_zarr](generated/dask.array.to_zarr.html.md): Save array to the zarr storage format
- [dask.array.topk](generated/dask.array.topk.html.md): Extract the k largest elements from a on the given axis,
- [dask.array.trace](generated/dask.array.trace.html.md): Return the sum along diagonals of the array.
- [dask.array.transpose](generated/dask.array.transpose.html.md): Returns an array with axes transposed.
- [dask.array.tri](generated/dask.array.tri.html.md): An array with ones at and below the given diagonal and zeros elsewhere.
- [dask.array.tril](generated/dask.array.tril.html.md): Lower triangle of an array.
- [dask.array.tril_indices](generated/dask.array.tril_indices.html.md): Return the indices for the lower-triangle of an (n, m) array.
- [dask.array.tril_indices_from](generated/dask.array.tril_indices_from.html.md): Return the indices for the lower-triangle of arr.
- [dask.array.triu](generated/dask.array.triu.html.md): Upper triangle of an array.
- [dask.array.triu_indices](generated/dask.array.triu_indices.html.md): Return the indices for the upper-triangle of an (n, m) array.
- [dask.array.triu_indices_from](generated/dask.array.triu_indices_from.html.md): Return the indices for the upper-triangle of arr.
- [dask.array.true_divide](generated/dask.array.true_divide.html.md): This docstring was copied from numpy.divide.
- [dask.array.trunc](generated/dask.array.trunc.html.md): This docstring was copied from numpy.trunc.
- [dask.array.union1d](generated/dask.array.union1d.html.md): Find the union of two arrays.
- [dask.array.unique](generated/dask.array.unique.html.md): Find the unique elements of an array.
- [dask.array.unravel_index](generated/dask.array.unravel_index.html.md): This docstring was copied from numpy.unravel_index.
- [dask.array.utils.meta_from_array](generated/dask.array.utils.meta_from_array.html.md): Normalize an array to appropriate meta object
- [dask.array.var](generated/dask.array.var.html.md): Compute the variance along the specified axis.
- [dask.array.vdot](generated/dask.array.vdot.html.md): This docstring was copied from numpy.vdot.
- [dask.array.vstack](generated/dask.array.vstack.html.md): Stack arrays in sequence vertically (row wise).
- [dask.array.where](generated/dask.array.where.html.md): This docstring was copied from numpy.where.
- [dask.array.zeros](generated/dask.array.zeros.html.md): > Blocked variant of zeros_like
- [dask.array.zeros_like](generated/dask.array.zeros_like.html.md): Return an array of zeros with the same shape and type as a given array.
- [dask.bag.Bag.accumulate](generated/dask.bag.Bag.accumulate.html.md): Repeatedly apply binary function to a sequence, accumulating results.
- [dask.bag.Bag.all](generated/dask.bag.Bag.all.html.md): Are all elements truthy?
- [dask.bag.Bag.any](generated/dask.bag.Bag.any.html.md): Are any of the elements truthy?
- [dask.bag.Bag.compute](generated/dask.bag.Bag.compute.html.md): Compute this dask collection
- [dask.bag.Bag.count](generated/dask.bag.Bag.count.html.md): Count the number of elements.
- [dask.bag.Bag.distinct](generated/dask.bag.Bag.distinct.html.md): Distinct elements of collection
- [dask.bag.Bag.filter](generated/dask.bag.Bag.filter.html.md): Filter elements in collection by a predicate function.
- [dask.bag.Bag.flatten](generated/dask.bag.Bag.flatten.html.md): Concatenate nested lists into one long list.
- [dask.bag.Bag.fold](generated/dask.bag.Bag.fold.html.md): Parallelizable reduction
- [dask.bag.Bag.foldby](generated/dask.bag.Bag.foldby.html.md): Combined reduction and groupby.
- [dask.bag.Bag.frequencies](generated/dask.bag.Bag.frequencies.html.md): Count number of occurrences of each distinct element.
- [dask.bag.Bag.groupby](generated/dask.bag.Bag.groupby.html.md): Group collection by key function
- [dask.bag.Bag](generated/dask.bag.Bag.html.md): Parallel collection of Python objects
- [dask.bag.Bag.join](generated/dask.bag.Bag.join.html.md): Joins collection with another collection.
- [dask.bag.Bag.map](generated/dask.bag.Bag.map.html.md): Apply a function elementwise across one or more bags.
- [dask.bag.Bag.map_partitions](generated/dask.bag.Bag.map_partitions.html.md): Apply a function to every partition across one or more bags.
- [dask.bag.Bag.max](generated/dask.bag.Bag.max.html.md): Maximum element
- [dask.bag.Bag.mean](generated/dask.bag.Bag.mean.html.md): Arithmetic mean
- [dask.bag.Bag.min](generated/dask.bag.Bag.min.html.md): Minimum element
- [dask.bag.Bag.persist](generated/dask.bag.Bag.persist.html.md): Persist this dask collection into memory
- [dask.bag.Bag.pluck](generated/dask.bag.Bag.pluck.html.md): Select item from all tuples/dicts in collection.
- [dask.bag.Bag.product](generated/dask.bag.Bag.product.html.md): Cartesian product between two bags.
- [dask.bag.Bag.random_sample](generated/dask.bag.Bag.random_sample.html.md): Return elements from bag with probability of `prob`.
- [dask.bag.Bag.reduction](generated/dask.bag.Bag.reduction.html.md): Reduce collection with reduction operators.
- [dask.bag.Bag.remove](generated/dask.bag.Bag.remove.html.md): Remove elements in collection that match predicate.
- [dask.bag.Bag.repartition](generated/dask.bag.Bag.repartition.html.md): Repartition Bag across new divisions.
- [dask.bag.Bag.starmap](generated/dask.bag.Bag.starmap.html.md): Apply a function using argument tuples from the given bag.
- [dask.bag.Bag.std](generated/dask.bag.Bag.std.html.md): Standard deviation
- [dask.bag.Bag.sum](generated/dask.bag.Bag.sum.html.md): Sum all elements
- [dask.bag.Bag.take](generated/dask.bag.Bag.take.html.md): Take the first k elements.
- [dask.bag.Bag.to_avro](generated/dask.bag.Bag.to_avro.html.md): Write bag to set of avro files
- [dask.bag.Bag.to_dataframe](generated/dask.bag.Bag.to_dataframe.html.md): Create Dask Dataframe from a Dask Bag.
- [dask.bag.Bag.to_delayed](generated/dask.bag.Bag.to_delayed.html.md): Convert into a list of `dask.delayed` objects, one per partition.
- [dask.bag.Bag.to_textfiles](generated/dask.bag.Bag.to_textfiles.html.md): Write dask Bag to disk, one filename per partition, one line per element.
- [dask.bag.Bag.topk](generated/dask.bag.Bag.topk.html.md): K largest elements in collection
- [dask.bag.Bag.var](generated/dask.bag.Bag.var.html.md): Page content
- [dask.bag.Bag.visualize](generated/dask.bag.Bag.visualize.html.md): Render the computation of this object’s task graph using graphviz.
- [dask.bag.Item.apply](generated/dask.bag.Item.apply.html.md): Page content
- [dask.bag.Item.compute](generated/dask.bag.Item.compute.html.md): Compute this dask collection
- [dask.bag.Item.from_delayed](generated/dask.bag.Item.from_delayed.html.md): Create bag item from a dask.delayed value.
- [dask.bag.Item](generated/dask.bag.Item.html.md): | [`__init__`](#dask.bag.Item.__init__)(dsk, key[, layer])                                          ...
- [dask.bag.Item.persist](generated/dask.bag.Item.persist.html.md): Persist this dask collection into memory
- [dask.bag.Item.to_delayed](generated/dask.bag.Item.to_delayed.html.md): Convert into a `dask.delayed` object.
- [dask.bag.Item.visualize](generated/dask.bag.Item.visualize.html.md): Render the computation of this object’s task graph using graphviz.
- [dask.bag.concat](generated/dask.bag.concat.html.md): Concatenate many bags together, unioning all elements.
- [dask.bag.from_delayed](generated/dask.bag.from_delayed.html.md): Create bag from many dask Delayed objects.
- [dask.bag.from_sequence](generated/dask.bag.from_sequence.html.md): Create a dask Bag from Python sequence.
- [dask.bag.from_url](generated/dask.bag.from_url.html.md): Create a dask Bag from a url.
- [dask.bag.map](generated/dask.bag.map.html.md): Apply a function elementwise across one or more bags.
- [dask.bag.map_partitions](generated/dask.bag.map_partitions.html.md): Apply a function to every partition across one or more bags.
- [dask.bag.random.choices](generated/dask.bag.random.choices.html.md): Return a k sized list of elements chosen with replacement.
- [dask.bag.random.sample](generated/dask.bag.random.sample.html.md): Chooses k unique random elements from a bag.
- [dask.bag.range](generated/dask.bag.range.html.md): Numbers from zero to n
- [dask.bag.read_avro](generated/dask.bag.read_avro.html.md): Read set of avro files
- [dask.bag.read_text](generated/dask.bag.read_text.html.md): Read lines from text files
- [dask.bag.to_textfiles](generated/dask.bag.to_textfiles.html.md): Write dask Bag to disk, one filename per partition, one line per element.
- [dask.bag.zip](generated/dask.bag.zip.html.md): Partition-wise bag zip
- [dask.dataframe.Aggregation](generated/dask.dataframe.Aggregation.html.md): User defined groupby-aggregation.
- [dask.dataframe.DataFrame.abs](generated/dask.dataframe.DataFrame.abs.html.md): Return a Series/DataFrame with absolute numeric value of each element.
- [dask.dataframe.DataFrame.add](generated/dask.dataframe.DataFrame.add.html.md): Page content
- [dask.dataframe.DataFrame.align](generated/dask.dataframe.DataFrame.align.html.md): Align two objects on their axes with the specified join method.
- [dask.dataframe.DataFrame.all](generated/dask.dataframe.DataFrame.all.html.md): Return whether all elements are True, potentially over an axis.
- [dask.dataframe.DataFrame.analyze](generated/dask.dataframe.DataFrame.analyze.html.md): Outputs statistics about every node in the expression.
- [dask.dataframe.DataFrame.any](generated/dask.dataframe.DataFrame.any.html.md): Return whether any element is True, potentially over an axis.
- [dask.dataframe.DataFrame.apply](generated/dask.dataframe.DataFrame.apply.html.md): Parallel version of pandas.DataFrame.apply
- [dask.dataframe.DataFrame.assign](generated/dask.dataframe.DataFrame.assign.html.md): Assign new columns to a DataFrame.
- [dask.dataframe.DataFrame.astype](generated/dask.dataframe.DataFrame.astype.html.md): Cast a pandas object to a specified dtype `dtype`.
- [dask.dataframe.DataFrame.bfill](generated/dask.dataframe.DataFrame.bfill.html.md): Fill NA/NaN values by using the next valid observation to fill the gap.
- [dask.dataframe.DataFrame.categorize](generated/dask.dataframe.DataFrame.categorize.html.md): Convert columns of the DataFrame to category dtype.
- [dask.dataframe.DataFrame.columns](generated/dask.dataframe.DataFrame.columns.html.md): Page content
- [dask.dataframe.DataFrame.compute](generated/dask.dataframe.DataFrame.compute.html.md): Compute this dask collection
- [dask.dataframe.DataFrame.copy](generated/dask.dataframe.DataFrame.copy.html.md): Make a copy of the dataframe
- [dask.dataframe.DataFrame.corr](generated/dask.dataframe.DataFrame.corr.html.md): Compute pairwise correlation of columns, excluding NA/null values.
- [dask.dataframe.DataFrame.count](generated/dask.dataframe.DataFrame.count.html.md): Count non-NA cells for each column or row.
- [dask.dataframe.DataFrame.cov](generated/dask.dataframe.DataFrame.cov.html.md): Compute pairwise covariance of columns, excluding NA/null values.
- [dask.dataframe.DataFrame.cummax](generated/dask.dataframe.DataFrame.cummax.html.md): Return cumulative maximum over a DataFrame or Series axis.
- [dask.dataframe.DataFrame.cummin](generated/dask.dataframe.DataFrame.cummin.html.md): Return cumulative minimum over a DataFrame or Series axis.
- [dask.dataframe.DataFrame.cumprod](generated/dask.dataframe.DataFrame.cumprod.html.md): Return cumulative product over a DataFrame or Series axis.
- [dask.dataframe.DataFrame.cumsum](generated/dask.dataframe.DataFrame.cumsum.html.md): Return cumulative sum over a DataFrame or Series axis.
- [dask.dataframe.DataFrame.describe](generated/dask.dataframe.DataFrame.describe.html.md): Generate descriptive statistics.
- [dask.dataframe.DataFrame.diff](generated/dask.dataframe.DataFrame.diff.html.md): First discrete difference of element.
- [dask.dataframe.DataFrame.div](generated/dask.dataframe.DataFrame.div.html.md): Page content
- [dask.dataframe.DataFrame.divide](generated/dask.dataframe.DataFrame.divide.html.md): Page content
- [dask.dataframe.DataFrame.divisions](generated/dask.dataframe.DataFrame.divisions.html.md): Tuple of `npartitions + 1` values, in ascending order, marking the
- [dask.dataframe.DataFrame.drop](generated/dask.dataframe.DataFrame.drop.html.md): Drop specified labels from rows or columns.
- [dask.dataframe.DataFrame.drop_duplicates](generated/dask.dataframe.DataFrame.drop_duplicates.html.md): Return DataFrame with duplicate rows removed.
- [dask.dataframe.DataFrame.dropna](generated/dask.dataframe.DataFrame.dropna.html.md): Remove missing values.
- [dask.dataframe.DataFrame.dtypes](generated/dask.dataframe.DataFrame.dtypes.html.md): Return data types
- [dask.dataframe.DataFrame.eq](generated/dask.dataframe.DataFrame.eq.html.md): Page content
- [dask.dataframe.DataFrame.eval](generated/dask.dataframe.DataFrame.eval.html.md): Evaluate a string describing operations on DataFrame columns.
- [dask.dataframe.DataFrame.explain](generated/dask.dataframe.DataFrame.explain.html.md): Create a graph representation of the Expression.
- [dask.dataframe.DataFrame.explode](generated/dask.dataframe.DataFrame.explode.html.md): Transform each element of a list-like to a row, replicating index values.
- [dask.dataframe.DataFrame.ffill](generated/dask.dataframe.DataFrame.ffill.html.md): Fill NA/NaN values by propagating the last valid observation to next valid.
- [dask.dataframe.DataFrame.fillna](generated/dask.dataframe.DataFrame.fillna.html.md): Fill NA/NaN values with value.
- [dask.dataframe.DataFrame.floordiv](generated/dask.dataframe.DataFrame.floordiv.html.md): Page content
- [dask.dataframe.DataFrame.from_dict](generated/dask.dataframe.DataFrame.from_dict.html.md): Construct a Dask DataFrame from a Python Dictionary
- [dask.dataframe.DataFrame.ge](generated/dask.dataframe.DataFrame.ge.html.md): Page content
- [dask.dataframe.DataFrame.get_partition](generated/dask.dataframe.DataFrame.get_partition.html.md): Get a dask DataFrame/Series representing the nth partition.
- [dask.dataframe.DataFrame.groupby](generated/dask.dataframe.DataFrame.groupby.html.md): Group DataFrame using a mapper or by a Series of columns.
- [dask.dataframe.DataFrame.gt](generated/dask.dataframe.DataFrame.gt.html.md): Page content
- [dask.dataframe.DataFrame.head](generated/dask.dataframe.DataFrame.head.html.md): First n rows of the dataset
- [dask.dataframe.DataFrame](generated/dask.dataframe.DataFrame.html.md): DataFrame-like Expr Collection.
- [dask.dataframe.DataFrame.idxmax](generated/dask.dataframe.DataFrame.idxmax.html.md): Return index of first occurrence of maximum over requested axis.
- [dask.dataframe.DataFrame.idxmin](generated/dask.dataframe.DataFrame.idxmin.html.md): Return index of first occurrence of minimum over requested axis.
- [dask.dataframe.DataFrame.iloc](generated/dask.dataframe.DataFrame.iloc.html.md): Purely integer-location based indexing for selection by position.
- [dask.dataframe.DataFrame.index](generated/dask.dataframe.DataFrame.index.html.md): Return dask Index instance
- [dask.dataframe.DataFrame.info](generated/dask.dataframe.DataFrame.info.html.md): Concise summary of a Dask DataFrame
- [dask.dataframe.DataFrame.isin](generated/dask.dataframe.DataFrame.isin.html.md): Whether each element in the DataFrame is contained in values.
- [dask.dataframe.DataFrame.isna](generated/dask.dataframe.DataFrame.isna.html.md): Detect missing values.
- [dask.dataframe.DataFrame.isnull](generated/dask.dataframe.DataFrame.isnull.html.md): DataFrame.isnull is an alias for DataFrame.isna.
- [dask.dataframe.DataFrame.items](generated/dask.dataframe.DataFrame.items.html.md): Iterate over (column name, Series) pairs.
- [dask.dataframe.DataFrame.iterrows](generated/dask.dataframe.DataFrame.iterrows.html.md): Iterate over DataFrame rows as (index, Series) pairs.
- [dask.dataframe.DataFrame.itertuples](generated/dask.dataframe.DataFrame.itertuples.html.md): Iterate over DataFrame rows as namedtuples.
- [dask.dataframe.DataFrame.join](generated/dask.dataframe.DataFrame.join.html.md): Join columns of another DataFrame.
- [dask.dataframe.DataFrame.known_divisions](generated/dask.dataframe.DataFrame.known_divisions.html.md): Whether the divisions are known.
- [dask.dataframe.DataFrame.le](generated/dask.dataframe.DataFrame.le.html.md): Page content
- [dask.dataframe.DataFrame.loc](generated/dask.dataframe.DataFrame.loc.html.md): Purely label-location based indexer for selection by label.
- [dask.dataframe.DataFrame.lt](generated/dask.dataframe.DataFrame.lt.html.md): Page content
- [dask.dataframe.DataFrame.map_partitions](generated/dask.dataframe.DataFrame.map_partitions.html.md): Apply a Python function to each partition
- [dask.dataframe.DataFrame.mask](generated/dask.dataframe.DataFrame.mask.html.md): Replace values where the condition is True.
- [dask.dataframe.DataFrame.max](generated/dask.dataframe.DataFrame.max.html.md): Return the maximum of the values over the requested axis.
- [dask.dataframe.DataFrame.mean](generated/dask.dataframe.DataFrame.mean.html.md): Return the mean of the values over the requested axis.
- [dask.dataframe.DataFrame.median](generated/dask.dataframe.DataFrame.median.html.md): Return the median of the values over the requested axis.
- [dask.dataframe.DataFrame.median_approximate](generated/dask.dataframe.DataFrame.median_approximate.html.md): Return the approximate median of the values over the requested axis.
- [dask.dataframe.DataFrame.melt](generated/dask.dataframe.DataFrame.melt.html.md): Unpivot DataFrame from wide to long format, optionally leaving identifiers set.
- [dask.dataframe.DataFrame.memory_usage](generated/dask.dataframe.DataFrame.memory_usage.html.md): Return the memory usage of each column in bytes.
- [dask.dataframe.DataFrame.memory_usage_per_partition](generated/dask.dataframe.DataFrame.memory_usage_per_partition.html.md): Return the memory usage of each partition
- [dask.dataframe.DataFrame.merge](generated/dask.dataframe.DataFrame.merge.html.md): Merge the DataFrame with another DataFrame
- [dask.dataframe.DataFrame.min](generated/dask.dataframe.DataFrame.min.html.md): Return the minimum of the values over the requested axis.
- [dask.dataframe.DataFrame.mod](generated/dask.dataframe.DataFrame.mod.html.md): Page content
- [dask.dataframe.DataFrame.mode](generated/dask.dataframe.DataFrame.mode.html.md): Get the mode(s) of each element along the selected axis.
- [dask.dataframe.DataFrame.mul](generated/dask.dataframe.DataFrame.mul.html.md): Page content
- [dask.dataframe.DataFrame.ndim](generated/dask.dataframe.DataFrame.ndim.html.md): Return dimensionality
- [dask.dataframe.DataFrame.ne](generated/dask.dataframe.DataFrame.ne.html.md): Page content
- [dask.dataframe.DataFrame.nlargest](generated/dask.dataframe.DataFrame.nlargest.html.md): Return the first n rows ordered by columns in descending order.
- [dask.dataframe.DataFrame.npartitions](generated/dask.dataframe.DataFrame.npartitions.html.md): Return number of partitions
- [dask.dataframe.DataFrame.nsmallest](generated/dask.dataframe.DataFrame.nsmallest.html.md): Return the first n rows ordered by columns in ascending order.
- [dask.dataframe.DataFrame.partitions](generated/dask.dataframe.DataFrame.partitions.html.md): Slice dataframe by partitions
- [dask.dataframe.DataFrame.persist](generated/dask.dataframe.DataFrame.persist.html.md): Persist this dask collection into memory
- [dask.dataframe.DataFrame.pivot_table](generated/dask.dataframe.DataFrame.pivot_table.html.md): Create a spreadsheet-style pivot table as a DataFrame. Target `columns`
- [dask.dataframe.DataFrame.pop](generated/dask.dataframe.DataFrame.pop.html.md): Return item and drop it from DataFrame. Raise KeyError if not found.
- [dask.dataframe.DataFrame.pow](generated/dask.dataframe.DataFrame.pow.html.md): Page content
- [dask.dataframe.DataFrame.prod](generated/dask.dataframe.DataFrame.prod.html.md): Return the product of the values over the requested axis.
- [dask.dataframe.DataFrame.quantile](generated/dask.dataframe.DataFrame.quantile.html.md): Approximate row-wise and precise column-wise quantiles of DataFrame
- [dask.dataframe.DataFrame.query](generated/dask.dataframe.DataFrame.query.html.md): Filter dataframe with complex expression
- [dask.dataframe.DataFrame.radd](generated/dask.dataframe.DataFrame.radd.html.md): Page content
- [dask.dataframe.DataFrame.random_split](generated/dask.dataframe.DataFrame.random_split.html.md): Pseudorandomly split dataframe into different pieces row-wise
- [dask.dataframe.DataFrame.rdiv](generated/dask.dataframe.DataFrame.rdiv.html.md): Page content
- [dask.dataframe.DataFrame.rename](generated/dask.dataframe.DataFrame.rename.html.md): Rename columns or index labels.
- [dask.dataframe.DataFrame.rename_axis](generated/dask.dataframe.DataFrame.rename_axis.html.md): Set the name of the axis for the index or columns.
- [dask.dataframe.DataFrame.repartition](generated/dask.dataframe.DataFrame.repartition.html.md): Repartition a collection
- [dask.dataframe.DataFrame.replace](generated/dask.dataframe.DataFrame.replace.html.md): Replace values given in to_replace with value.
- [dask.dataframe.DataFrame.resample](generated/dask.dataframe.DataFrame.resample.html.md): Resample time-series data.
- [dask.dataframe.DataFrame.reset_index](generated/dask.dataframe.DataFrame.reset_index.html.md): Reset the index to the default index.
- [dask.dataframe.DataFrame.rfloordiv](generated/dask.dataframe.DataFrame.rfloordiv.html.md): Page content
- [dask.dataframe.DataFrame.rmod](generated/dask.dataframe.DataFrame.rmod.html.md): Page content
- [dask.dataframe.DataFrame.rmul](generated/dask.dataframe.DataFrame.rmul.html.md): Page content
- [dask.dataframe.DataFrame.rolling](generated/dask.dataframe.DataFrame.rolling.html.md): Provides rolling transformations.
- [dask.dataframe.DataFrame.round](generated/dask.dataframe.DataFrame.round.html.md): Round numeric columns in a DataFrame to a variable number of decimal places.
- [dask.dataframe.DataFrame.rpow](generated/dask.dataframe.DataFrame.rpow.html.md): Page content
- [dask.dataframe.DataFrame.rsub](generated/dask.dataframe.DataFrame.rsub.html.md): Page content
- [dask.dataframe.DataFrame.rtruediv](generated/dask.dataframe.DataFrame.rtruediv.html.md): Page content
- [dask.dataframe.DataFrame.sample](generated/dask.dataframe.DataFrame.sample.html.md): Random sample of items
- [dask.dataframe.DataFrame.select_dtypes](generated/dask.dataframe.DataFrame.select_dtypes.html.md): Return a subset of the DataFrame’s columns based on the column dtypes.
- [dask.dataframe.DataFrame.sem](generated/dask.dataframe.DataFrame.sem.html.md): Return unbiased standard error of the mean over requested axis.
- [dask.dataframe.DataFrame.set_index](generated/dask.dataframe.DataFrame.set_index.html.md): Set the DataFrame index (row labels) using an existing column.
- [dask.dataframe.DataFrame.shape](generated/dask.dataframe.DataFrame.shape.html.md): Page content
- [dask.dataframe.DataFrame.shuffle](generated/dask.dataframe.DataFrame.shuffle.html.md): Rearrange DataFrame into new partitions
- [dask.dataframe.DataFrame.size](generated/dask.dataframe.DataFrame.size.html.md): Size of the Series or DataFrame as a Delayed object.
- [dask.dataframe.DataFrame.sort_values](generated/dask.dataframe.DataFrame.sort_values.html.md): Sort the dataset by a single column.
- [dask.dataframe.DataFrame.squeeze](generated/dask.dataframe.DataFrame.squeeze.html.md): Squeeze 1 dimensional axis objects into scalars.
- [dask.dataframe.DataFrame.std](generated/dask.dataframe.DataFrame.std.html.md): Return sample standard deviation over requested axis.
- [dask.dataframe.DataFrame.sub](generated/dask.dataframe.DataFrame.sub.html.md): Page content
- [dask.dataframe.DataFrame.sum](generated/dask.dataframe.DataFrame.sum.html.md): Return the sum of the values over the requested axis.
- [dask.dataframe.DataFrame.tail](generated/dask.dataframe.DataFrame.tail.html.md): Last n rows of the dataset
- [dask.dataframe.DataFrame.to_backend](generated/dask.dataframe.DataFrame.to_backend.html.md): Move to a new DataFrame backend
- [dask.dataframe.DataFrame.to_bag](generated/dask.dataframe.DataFrame.to_bag.html.md): Create a Dask Bag from a Series
- [dask.dataframe.DataFrame.to_csv](generated/dask.dataframe.DataFrame.to_csv.html.md): See dd.to_csv docstring for more information
- [dask.dataframe.DataFrame.to_dask_array](generated/dask.dataframe.DataFrame.to_dask_array.html.md): Convert a dask DataFrame to a dask array.
- [dask.dataframe.DataFrame.to_delayed](generated/dask.dataframe.DataFrame.to_delayed.html.md): Convert into a list of `dask.delayed` objects, one per partition.
- [dask.dataframe.DataFrame.to_hdf](generated/dask.dataframe.DataFrame.to_hdf.html.md): See dd.to_hdf docstring for more information
- [dask.dataframe.DataFrame.to_html](generated/dask.dataframe.DataFrame.to_html.html.md): Render a DataFrame as an HTML table.
- [dask.dataframe.DataFrame.to_json](generated/dask.dataframe.DataFrame.to_json.html.md): See dd.to_json docstring for more information
- [dask.dataframe.DataFrame.to_orc](generated/dask.dataframe.DataFrame.to_orc.html.md): See dd.to_orc docstring for more information
- [dask.dataframe.DataFrame.to_parquet](generated/dask.dataframe.DataFrame.to_parquet.html.md): Page content
- [dask.dataframe.DataFrame.to_records](generated/dask.dataframe.DataFrame.to_records.html.md): Page content
- [dask.dataframe.DataFrame.to_sql](generated/dask.dataframe.DataFrame.to_sql.html.md): Page content
- [dask.dataframe.DataFrame.to_string](generated/dask.dataframe.DataFrame.to_string.html.md): Render a DataFrame to a console-friendly tabular output.
- [dask.dataframe.DataFrame.to_timestamp](generated/dask.dataframe.DataFrame.to_timestamp.html.md): Cast PeriodIndex to DatetimeIndex of timestamps, at *beginning* of period.
- [dask.dataframe.DataFrame.truediv](generated/dask.dataframe.DataFrame.truediv.html.md): Page content
- [dask.dataframe.DataFrame.values](generated/dask.dataframe.DataFrame.values.html.md): Return a dask.array of the values of this dataframe
- [dask.dataframe.DataFrame.var](generated/dask.dataframe.DataFrame.var.html.md): Return unbiased variance over requested axis.
- [dask.dataframe.DataFrame.visualize](generated/dask.dataframe.DataFrame.visualize.html.md): Visualize the expression or task graph
- [dask.dataframe.DataFrame.where](generated/dask.dataframe.DataFrame.where.html.md): Replace values where the condition is False.
- [dask.dataframe.Index.add](generated/dask.dataframe.Index.add.html.md): Page content
- [dask.dataframe.Index.align](generated/dask.dataframe.Index.align.html.md): Align two objects on their axes with the specified join method.
- [dask.dataframe.Index.all](generated/dask.dataframe.Index.all.html.md): Return whether all elements are True, potentially over an axis.
- [dask.dataframe.Index.any](generated/dask.dataframe.Index.any.html.md): Return whether any element is True, potentially over an axis.
- [dask.dataframe.Index.apply](generated/dask.dataframe.Index.apply.html.md): Parallel version of pandas.Series.apply
- [dask.dataframe.Index.astype](generated/dask.dataframe.Index.astype.html.md): Cast a pandas object to a specified dtype `dtype`.
- [dask.dataframe.Index.autocorr](generated/dask.dataframe.Index.autocorr.html.md): Compute the lag-N autocorrelation.
- [dask.dataframe.Index.between](generated/dask.dataframe.Index.between.html.md): Return boolean Series equivalent to left <= series <= right.
- [dask.dataframe.Index.bfill](generated/dask.dataframe.Index.bfill.html.md): Fill NA/NaN values by using the next valid observation to fill the gap.
- [dask.dataframe.Index.clear_divisions](generated/dask.dataframe.Index.clear_divisions.html.md): Forget division information.
- [dask.dataframe.Index.clip](generated/dask.dataframe.Index.clip.html.md): Trim values at input threshold(s).
- [dask.dataframe.Index.compute](generated/dask.dataframe.Index.compute.html.md): Compute this dask collection
- [dask.dataframe.Index.copy](generated/dask.dataframe.Index.copy.html.md): Make a copy of the dataframe
- [dask.dataframe.Index.corr](generated/dask.dataframe.Index.corr.html.md): Compute correlation with other Series, excluding missing values.
- [dask.dataframe.Index.count](generated/dask.dataframe.Index.count.html.md): Count non-NA cells for each column or row.
- [dask.dataframe.Index.cov](generated/dask.dataframe.Index.cov.html.md): Compute covariance with Series, excluding missing values.
- [dask.dataframe.Index.cummax](generated/dask.dataframe.Index.cummax.html.md): Return cumulative maximum over a DataFrame or Series axis.
- [dask.dataframe.Index.cummin](generated/dask.dataframe.Index.cummin.html.md): Return cumulative minimum over a DataFrame or Series axis.
- [dask.dataframe.Index.cumprod](generated/dask.dataframe.Index.cumprod.html.md): Return cumulative product over a DataFrame or Series axis.
- [dask.dataframe.Index.cumsum](generated/dask.dataframe.Index.cumsum.html.md): Return cumulative sum over a DataFrame or Series axis.
- [dask.dataframe.Index.describe](generated/dask.dataframe.Index.describe.html.md): Generate descriptive statistics.
- [dask.dataframe.Index.diff](generated/dask.dataframe.Index.diff.html.md): First discrete difference of element.
- [dask.dataframe.Index.div](generated/dask.dataframe.Index.div.html.md): Page content
- [dask.dataframe.Index.drop_duplicates](generated/dask.dataframe.Index.drop_duplicates.html.md): Page content
- [dask.dataframe.Index.dropna](generated/dask.dataframe.Index.dropna.html.md): Return a new Series with missing values removed.
- [dask.dataframe.Index.dtype](generated/dask.dataframe.Index.dtype.html.md): Page content
- [dask.dataframe.Index.eq](generated/dask.dataframe.Index.eq.html.md): Page content
- [dask.dataframe.Index.explode](generated/dask.dataframe.Index.explode.html.md): Transform each element of a list-like to a row.
- [dask.dataframe.Index.ffill](generated/dask.dataframe.Index.ffill.html.md): Fill NA/NaN values by propagating the last valid observation to next valid.
- [dask.dataframe.Index.fillna](generated/dask.dataframe.Index.fillna.html.md): Fill NA/NaN values with value.
- [dask.dataframe.Index.floordiv](generated/dask.dataframe.Index.floordiv.html.md): Page content
- [dask.dataframe.Index.ge](generated/dask.dataframe.Index.ge.html.md): Page content
- [dask.dataframe.Index.get_partition](generated/dask.dataframe.Index.get_partition.html.md): Get a dask DataFrame/Series representing the nth partition.
- [dask.dataframe.Index.groupby](generated/dask.dataframe.Index.groupby.html.md): Group Series using a mapper or by a Series of columns.
- [dask.dataframe.Index.gt](generated/dask.dataframe.Index.gt.html.md): Page content
- [dask.dataframe.Index.head](generated/dask.dataframe.Index.head.html.md): First n rows of the dataset
- [dask.dataframe.Index](generated/dask.dataframe.Index.html.md): Index-like Expr Collection.
- [dask.dataframe.Index.is_monotonic_decreasing](generated/dask.dataframe.Index.is_monotonic_decreasing.html.md): Return True if values in the object are monotonically decreasing.
- [dask.dataframe.Index.is_monotonic_increasing](generated/dask.dataframe.Index.is_monotonic_increasing.html.md): Return True if values in the object are monotonically increasing.
- [dask.dataframe.Index.isin](generated/dask.dataframe.Index.isin.html.md): Whether each element in the DataFrame is contained in values.
- [dask.dataframe.Index.isna](generated/dask.dataframe.Index.isna.html.md): Detect missing values.
- [dask.dataframe.Index.isnull](generated/dask.dataframe.Index.isnull.html.md): DataFrame.isnull is an alias for DataFrame.isna.
- [dask.dataframe.Index.known_divisions](generated/dask.dataframe.Index.known_divisions.html.md): Whether the divisions are known.
- [dask.dataframe.Index.le](generated/dask.dataframe.Index.le.html.md): Page content
- [dask.dataframe.Index.loc](generated/dask.dataframe.Index.loc.html.md): Purely label-location based indexer for selection by label.
- [dask.dataframe.Index.lt](generated/dask.dataframe.Index.lt.html.md): Page content
- [dask.dataframe.Index.map](generated/dask.dataframe.Index.map.html.md): Map values using an input mapping or function.
- [dask.dataframe.Index.map_overlap](generated/dask.dataframe.Index.map_overlap.html.md): Apply a function to each partition, sharing rows with adjacent partitions.
- [dask.dataframe.Index.map_partitions](generated/dask.dataframe.Index.map_partitions.html.md): Apply a Python function to each partition
- [dask.dataframe.Index.mask](generated/dask.dataframe.Index.mask.html.md): Replace values where the condition is True.
- [dask.dataframe.Index.max](generated/dask.dataframe.Index.max.html.md): Return the maximum of the values over the requested axis.
- [dask.dataframe.Index.median](generated/dask.dataframe.Index.median.html.md): Return the median of the values over the requested axis.
- [dask.dataframe.Index.median_approximate](generated/dask.dataframe.Index.median_approximate.html.md): Return the approximate median of the values over the requested axis.
- [dask.dataframe.Index.memory_usage](generated/dask.dataframe.Index.memory_usage.html.md): Memory usage of the values.
- [dask.dataframe.Index.memory_usage_per_partition](generated/dask.dataframe.Index.memory_usage_per_partition.html.md): Return the memory usage of each partition
- [dask.dataframe.Index.min](generated/dask.dataframe.Index.min.html.md): Return the minimum of the values over the requested axis.
- [dask.dataframe.Index.mod](generated/dask.dataframe.Index.mod.html.md): Page content
- [dask.dataframe.Index.mul](generated/dask.dataframe.Index.mul.html.md): Page content
- [dask.dataframe.Index.nbytes](generated/dask.dataframe.Index.nbytes.html.md): Number of bytes
- [dask.dataframe.Index.ndim](generated/dask.dataframe.Index.ndim.html.md): Return dimensionality
- [dask.dataframe.Index.ne](generated/dask.dataframe.Index.ne.html.md): Page content
- [dask.dataframe.Index.nlargest](generated/dask.dataframe.Index.nlargest.html.md): Return the largest n elements.
- [dask.dataframe.Index.notnull](generated/dask.dataframe.Index.notnull.html.md): DataFrame.notnull is an alias for DataFrame.notna.
- [dask.dataframe.Index.nsmallest](generated/dask.dataframe.Index.nsmallest.html.md): Return the smallest n elements.
- [dask.dataframe.Index.nunique](generated/dask.dataframe.Index.nunique.html.md): Return number of unique elements in the object.
- [dask.dataframe.Index.nunique_approx](generated/dask.dataframe.Index.nunique_approx.html.md): Approximate number of unique rows.
- [dask.dataframe.Index.persist](generated/dask.dataframe.Index.persist.html.md): Persist this dask collection into memory
- [dask.dataframe.Index.pipe](generated/dask.dataframe.Index.pipe.html.md): Apply chainable functions that expect Series or DataFrames.
- [dask.dataframe.Index.pow](generated/dask.dataframe.Index.pow.html.md): Page content
- [dask.dataframe.Index.quantile](generated/dask.dataframe.Index.quantile.html.md): Approximate quantiles of Series
- [dask.dataframe.Index.radd](generated/dask.dataframe.Index.radd.html.md): Page content
- [dask.dataframe.Index.random_split](generated/dask.dataframe.Index.random_split.html.md): Pseudorandomly split dataframe into different pieces row-wise
- [dask.dataframe.Index.rdiv](generated/dask.dataframe.Index.rdiv.html.md): Page content
- [dask.dataframe.Index.rename](generated/dask.dataframe.Index.rename.html.md): Alter Series index labels or name
- [dask.dataframe.Index.repartition](generated/dask.dataframe.Index.repartition.html.md): Repartition a collection
- [dask.dataframe.Index.replace](generated/dask.dataframe.Index.replace.html.md): Replace values given in to_replace with value.
- [dask.dataframe.Index.resample](generated/dask.dataframe.Index.resample.html.md): Resample time-series data.
- [dask.dataframe.Index.reset_index](generated/dask.dataframe.Index.reset_index.html.md): Reset the index to the default index.
- [dask.dataframe.Index.rolling](generated/dask.dataframe.Index.rolling.html.md): Provides rolling transformations.
- [dask.dataframe.Index.round](generated/dask.dataframe.Index.round.html.md): Round numeric columns in a DataFrame to a variable number of decimal places.
- [dask.dataframe.Index.sample](generated/dask.dataframe.Index.sample.html.md): Random sample of items
- [dask.dataframe.Index.sem](generated/dask.dataframe.Index.sem.html.md): Return unbiased standard error of the mean over requested axis.
- [dask.dataframe.Index.shape](generated/dask.dataframe.Index.shape.html.md): Return a tuple representing the dimensionality of the DataFrame.
- [dask.dataframe.Index.shift](generated/dask.dataframe.Index.shift.html.md): Shift index by desired number of periods with an optional time freq.
- [dask.dataframe.Index.size](generated/dask.dataframe.Index.size.html.md): Size of the Series or DataFrame as a Delayed object.
- [dask.dataframe.Index.sub](generated/dask.dataframe.Index.sub.html.md): Page content
- [dask.dataframe.Index.to_backend](generated/dask.dataframe.Index.to_backend.html.md): Move to a new DataFrame backend
- [dask.dataframe.Index.to_bag](generated/dask.dataframe.Index.to_bag.html.md): Create a Dask Bag from a Series
- [dask.dataframe.Index.to_csv](generated/dask.dataframe.Index.to_csv.html.md): See dd.to_csv docstring for more information
- [dask.dataframe.Index.to_dask_array](generated/dask.dataframe.Index.to_dask_array.html.md): Convert a dask DataFrame to a dask array.
- [dask.dataframe.Index.to_delayed](generated/dask.dataframe.Index.to_delayed.html.md): Convert into a list of `dask.delayed` objects, one per partition.
- [dask.dataframe.Index.to_frame](generated/dask.dataframe.Index.to_frame.html.md): Create a DataFrame with a column containing the Index.
- [dask.dataframe.Index.to_hdf](generated/dask.dataframe.Index.to_hdf.html.md): See dd.to_hdf docstring for more information
- [dask.dataframe.Index.to_series](generated/dask.dataframe.Index.to_series.html.md): Create a Series with both index and values equal to the index keys.
- [dask.dataframe.Index.to_string](generated/dask.dataframe.Index.to_string.html.md): Render a string representation of the Series.
- [dask.dataframe.Index.to_timestamp](generated/dask.dataframe.Index.to_timestamp.html.md): Cast PeriodIndex to DatetimeIndex of timestamps, at *beginning* of period.
- [dask.dataframe.Index.truediv](generated/dask.dataframe.Index.truediv.html.md): Page content
- [dask.dataframe.Index.unique](generated/dask.dataframe.Index.unique.html.md): Return Series of unique values in the object. Includes NA values.
- [dask.dataframe.Index.value_counts](generated/dask.dataframe.Index.value_counts.html.md): Return a Series containing counts of unique values.
- [dask.dataframe.Index.values](generated/dask.dataframe.Index.values.html.md): Return a dask.array of the values of this dataframe
- [dask.dataframe.Index.visualize](generated/dask.dataframe.Index.visualize.html.md): Visualize the expression or task graph
- [dask.dataframe.Index.where](generated/dask.dataframe.Index.where.html.md): Replace values where the condition is False.
- [dask.dataframe.Series.add](generated/dask.dataframe.Series.add.html.md): Page content
- [dask.dataframe.Series.align](generated/dask.dataframe.Series.align.html.md): Align two objects on their axes with the specified join method.
- [dask.dataframe.Series.all](generated/dask.dataframe.Series.all.html.md): Return whether all elements are True, potentially over an axis.
- [dask.dataframe.Series.any](generated/dask.dataframe.Series.any.html.md): Return whether any element is True, potentially over an axis.
- [dask.dataframe.Series.apply](generated/dask.dataframe.Series.apply.html.md): Parallel version of pandas.Series.apply
- [dask.dataframe.Series.astype](generated/dask.dataframe.Series.astype.html.md): Cast a pandas object to a specified dtype `dtype`.
- [dask.dataframe.Series.autocorr](generated/dask.dataframe.Series.autocorr.html.md): Compute the lag-N autocorrelation.
- [dask.dataframe.Series.between](generated/dask.dataframe.Series.between.html.md): Return boolean Series equivalent to left <= series <= right.
- [dask.dataframe.Series.bfill](generated/dask.dataframe.Series.bfill.html.md): Fill NA/NaN values by using the next valid observation to fill the gap.
- [dask.dataframe.Series.cat.add_categories](generated/dask.dataframe.Series.cat.add_categories.html.md): Add new categories.
- [dask.dataframe.Series.cat.as_known](generated/dask.dataframe.Series.cat.as_known.html.md): Ensure the categories in this series are known.
- [dask.dataframe.Series.cat.as_ordered](generated/dask.dataframe.Series.cat.as_ordered.html.md): Set the Categorical to be ordered.
- [dask.dataframe.Series.cat.as_unknown](generated/dask.dataframe.Series.cat.as_unknown.html.md): Ensure the categories in this series are unknown
- [dask.dataframe.Series.cat.as_unordered](generated/dask.dataframe.Series.cat.as_unordered.html.md): Set the Categorical to be unordered.
- [dask.dataframe.Series.cat.categories](generated/dask.dataframe.Series.cat.categories.html.md): The categories of this categorical.
- [dask.dataframe.Series.cat.codes](generated/dask.dataframe.Series.cat.codes.html.md): The codes of this categorical.
- [dask.dataframe.Series.cat.known](generated/dask.dataframe.Series.cat.known.html.md): Whether the categories are fully known
- [dask.dataframe.Series.cat.ordered](generated/dask.dataframe.Series.cat.ordered.html.md): Whether the categories have an ordered relationship
- [dask.dataframe.Series.cat.remove_categories](generated/dask.dataframe.Series.cat.remove_categories.html.md): Remove the specified categories.
- [dask.dataframe.Series.cat.remove_unused_categories](generated/dask.dataframe.Series.cat.remove_unused_categories.html.md): Removes categories which are not used
- [dask.dataframe.Series.cat.rename_categories](generated/dask.dataframe.Series.cat.rename_categories.html.md): Rename categories.
- [dask.dataframe.Series.cat.reorder_categories](generated/dask.dataframe.Series.cat.reorder_categories.html.md): Reorder categories as specified in new_categories.
- [dask.dataframe.Series.cat.set_categories](generated/dask.dataframe.Series.cat.set_categories.html.md): Set the categories to the specified new categories.
- [dask.dataframe.Series.clear_divisions](generated/dask.dataframe.Series.clear_divisions.html.md): Forget division information.
- [dask.dataframe.Series.clip](generated/dask.dataframe.Series.clip.html.md): Trim values at input threshold(s).
- [dask.dataframe.Series.compute](generated/dask.dataframe.Series.compute.html.md): Compute this dask collection
- [dask.dataframe.Series.copy](generated/dask.dataframe.Series.copy.html.md): Make a copy of the dataframe
- [dask.dataframe.Series.corr](generated/dask.dataframe.Series.corr.html.md): Compute correlation with other Series, excluding missing values.
- [dask.dataframe.Series.count](generated/dask.dataframe.Series.count.html.md): Count non-NA cells for each column or row.
- [dask.dataframe.Series.cov](generated/dask.dataframe.Series.cov.html.md): Compute covariance with Series, excluding missing values.
- [dask.dataframe.Series.cummax](generated/dask.dataframe.Series.cummax.html.md): Return cumulative maximum over a DataFrame or Series axis.
- [dask.dataframe.Series.cummin](generated/dask.dataframe.Series.cummin.html.md): Return cumulative minimum over a DataFrame or Series axis.
- [dask.dataframe.Series.cumprod](generated/dask.dataframe.Series.cumprod.html.md): Return cumulative product over a DataFrame or Series axis.
- [dask.dataframe.Series.cumsum](generated/dask.dataframe.Series.cumsum.html.md): Return cumulative sum over a DataFrame or Series axis.
- [dask.dataframe.Series.describe](generated/dask.dataframe.Series.describe.html.md): Generate descriptive statistics.
- [dask.dataframe.Series.diff](generated/dask.dataframe.Series.diff.html.md): First discrete difference of element.
- [dask.dataframe.Series.div](generated/dask.dataframe.Series.div.html.md): Page content
- [dask.dataframe.Series.drop_duplicates](generated/dask.dataframe.Series.drop_duplicates.html.md): Page content
- [dask.dataframe.Series.dropna](generated/dask.dataframe.Series.dropna.html.md): Return a new Series with missing values removed.
- [dask.dataframe.Series.dt.ceil](generated/dask.dataframe.Series.dt.ceil.html.md): Perform ceil operation on the data to the specified freq.
- [dask.dataframe.Series.dt.date](generated/dask.dataframe.Series.dt.date.html.md): Returns numpy array of python [`datetime.date`](https://docs.python.org/3/library/datetime.html#date...
- [dask.dataframe.Series.dt.day](generated/dask.dataframe.Series.dt.day.html.md): The day of the datetime.
- [dask.dataframe.Series.dt.day_of_week](generated/dask.dataframe.Series.dt.day_of_week.html.md): The day of the week with Monday=0, Sunday=6.
- [dask.dataframe.Series.dt.day_of_year](generated/dask.dataframe.Series.dt.day_of_year.html.md): The ordinal day of the year.
- [dask.dataframe.Series.dt.dayofweek](generated/dask.dataframe.Series.dt.dayofweek.html.md): The day of the week with Monday=0, Sunday=6.
- [dask.dataframe.Series.dt.dayofyear](generated/dask.dataframe.Series.dt.dayofyear.html.md): The ordinal day of the year.
- [dask.dataframe.Series.dt.days_in_month](generated/dask.dataframe.Series.dt.days_in_month.html.md): The number of days in the month.
- [dask.dataframe.Series.dt.daysinmonth](generated/dask.dataframe.Series.dt.daysinmonth.html.md): The number of days in the month.
- [dask.dataframe.Series.dt.floor](generated/dask.dataframe.Series.dt.floor.html.md): Perform floor operation on the data to the specified freq.
- [dask.dataframe.Series.dt.freq](generated/dask.dataframe.Series.dt.freq.html.md): Tries to return a string representing a frequency generated by infer_freq.
- [dask.dataframe.Series.dt.hour](generated/dask.dataframe.Series.dt.hour.html.md): The hours of the datetime.
- [dask.dataframe.Series.dt.is_leap_year](generated/dask.dataframe.Series.dt.is_leap_year.html.md): Boolean indicator if the date belongs to a leap year.
- [dask.dataframe.Series.dt.is_month_end](generated/dask.dataframe.Series.dt.is_month_end.html.md): Indicates whether the date is the last day of the month.
- [dask.dataframe.Series.dt.is_month_start](generated/dask.dataframe.Series.dt.is_month_start.html.md): Indicates whether the date is the first day of the month.
- [dask.dataframe.Series.dt.is_quarter_end](generated/dask.dataframe.Series.dt.is_quarter_end.html.md): Indicator for whether the date is the last day of a quarter.
- [dask.dataframe.Series.dt.is_quarter_start](generated/dask.dataframe.Series.dt.is_quarter_start.html.md): Indicator for whether the date is the first day of a quarter.
- [dask.dataframe.Series.dt.is_year_end](generated/dask.dataframe.Series.dt.is_year_end.html.md): Indicate whether the date is the last day of the year.
- [dask.dataframe.Series.dt.is_year_start](generated/dask.dataframe.Series.dt.is_year_start.html.md): Indicate whether the date is the first day of a year.
- [dask.dataframe.Series.dt.isocalendar](generated/dask.dataframe.Series.dt.isocalendar.html.md): Calculate year, week, and day according to the ISO 8601 standard.
- [dask.dataframe.Series.dt.microsecond](generated/dask.dataframe.Series.dt.microsecond.html.md): The microseconds of the datetime.
- [dask.dataframe.Series.dt.minute](generated/dask.dataframe.Series.dt.minute.html.md): The minutes of the datetime.
- [dask.dataframe.Series.dt.month](generated/dask.dataframe.Series.dt.month.html.md): The month as January=1, December=12.
- [dask.dataframe.Series.dt.nanosecond](generated/dask.dataframe.Series.dt.nanosecond.html.md): The nanoseconds of the datetime.
- [dask.dataframe.Series.dt.normalize](generated/dask.dataframe.Series.dt.normalize.html.md): Convert times to midnight.
- [dask.dataframe.Series.dt.quarter](generated/dask.dataframe.Series.dt.quarter.html.md): The quarter of the date.
- [dask.dataframe.Series.dt.round](generated/dask.dataframe.Series.dt.round.html.md): Perform round operation on the data to the specified freq.
- [dask.dataframe.Series.dt.second](generated/dask.dataframe.Series.dt.second.html.md): The seconds of the datetime.
- [dask.dataframe.Series.dt.strftime](generated/dask.dataframe.Series.dt.strftime.html.md): Convert to Index using specified date_format.
- [dask.dataframe.Series.dt.time](generated/dask.dataframe.Series.dt.time.html.md): Returns numpy array of [`datetime.time`](https://docs.python.org/3/library/datetime.html#datetime.ti...
- [dask.dataframe.Series.dt.timetz](generated/dask.dataframe.Series.dt.timetz.html.md): Returns numpy array of [`datetime.time`](https://docs.python.org/3/library/datetime.html#datetime.ti...
- [dask.dataframe.Series.dt.tz](generated/dask.dataframe.Series.dt.tz.html.md): Return the timezone.
- [dask.dataframe.Series.dt.week](generated/dask.dataframe.Series.dt.week.html.md): The week ordinal of the year.
- [dask.dataframe.Series.dt.weekday](generated/dask.dataframe.Series.dt.weekday.html.md): The day of the week with Monday=0, Sunday=6.
- [dask.dataframe.Series.dt.weekofyear](generated/dask.dataframe.Series.dt.weekofyear.html.md): The week ordinal of the year.
- [dask.dataframe.Series.dt.year](generated/dask.dataframe.Series.dt.year.html.md): The year of the datetime.
- [dask.dataframe.Series.dtype](generated/dask.dataframe.Series.dtype.html.md): Page content
- [dask.dataframe.Series.eq](generated/dask.dataframe.Series.eq.html.md): Page content
- [dask.dataframe.Series.explode](generated/dask.dataframe.Series.explode.html.md): Transform each element of a list-like to a row.
- [dask.dataframe.Series.ffill](generated/dask.dataframe.Series.ffill.html.md): Fill NA/NaN values by propagating the last valid observation to next valid.
- [dask.dataframe.Series.fillna](generated/dask.dataframe.Series.fillna.html.md): Fill NA/NaN values with value.
- [dask.dataframe.Series.floordiv](generated/dask.dataframe.Series.floordiv.html.md): Page content
- [dask.dataframe.Series.ge](generated/dask.dataframe.Series.ge.html.md): Page content
- [dask.dataframe.Series.get_partition](generated/dask.dataframe.Series.get_partition.html.md): Get a dask DataFrame/Series representing the nth partition.
- [dask.dataframe.Series.groupby](generated/dask.dataframe.Series.groupby.html.md): Group Series using a mapper or by a Series of columns.
- [dask.dataframe.Series.gt](generated/dask.dataframe.Series.gt.html.md): Page content
- [dask.dataframe.Series.head](generated/dask.dataframe.Series.head.html.md): First n rows of the dataset
- [dask.dataframe.Series](generated/dask.dataframe.Series.html.md): Series-like Expr Collection.
- [dask.dataframe.Series.idxmax](generated/dask.dataframe.Series.idxmax.html.md): Return index of first occurrence of maximum over requested axis.
- [dask.dataframe.Series.idxmin](generated/dask.dataframe.Series.idxmin.html.md): Return index of first occurrence of minimum over requested axis.
- [dask.dataframe.Series.isin](generated/dask.dataframe.Series.isin.html.md): Whether each element in the DataFrame is contained in values.
- [dask.dataframe.Series.isna](generated/dask.dataframe.Series.isna.html.md): Detect missing values.
- [dask.dataframe.Series.isnull](generated/dask.dataframe.Series.isnull.html.md): DataFrame.isnull is an alias for DataFrame.isna.
- [dask.dataframe.Series.known_divisions](generated/dask.dataframe.Series.known_divisions.html.md): Whether the divisions are known.
- [dask.dataframe.Series.le](generated/dask.dataframe.Series.le.html.md): Page content
- [dask.dataframe.Series.loc](generated/dask.dataframe.Series.loc.html.md): Purely label-location based indexer for selection by label.
- [dask.dataframe.Series.lt](generated/dask.dataframe.Series.lt.html.md): Page content
- [dask.dataframe.Series.map](generated/dask.dataframe.Series.map.html.md): Map values of Series according to an input mapping or function.
- [dask.dataframe.Series.map_overlap](generated/dask.dataframe.Series.map_overlap.html.md): Apply a function to each partition, sharing rows with adjacent partitions.
- [dask.dataframe.Series.map_partitions](generated/dask.dataframe.Series.map_partitions.html.md): Apply a Python function to each partition
- [dask.dataframe.Series.mask](generated/dask.dataframe.Series.mask.html.md): Replace values where the condition is True.
- [dask.dataframe.Series.max](generated/dask.dataframe.Series.max.html.md): Return the maximum of the values over the requested axis.
- [dask.dataframe.Series.mean](generated/dask.dataframe.Series.mean.html.md): Return the mean of the values over the requested axis.
- [dask.dataframe.Series.median](generated/dask.dataframe.Series.median.html.md): Return the median of the values over the requested axis.
- [dask.dataframe.Series.median_approximate](generated/dask.dataframe.Series.median_approximate.html.md): Return the approximate median of the values over the requested axis.
- [dask.dataframe.Series.memory_usage](generated/dask.dataframe.Series.memory_usage.html.md): Return the memory usage of the Series.
- [dask.dataframe.Series.memory_usage_per_partition](generated/dask.dataframe.Series.memory_usage_per_partition.html.md): Return the memory usage of each partition
- [dask.dataframe.Series.min](generated/dask.dataframe.Series.min.html.md): Return the minimum of the values over the requested axis.
- [dask.dataframe.Series.mod](generated/dask.dataframe.Series.mod.html.md): Page content
- [dask.dataframe.Series.mul](generated/dask.dataframe.Series.mul.html.md): Page content
- [dask.dataframe.Series.nbytes](generated/dask.dataframe.Series.nbytes.html.md): Number of bytes
- [dask.dataframe.Series.ndim](generated/dask.dataframe.Series.ndim.html.md): Return dimensionality
- [dask.dataframe.Series.ne](generated/dask.dataframe.Series.ne.html.md): Page content
- [dask.dataframe.Series.nlargest](generated/dask.dataframe.Series.nlargest.html.md): Return the largest n elements.
- [dask.dataframe.Series.notnull](generated/dask.dataframe.Series.notnull.html.md): DataFrame.notnull is an alias for DataFrame.notna.
- [dask.dataframe.Series.nsmallest](generated/dask.dataframe.Series.nsmallest.html.md): Return the smallest n elements.
- [dask.dataframe.Series.nunique](generated/dask.dataframe.Series.nunique.html.md): Return number of unique elements in the object.
- [dask.dataframe.Series.nunique_approx](generated/dask.dataframe.Series.nunique_approx.html.md): Approximate number of unique rows.
- [dask.dataframe.Series.persist](generated/dask.dataframe.Series.persist.html.md): Persist this dask collection into memory
- [dask.dataframe.Series.pipe](generated/dask.dataframe.Series.pipe.html.md): Apply chainable functions that expect Series or DataFrames.
- [dask.dataframe.Series.pow](generated/dask.dataframe.Series.pow.html.md): Page content
- [dask.dataframe.Series.prod](generated/dask.dataframe.Series.prod.html.md): Return the product of the values over the requested axis.
- [dask.dataframe.Series.quantile](generated/dask.dataframe.Series.quantile.html.md): Approximate quantiles of Series
- [dask.dataframe.Series.radd](generated/dask.dataframe.Series.radd.html.md): Page content
- [dask.dataframe.Series.random_split](generated/dask.dataframe.Series.random_split.html.md): Pseudorandomly split dataframe into different pieces row-wise
- [dask.dataframe.Series.rdiv](generated/dask.dataframe.Series.rdiv.html.md): Page content
- [dask.dataframe.Series.rename](generated/dask.dataframe.Series.rename.html.md): Alter Series index labels or name
- [dask.dataframe.Series.repartition](generated/dask.dataframe.Series.repartition.html.md): Repartition a collection
- [dask.dataframe.Series.replace](generated/dask.dataframe.Series.replace.html.md): Replace values given in to_replace with value.
- [dask.dataframe.Series.resample](generated/dask.dataframe.Series.resample.html.md): Resample time-series data.
- [dask.dataframe.Series.reset_index](generated/dask.dataframe.Series.reset_index.html.md): Reset the index to the default index.
- [dask.dataframe.Series.rolling](generated/dask.dataframe.Series.rolling.html.md): Provides rolling transformations.
- [dask.dataframe.Series.round](generated/dask.dataframe.Series.round.html.md): Round numeric columns in a DataFrame to a variable number of decimal places.
- [dask.dataframe.Series.sample](generated/dask.dataframe.Series.sample.html.md): Random sample of items
- [dask.dataframe.Series.sem](generated/dask.dataframe.Series.sem.html.md): Return unbiased standard error of the mean over requested axis.
- [dask.dataframe.Series.shape](generated/dask.dataframe.Series.shape.html.md): Return a tuple representing the dimensionality of the DataFrame.
- [dask.dataframe.Series.shift](generated/dask.dataframe.Series.shift.html.md): Shift index by desired number of periods with an optional time freq.
- [dask.dataframe.Series.size](generated/dask.dataframe.Series.size.html.md): Size of the Series or DataFrame as a Delayed object.
- [dask.dataframe.Series.std](generated/dask.dataframe.Series.std.html.md): Return sample standard deviation over requested axis.
- [dask.dataframe.Series.str.capitalize](generated/dask.dataframe.Series.str.capitalize.html.md): Convert strings in the Series/Index to be capitalized.
- [dask.dataframe.Series.str.casefold](generated/dask.dataframe.Series.str.casefold.html.md): Convert strings in the Series/Index to be casefolded.
- [dask.dataframe.Series.str.cat](generated/dask.dataframe.Series.str.cat.html.md): Page content
- [dask.dataframe.Series.str.center](generated/dask.dataframe.Series.str.center.html.md): Pad left and right side of strings in the Series/Index.
- [dask.dataframe.Series.str.contains](generated/dask.dataframe.Series.str.contains.html.md): Test if pattern or regex is contained within a string of a Series or Index.
- [dask.dataframe.Series.str.count](generated/dask.dataframe.Series.str.count.html.md): Count occurrences of pattern in each string of the Series/Index.
- [dask.dataframe.Series.str.decode](generated/dask.dataframe.Series.str.decode.html.md): Decode character string in the Series/Index using indicated encoding.
- [dask.dataframe.Series.str.encode](generated/dask.dataframe.Series.str.encode.html.md): Encode character string in the Series/Index using indicated encoding.
- [dask.dataframe.Series.str.endswith](generated/dask.dataframe.Series.str.endswith.html.md): Test if the end of each string element matches a pattern.
- [dask.dataframe.Series.str.extract](generated/dask.dataframe.Series.str.extract.html.md): Extract capture groups in the regex pat as columns in a DataFrame.
- [dask.dataframe.Series.str.extractall](generated/dask.dataframe.Series.str.extractall.html.md): Extract capture groups in the regex pat as columns in DataFrame.
- [dask.dataframe.Series.str.find](generated/dask.dataframe.Series.str.find.html.md): Return lowest indexes in each strings in the Series/Index.
- [dask.dataframe.Series.str.findall](generated/dask.dataframe.Series.str.findall.html.md): Find all occurrences of pattern or regular expression in the Series/Index.
- [dask.dataframe.Series.str.fullmatch](generated/dask.dataframe.Series.str.fullmatch.html.md): Determine if each string entirely matches a regular expression.
- [dask.dataframe.Series.str.get](generated/dask.dataframe.Series.str.get.html.md): Extract element from each component at specified position or with specified key.
- [dask.dataframe.Series.str.index](generated/dask.dataframe.Series.str.index.html.md): Return lowest indexes in each string in Series/Index.
- [dask.dataframe.Series.str.isalnum](generated/dask.dataframe.Series.str.isalnum.html.md): Check whether all characters in each string are alphanumeric.
- [dask.dataframe.Series.str.isalpha](generated/dask.dataframe.Series.str.isalpha.html.md): Check whether all characters in each string are alphabetic.
- [dask.dataframe.Series.str.isdecimal](generated/dask.dataframe.Series.str.isdecimal.html.md): Check whether all characters in each string are decimal.
- [dask.dataframe.Series.str.isdigit](generated/dask.dataframe.Series.str.isdigit.html.md): Check whether all characters in each string are digits.
- [dask.dataframe.Series.str.islower](generated/dask.dataframe.Series.str.islower.html.md): Check whether all characters in each string are lowercase.
- [dask.dataframe.Series.str.isnumeric](generated/dask.dataframe.Series.str.isnumeric.html.md): Check whether all characters in each string are numeric.
- [dask.dataframe.Series.str.isspace](generated/dask.dataframe.Series.str.isspace.html.md): Check whether all characters in each string are whitespace.
- [dask.dataframe.Series.str.istitle](generated/dask.dataframe.Series.str.istitle.html.md): Check whether all characters in each string are titlecase.
- [dask.dataframe.Series.str.isupper](generated/dask.dataframe.Series.str.isupper.html.md): Check whether all characters in each string are uppercase.
- [dask.dataframe.Series.str.join](generated/dask.dataframe.Series.str.join.html.md): Join lists contained as elements in the Series/Index with passed delimiter.
- [dask.dataframe.Series.str.len](generated/dask.dataframe.Series.str.len.html.md): Compute the length of each element in the Series/Index.
- [dask.dataframe.Series.str.ljust](generated/dask.dataframe.Series.str.ljust.html.md): Pad right side of strings in the Series/Index.
- [dask.dataframe.Series.str.lower](generated/dask.dataframe.Series.str.lower.html.md): Convert strings in the Series/Index to lowercase.
- [dask.dataframe.Series.str.lstrip](generated/dask.dataframe.Series.str.lstrip.html.md): Remove leading characters.
- [dask.dataframe.Series.str.match](generated/dask.dataframe.Series.str.match.html.md): Determine if each string starts with a match of a regular expression.
- [dask.dataframe.Series.str.normalize](generated/dask.dataframe.Series.str.normalize.html.md): Return the Unicode normal form for the strings in the Series/Index.
- [dask.dataframe.Series.str.pad](generated/dask.dataframe.Series.str.pad.html.md): Pad strings in the Series/Index up to width.
- [dask.dataframe.Series.str.partition](generated/dask.dataframe.Series.str.partition.html.md): Split the string at the first occurrence of sep.
- [dask.dataframe.Series.str.repeat](generated/dask.dataframe.Series.str.repeat.html.md): Duplicate each string in the Series or Index.
- [dask.dataframe.Series.str.replace](generated/dask.dataframe.Series.str.replace.html.md): Replace each occurrence of pattern/regex in the Series/Index.
- [dask.dataframe.Series.str.rfind](generated/dask.dataframe.Series.str.rfind.html.md): Return highest indexes in each strings in the Series/Index.
- [dask.dataframe.Series.str.rindex](generated/dask.dataframe.Series.str.rindex.html.md): Return highest indexes in each string in Series/Index.
- [dask.dataframe.Series.str.rjust](generated/dask.dataframe.Series.str.rjust.html.md): Pad left side of strings in the Series/Index.
- [dask.dataframe.Series.str.rpartition](generated/dask.dataframe.Series.str.rpartition.html.md): Split the string at the last occurrence of sep.
- [dask.dataframe.Series.str.rsplit](generated/dask.dataframe.Series.str.rsplit.html.md): Page content
- [dask.dataframe.Series.str.rstrip](generated/dask.dataframe.Series.str.rstrip.html.md): Remove trailing characters.
- [dask.dataframe.Series.str.slice](generated/dask.dataframe.Series.str.slice.html.md): Slice substrings from each element in the Series or Index.
- [dask.dataframe.Series.str.split](generated/dask.dataframe.Series.str.split.html.md): Known inconsistencies: `expand=True` with unknown `n` will raise a `NotImplementedError`.
- [dask.dataframe.Series.str.startswith](generated/dask.dataframe.Series.str.startswith.html.md): Test if the start of each string element matches a pattern.
- [dask.dataframe.Series.str.strip](generated/dask.dataframe.Series.str.strip.html.md): Remove leading and trailing characters.
- [dask.dataframe.Series.str.swapcase](generated/dask.dataframe.Series.str.swapcase.html.md): Convert strings in the Series/Index to be swapcased.
- [dask.dataframe.Series.str.title](generated/dask.dataframe.Series.str.title.html.md): Convert strings in the Series/Index to titlecase.
- [dask.dataframe.Series.str.translate](generated/dask.dataframe.Series.str.translate.html.md): Map all characters in the string through the given mapping table.
- [dask.dataframe.Series.str.upper](generated/dask.dataframe.Series.str.upper.html.md): Convert strings in the Series/Index to uppercase.
- [dask.dataframe.Series.str.wrap](generated/dask.dataframe.Series.str.wrap.html.md): Wrap strings in Series/Index at specified line width.
- [dask.dataframe.Series.str.zfill](generated/dask.dataframe.Series.str.zfill.html.md): Pad strings in the Series/Index by prepending ‘0’ characters.
- [dask.dataframe.Series.sub](generated/dask.dataframe.Series.sub.html.md): Page content
- [dask.dataframe.Series.sum](generated/dask.dataframe.Series.sum.html.md): Return the sum of the values over the requested axis.
- [dask.dataframe.Series.to_backend](generated/dask.dataframe.Series.to_backend.html.md): Move to a new DataFrame backend
- [dask.dataframe.Series.to_bag](generated/dask.dataframe.Series.to_bag.html.md): Create a Dask Bag from a Series
- [dask.dataframe.Series.to_csv](generated/dask.dataframe.Series.to_csv.html.md): See dd.to_csv docstring for more information
- [dask.dataframe.Series.to_dask_array](generated/dask.dataframe.Series.to_dask_array.html.md): Convert a dask DataFrame to a dask array.
- [dask.dataframe.Series.to_delayed](generated/dask.dataframe.Series.to_delayed.html.md): Convert into a list of `dask.delayed` objects, one per partition.
- [dask.dataframe.Series.to_frame](generated/dask.dataframe.Series.to_frame.html.md): Convert Series to DataFrame.
- [dask.dataframe.Series.to_hdf](generated/dask.dataframe.Series.to_hdf.html.md): See dd.to_hdf docstring for more information
- [dask.dataframe.Series.to_string](generated/dask.dataframe.Series.to_string.html.md): Render a string representation of the Series.
- [dask.dataframe.Series.to_timestamp](generated/dask.dataframe.Series.to_timestamp.html.md): Cast PeriodIndex to DatetimeIndex of timestamps, at *beginning* of period.
- [dask.dataframe.Series.truediv](generated/dask.dataframe.Series.truediv.html.md): Page content
- [dask.dataframe.Series.unique](generated/dask.dataframe.Series.unique.html.md): Return Series of unique values in the object. Includes NA values.
- [dask.dataframe.Series.value_counts](generated/dask.dataframe.Series.value_counts.html.md): Return a Series containing counts of unique values.
- [dask.dataframe.Series.values](generated/dask.dataframe.Series.values.html.md): Return a dask.array of the values of this dataframe
- [dask.dataframe.Series.var](generated/dask.dataframe.Series.var.html.md): Return unbiased variance over requested axis.
- [dask.dataframe.Series.visualize](generated/dask.dataframe.Series.visualize.html.md): Visualize the expression or task graph
- [dask.dataframe.Series.where](generated/dask.dataframe.Series.where.html.md): Replace values where the condition is False.
- [dask.dataframe.api.GroupBy.aggregate](generated/dask.dataframe.api.GroupBy.aggregate.html.md): Aggregate using one or more specified operations
- [dask.dataframe.api.GroupBy.apply](generated/dask.dataframe.api.GroupBy.apply.html.md): Parallel version of pandas GroupBy.apply
- [dask.dataframe.api.GroupBy.bfill](generated/dask.dataframe.api.GroupBy.bfill.html.md): Backward fill the values.
- [dask.dataframe.api.GroupBy.corr](generated/dask.dataframe.api.GroupBy.corr.html.md): Compute pairwise correlation of columns, excluding NA/null values.
- [dask.dataframe.api.GroupBy.count](generated/dask.dataframe.api.GroupBy.count.html.md): Compute count of group, excluding missing values.
- [dask.dataframe.api.GroupBy.cov](generated/dask.dataframe.api.GroupBy.cov.html.md): Compute pairwise covariance of columns, excluding NA/null values.
- [dask.dataframe.api.GroupBy.cumcount](generated/dask.dataframe.api.GroupBy.cumcount.html.md): Number each item in each group from 0 to the length of that group - 1.
- [dask.dataframe.api.GroupBy.cumprod](generated/dask.dataframe.api.GroupBy.cumprod.html.md): Cumulative product for each group.
- [dask.dataframe.api.GroupBy.cumsum](generated/dask.dataframe.api.GroupBy.cumsum.html.md): Cumulative sum for each group.
- [dask.dataframe.api.GroupBy.ffill](generated/dask.dataframe.api.GroupBy.ffill.html.md): Forward fill the values.
- [dask.dataframe.api.GroupBy.first](generated/dask.dataframe.api.GroupBy.first.html.md): Compute the first entry of each column within each group.
- [dask.dataframe.api.GroupBy.get_group](generated/dask.dataframe.api.GroupBy.get_group.html.md): Construct DataFrame from group with provided name.
- [dask.dataframe.api.GroupBy.idxmax](generated/dask.dataframe.api.GroupBy.idxmax.html.md): Return index of first occurrence of maximum over requested axis.
- [dask.dataframe.api.GroupBy.idxmin](generated/dask.dataframe.api.GroupBy.idxmin.html.md): Return index of first occurrence of minimum over requested axis.
- [dask.dataframe.api.GroupBy.last](generated/dask.dataframe.api.GroupBy.last.html.md): Compute the last entry of each column within each group.
- [dask.dataframe.api.GroupBy.max](generated/dask.dataframe.api.GroupBy.max.html.md): Compute max of group values.
- [dask.dataframe.api.GroupBy.mean](generated/dask.dataframe.api.GroupBy.mean.html.md): Compute mean of groups, excluding missing values.
- [dask.dataframe.api.GroupBy.min](generated/dask.dataframe.api.GroupBy.min.html.md): Compute min of group values.
- [dask.dataframe.api.GroupBy.rolling](generated/dask.dataframe.api.GroupBy.rolling.html.md): Provides rolling transformations.
- [dask.dataframe.api.GroupBy.size](generated/dask.dataframe.api.GroupBy.size.html.md): Compute group sizes.
- [dask.dataframe.api.GroupBy.std](generated/dask.dataframe.api.GroupBy.std.html.md): Compute standard deviation of groups, excluding missing values.
- [dask.dataframe.api.GroupBy.sum](generated/dask.dataframe.api.GroupBy.sum.html.md): Compute sum of group values.
- [dask.dataframe.api.GroupBy.transform](generated/dask.dataframe.api.GroupBy.transform.html.md): Parallel version of pandas GroupBy.transform
- [dask.dataframe.api.GroupBy.var](generated/dask.dataframe.api.GroupBy.var.html.md): Compute variance of groups, excluding missing values.
- [dask.dataframe.api.Rolling.apply](generated/dask.dataframe.api.Rolling.apply.html.md): Calculate the rolling custom aggregation function.
- [dask.dataframe.api.Rolling.count](generated/dask.dataframe.api.Rolling.count.html.md): Calculate the rolling count of non NaN observations.
- [dask.dataframe.api.Rolling.kurt](generated/dask.dataframe.api.Rolling.kurt.html.md): Calculate the rolling Fisher’s definition of kurtosis without bias.
- [dask.dataframe.api.Rolling.max](generated/dask.dataframe.api.Rolling.max.html.md): Calculate the rolling maximum.
- [dask.dataframe.api.Rolling.mean](generated/dask.dataframe.api.Rolling.mean.html.md): Calculate the rolling mean.
- [dask.dataframe.api.Rolling.median](generated/dask.dataframe.api.Rolling.median.html.md): Calculate the rolling median.
- [dask.dataframe.api.Rolling.min](generated/dask.dataframe.api.Rolling.min.html.md): Calculate the rolling minimum.
- [dask.dataframe.api.Rolling.quantile](generated/dask.dataframe.api.Rolling.quantile.html.md): Calculate the rolling quantile.
- [dask.dataframe.api.Rolling.skew](generated/dask.dataframe.api.Rolling.skew.html.md): Calculate the rolling unbiased skewness.
- [dask.dataframe.api.Rolling.std](generated/dask.dataframe.api.Rolling.std.html.md): Calculate the rolling standard deviation.
- [dask.dataframe.api.Rolling.sum](generated/dask.dataframe.api.Rolling.sum.html.md): Calculate the rolling sum.
- [dask.dataframe.api.Rolling.var](generated/dask.dataframe.api.Rolling.var.html.md): Calculate the rolling variance.
- [dask.dataframe.api.SeriesGroupBy.aggregate](generated/dask.dataframe.api.SeriesGroupBy.aggregate.html.md): Aggregate using one or more specified operations
- [dask.dataframe.api.SeriesGroupBy.apply](generated/dask.dataframe.api.SeriesGroupBy.apply.html.md): Parallel version of pandas GroupBy.apply
- [dask.dataframe.api.SeriesGroupBy.bfill](generated/dask.dataframe.api.SeriesGroupBy.bfill.html.md): Backward fill the values.
- [dask.dataframe.api.SeriesGroupBy.count](generated/dask.dataframe.api.SeriesGroupBy.count.html.md): Compute count of group, excluding missing values.
- [dask.dataframe.api.SeriesGroupBy.cumcount](generated/dask.dataframe.api.SeriesGroupBy.cumcount.html.md): Number each item in each group from 0 to the length of that group - 1.
- [dask.dataframe.api.SeriesGroupBy.cumprod](generated/dask.dataframe.api.SeriesGroupBy.cumprod.html.md): Cumulative product for each group.
- [dask.dataframe.api.SeriesGroupBy.cumsum](generated/dask.dataframe.api.SeriesGroupBy.cumsum.html.md): Cumulative sum for each group.
- [dask.dataframe.api.SeriesGroupBy.ffill](generated/dask.dataframe.api.SeriesGroupBy.ffill.html.md): Forward fill the values.
- [dask.dataframe.api.SeriesGroupBy.first](generated/dask.dataframe.api.SeriesGroupBy.first.html.md): Compute the first entry of each column within each group.
- [dask.dataframe.api.SeriesGroupBy.get_group](generated/dask.dataframe.api.SeriesGroupBy.get_group.html.md): Construct DataFrame from group with provided name.
- [dask.dataframe.api.SeriesGroupBy.idxmax](generated/dask.dataframe.api.SeriesGroupBy.idxmax.html.md): Return index of first occurrence of maximum over requested axis.
- [dask.dataframe.api.SeriesGroupBy.idxmin](generated/dask.dataframe.api.SeriesGroupBy.idxmin.html.md): Return index of first occurrence of minimum over requested axis.
- [dask.dataframe.api.SeriesGroupBy.last](generated/dask.dataframe.api.SeriesGroupBy.last.html.md): Compute the last entry of each column within each group.
- [dask.dataframe.api.SeriesGroupBy.max](generated/dask.dataframe.api.SeriesGroupBy.max.html.md): Compute max of group values.
- [dask.dataframe.api.SeriesGroupBy.mean](generated/dask.dataframe.api.SeriesGroupBy.mean.html.md): Compute mean of groups, excluding missing values.
- [dask.dataframe.api.SeriesGroupBy.min](generated/dask.dataframe.api.SeriesGroupBy.min.html.md): Compute min of group values.
- [dask.dataframe.api.SeriesGroupBy.nunique](generated/dask.dataframe.api.SeriesGroupBy.nunique.html.md): Return number of unique elements in the group.
- [dask.dataframe.api.SeriesGroupBy.rolling](generated/dask.dataframe.api.SeriesGroupBy.rolling.html.md): Provides rolling transformations.
- [dask.dataframe.api.SeriesGroupBy.size](generated/dask.dataframe.api.SeriesGroupBy.size.html.md): Compute group sizes.
- [dask.dataframe.api.SeriesGroupBy.std](generated/dask.dataframe.api.SeriesGroupBy.std.html.md): Compute standard deviation of groups, excluding missing values.
- [dask.dataframe.api.SeriesGroupBy.sum](generated/dask.dataframe.api.SeriesGroupBy.sum.html.md): Compute sum of group values.
- [dask.dataframe.api.SeriesGroupBy.transform](generated/dask.dataframe.api.SeriesGroupBy.transform.html.md): Parallel version of pandas GroupBy.transform
- [dask.dataframe.api.SeriesGroupBy.var](generated/dask.dataframe.api.SeriesGroupBy.var.html.md): Compute variance of groups, excluding missing values.
- [dask.dataframe.compute](generated/dask.dataframe.compute.html.md): Compute several dask collections at once.
- [dask.dataframe.concat](generated/dask.dataframe.concat.html.md): Concatenate DataFrames along rows.
- [dask.dataframe.from_array](generated/dask.dataframe.from_array.html.md): Read any sliceable array into a Dask Dataframe
- [dask.dataframe.from_dask_array](generated/dask.dataframe.from_dask_array.html.md): Create a Dask DataFrame from a Dask Array.
- [dask.dataframe.from_delayed](generated/dask.dataframe.from_delayed.html.md): Create Dask DataFrame from many Dask Delayed objects
- [dask.dataframe.from_map](generated/dask.dataframe.from_map.html.md): Create a DataFrame collection from a custom function map.
- [dask.dataframe.from_pandas](generated/dask.dataframe.from_pandas.html.md): Construct a Dask DataFrame from a Pandas DataFrame
- [dask.dataframe.get_dummies](generated/dask.dataframe.get_dummies.html.md): Convert categorical variable into dummy/indicator variables.
- [dask.dataframe.map_overlap](generated/dask.dataframe.map_overlap.html.md): Apply a function to each partition, sharing rows with adjacent partitions.
- [dask.dataframe.map_partitions](generated/dask.dataframe.map_partitions.html.md): Apply Python function on each DataFrame partition.
- [dask.dataframe.melt](generated/dask.dataframe.melt.html.md): Page content
- [dask.dataframe.merge](generated/dask.dataframe.merge.html.md): Merge DataFrame or named Series objects with a database-style join.
- [dask.dataframe.merge_asof](generated/dask.dataframe.merge_asof.html.md): Perform a merge by key distance.
- [dask.dataframe.pivot_table](generated/dask.dataframe.pivot_table.html.md): Create a spreadsheet-style pivot table as a DataFrame. Target `columns`
- [dask.dataframe.read_csv](generated/dask.dataframe.read_csv.html.md): Read CSV files into a Dask.DataFrame
- [dask.dataframe.read_fwf](generated/dask.dataframe.read_fwf.html.md): Read fixed-width files into a Dask.DataFrame
- [dask.dataframe.read_hdf](generated/dask.dataframe.read_hdf.html.md): Read HDF files into a Dask DataFrame
- [dask.dataframe.read_json](generated/dask.dataframe.read_json.html.md): Create a dataframe from a set of JSON files
- [dask.dataframe.read_orc](generated/dask.dataframe.read_orc.html.md): Read dataframe from ORC file(s)
- [dask.dataframe.read_parquet](generated/dask.dataframe.read_parquet.html.md): Read a Parquet file into a Dask DataFrame
- [dask.dataframe.read_sql](generated/dask.dataframe.read_sql.html.md): Read SQL query or database table into a DataFrame.
- [dask.dataframe.read_sql_query](generated/dask.dataframe.read_sql_query.html.md): Read SQL query into a DataFrame.
- [dask.dataframe.read_sql_table](generated/dask.dataframe.read_sql_table.html.md): Read SQL database table into a DataFrame.
- [dask.dataframe.read_table](generated/dask.dataframe.read_table.html.md): Read delimited files into a Dask.DataFrame
- [dask.dataframe.to_csv](generated/dask.dataframe.to_csv.html.md): Store Dask DataFrame to CSV files
- [dask.dataframe.to_datetime](generated/dask.dataframe.to_datetime.html.md): Convert argument to datetime.
- [dask.dataframe.to_hdf](generated/dask.dataframe.to_hdf.html.md): Store Dask Dataframe to Hierarchical Data Format (HDF) files
- [dask.dataframe.to_json](generated/dask.dataframe.to_json.html.md): Write dataframe into JSON text files
- [dask.dataframe.to_numeric](generated/dask.dataframe.to_numeric.html.md): Convert argument to a numeric type.
- [dask.dataframe.to_orc](generated/dask.dataframe.to_orc.html.md): Store Dask.dataframe to ORC files
- [dask.dataframe.to_parquet](generated/dask.dataframe.to_parquet.html.md): Store Dask.dataframe to Parquet files
- [dask.dataframe.to_records](generated/dask.dataframe.to_records.html.md): Create Dask Array from a Dask Dataframe
- [dask.dataframe.to_sql](generated/dask.dataframe.to_sql.html.md): Store Dask Dataframe to a SQL table
- [dask.dataframe.to_timedelta](generated/dask.dataframe.to_timedelta.html.md): Convert argument to timedelta.
- [dask.dataframe.tseries.resample.Resampler.agg](generated/dask.dataframe.tseries.resample.Resampler.agg.html.md): Aggregate using one or more operations over the specified axis.
- [dask.dataframe.tseries.resample.Resampler.count](generated/dask.dataframe.tseries.resample.Resampler.count.html.md): Compute count of group, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.first](generated/dask.dataframe.tseries.resample.Resampler.first.html.md): Compute the first non-null entry of each column.
- [dask.dataframe.tseries.resample.Resampler](generated/dask.dataframe.tseries.resample.Resampler.html.md): Aggregate using one or more operations
- [dask.dataframe.tseries.resample.Resampler.last](generated/dask.dataframe.tseries.resample.Resampler.last.html.md): Compute the last non-null entry of each column.
- [dask.dataframe.tseries.resample.Resampler.max](generated/dask.dataframe.tseries.resample.Resampler.max.html.md): Compute max value of group.
- [dask.dataframe.tseries.resample.Resampler.mean](generated/dask.dataframe.tseries.resample.Resampler.mean.html.md): Compute mean of groups, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.median](generated/dask.dataframe.tseries.resample.Resampler.median.html.md): Compute median of groups, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.min](generated/dask.dataframe.tseries.resample.Resampler.min.html.md): Compute min value of group.
- [dask.dataframe.tseries.resample.Resampler.nunique](generated/dask.dataframe.tseries.resample.Resampler.nunique.html.md): Return number of unique elements in the group.
- [dask.dataframe.tseries.resample.Resampler.ohlc](generated/dask.dataframe.tseries.resample.Resampler.ohlc.html.md): Compute open, high, low and close values of a group, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.prod](generated/dask.dataframe.tseries.resample.Resampler.prod.html.md): Compute prod of group values.
- [dask.dataframe.tseries.resample.Resampler.quantile](generated/dask.dataframe.tseries.resample.Resampler.quantile.html.md): Return value at the given quantile.
- [dask.dataframe.tseries.resample.Resampler.sem](generated/dask.dataframe.tseries.resample.Resampler.sem.html.md): Compute standard error of the mean of groups, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.size](generated/dask.dataframe.tseries.resample.Resampler.size.html.md): Compute group sizes.
- [dask.dataframe.tseries.resample.Resampler.std](generated/dask.dataframe.tseries.resample.Resampler.std.html.md): Compute standard deviation of groups, excluding missing values.
- [dask.dataframe.tseries.resample.Resampler.sum](generated/dask.dataframe.tseries.resample.Resampler.sum.html.md): Compute sum of group values.
- [dask.dataframe.tseries.resample.Resampler.var](generated/dask.dataframe.tseries.resample.Resampler.var.html.md): Compute variance of groups, excluding missing values.
- [dask.dataframe.utils.make_meta](generated/dask.dataframe.utils.make_meta.html.md): This method creates meta-data based on the type of `x`,
- [dask.tokenize.TokenizationError](generated/dask.tokenize.TokenizationError.html.md): Page content
- [dask.tokenize.tokenize](generated/dask.tokenize.tokenize.html.md): Deterministic token
- [Dask DataFrame API with Logical Query Planning](dataframe-api.html.md): | [`DataFrame`](generated/dask.dataframe.DataFrame.md#dask.dataframe.DataFrame)(expr)               ...
- [Dask DataFrames Best Practices](dataframe-best-practices.html.md): Suggestions for Dask DataFrames best practices and solutions to common problems.
- [Categoricals](dataframe-categoricals.html.md): Dask DataFrame divides [categorical data](https://pandas.pydata.org/pandas-docs/stable/categorical.h...
- [Load and Save Data with Dask DataFrames](dataframe-create.html.md): Learn how to create DataFrames and store them. Create a Dask DataFrame from various data storage formats like CSV, HDF, Apache Parquet, and others.
- [Dask DataFrame Design](dataframe-design.html.md): Dask DataFrames coordinate many Pandas DataFrames/Series arranged along an
- [Extending DataFrames](dataframe-extend.html.md): There are a few projects that subclass or replicate the functionality of Pandas
- [Additional Information](dataframe-extra.html.md): * [Parquet](dataframe-parquet.md)
- [Shuffling Performance](dataframe-groupby.html.md): Operations like `groupby`, `join`, and `set_index` have special
- [Using Hive Partitioning with Dask](dataframe-hive.html.md): It is sometimes useful to write your dataset with a hive-like directory scheme.
- [Indexing into Dask DataFrames](dataframe-indexing.html.md): Dask DataFrame supports some of Pandas’ indexing behavior.
- [Joins](dataframe-joins.html.md): DataFrame joins are a common and expensive computation that benefit from a
- [Optimizer](dataframe-optimizer.html.md): Dask DataFrame supports Query Planning since version 2024.03.0
- [Dask Dataframe and Parquet](dataframe-parquet.html.md): [Parquet](https://parquet.apache.org/) is a popular, columnar file format designed for efficient dat...
- [Dask Dataframe and SQL](dataframe-sql.html.md): SQL is a method for executing tabular computation on database servers.
- [Dask DataFrame](dataframe.html.md): A Dask DataFrame is a large parallel DataFrame composed of many smaller pandas DataFrames, split along the index. These pandas DataFrames may live on disk for larger-than-memory computing on a single machine, or on many different machines in a cluster.
- [Debug](how-to/debug.html.md): Debugging parallel programs is hard.  Normal debugging tools like logging and
- [Debugging and Performance](debugging-performance.html.md): This section contains resources to help you debug and understand performance.
- [API](delayed-api.html.md): The `dask.delayed` interface consists of one function, `delayed`:
- [Best Practices](delayed-best-practices.html.md): It is easy to get started with Dask delayed, but using it *well* does require
- [Working with Collections](delayed-collections.html.md): Often we want to do a bit of custom work with `dask.delayed` (for example,
- [Dask Delayed](delayed.html.md): The Dask delayed function decorates your functions so that they operate lazily. Rather than executing your function immediately, it will defer execution, placing the function and its arguments into a task graph.
- [Command Line](deploying-cli.html.md): This is the most fundamental way to deploy Dask on multiple machines.  In
- [Cloud](deploying-cloud.html.md): There are a variety of ways to deploy Dask on the cloud.
- [Docker Images](deploying-docker.html.md): Example docker images are maintained at [https://github.com/dask/dask-docker](https://github.com/das...
- [Additional Information](deploying-extra.html.md): * [Adaptive deployments](adaptive.md)
- [High Performance Computers](deploying-hpc.html.md): This page includes instructions and guidelines when deploying Dask on high
- [Kubernetes](deploying-kubernetes.html.md): [Kubernetes](https://kubernetes.io/) is a popular system for deploying distributed applications on c...
- [Python API (advanced)](deploying-python-advanced.html.md): In some rare cases, experts may want to create `Scheduler`, `Worker`, and
- [Python API](deploying-python.html.md): You can create a `dask.distributed` scheduler by importing and creating a
- [SSH](deploying-ssh.html.md): It is easy to set up Dask on informally managed networks of machines using SSH.
- [Deploy Dask Clusters](deploying.html.md): Dask works well at many scales ranging from a single machine to clusters of
- [Deployment Considerations](deployment-considerations.html.md): Thanks to the efforts of the open-source community, there are tools to deploy Dask [pretty much anyw...
- [Development Guidelines](develop.html.md): Dask is a community maintained project.  We welcome contributions in the form
- [Diagnostics (distributed)](diagnostics-distributed.html.md): The [Dask distributed scheduler](scheduling.md) provides live feedback in two
- [Diagnostics (local)](diagnostics-local.html.md): Profiling parallel code can be challenging, but `dask.diagnostics` provides
- [Ecosystem](ecosystem.html.md): There are a number of open source projects that extend the Dask interface and provide different
- [Query planning with Expression system](expr-system-internals.html.md): This document is intended for Dask developers and contributors. It is not
- [Extend sizeof](how-to/extend-sizeof.html.md): When Dask needs to compute the size of an object in bytes, e.g. to determine which objects to spill ...
- [FAQ](faq.html.md): **Question**: *Is Dask appropriate for adoption within a larger institutional context?*
- [Futures](futures.html.md): Dask futures reimplements the Python futures API so you can scale your Python futures workflow across a Dask cluster.
- [GPUs](gpu.html.md): Dask works with GPUs in a few ways.
- [Advanced graph manipulation](graph_manipulation.html.md): There are some situations where computations with Dask collections will result in
- [Task Graphs](graphs.html.md): Internally, Dask encodes algorithms as task graphs which are typically expressed as dictionaries. Th...
- [Visualize task graphs](graphviz.html.md): | [`visualize`](api.md#dask.visualize)(\*args[, filename, traverse, ...])   | Visualize several dask...
- [High Level Graphs](high-level-graphs.html.md): Dask graphs produced by collections like Arrays, Bags, and DataFrames have
- [Dask Installation](install.html.md): Dask Installation | You can easily install Dask with conda or pip
- [Dask Internals](internals.html.md): This section is intended for contributors and power users who are interested in
- [Images and Logos](logos.html.md): Here are some commonly used Dask icons and logos
- [Maintainer Guidelines](maintainers.html.md): This page describes best practices for Dask maintainers.
- [Machine Learning](ml.html.md): Machine learning is a broad field involving many different workflows.  This
- [Optimization](optimize.html.md): Performance can be significantly improved in different contexts by making
- [Ordering](order.html.md): This is an advanced topic that most users won’t need to worry about.
- [Stages of Computation](phases-of-computation.html.md): This page describes all of the parts of computation, some common causes of
- [Talks & Tutorials](presentations.html.md): <iframe width="560"
- [Prometheus](prometheus.html.md): [Prometheus](https://prometheus.io) is a widely popular tool for monitoring and alerting a wide vari...
- [Scheduler Overview](scheduler-overview.html.md): After we create a dask graph, we use a scheduler to run it. Dask currently
- [Scheduling in Depth](scheduling-policy.html.md): *Note: this technical document is not optimized for user readability.*
- [Scheduling](scheduling.html.md): All of the large-scale Dask collections like
- [Selecting the collection backend](how-to/selecting-the-collection-backend.html.md): **Warning**: Backend-library dispatching at the collection level is still an experimental feature. B...
- [Shared Memory](shared.html.md): The asynchronous scheduler accepts any `concurrent.futures.Executor`
- [Manage Environments](software-environments.html.md): It is critical that each of your dask workers uses the same set of
- [Comparison to Spark](spark.html.md): [Apache Spark](https://spark.apache.org/) is a popular distributed computing
- [Specification](spec.html.md): Dask is a specification to encode a graph – specifically, a directed
- [Community](support.html.md): Dask is used and developed by individuals at a variety of institutions.  It
- [Understanding Performance](understanding-performance.html.md): The first step in making computations run quickly is to understand the costs involved.
- [User Interfaces](user-interfaces.html.md): Dask supports several user interfaces:
- [Why Dask?](why.html.md): This document gives high-level motivation on why people choose to adopt Dask.

---

For more comprehensive documentation, see [llms-full.txt](llms-full.txt)