# 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/


2025

## 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.
- [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): <a id="array-assignment"></a>
- [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): <a id="array-chunks"></a>
- [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): It is easy to get started with Dask’s APIs, but using them *well* requires some
- [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): <iframe width="560"
- [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): This docstring was copied from numpy.ma.core.empty_like.
- [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): This docstring was copied from scipy.stats.f_oneway.
- [dask.array.stats.kurtosis](generated/dask.array.stats.kurtosis.html.md): This docstring was copied from scipy.stats.kurtosis.
- [dask.array.stats.kurtosistest](generated/dask.array.stats.kurtosistest.html.md): This docstring was copied from scipy.stats.kurtosistest.
- [dask.array.stats.moment](generated/dask.array.stats.moment.html.md): This docstring was copied from scipy.stats.moment.
- [dask.array.stats.normaltest](generated/dask.array.stats.normaltest.html.md): This docstring was copied from scipy.stats.normaltest.
- [dask.array.stats.power_divergence](generated/dask.array.stats.power_divergence.html.md): This docstring was copied from scipy.stats.power_divergence.
- [dask.array.stats.skew](generated/dask.array.stats.skew.html.md): This docstring was copied from scipy.stats.skew.
- [dask.array.stats.skewtest](generated/dask.array.stats.skewtest.html.md): This docstring was copied from scipy.stats.skewtest.
- [dask.array.stats.ttest_1samp](generated/dask.array.stats.ttest_1samp.html.md): This docstring was copied from scipy.stats.ttest_1samp.
- [dask.array.stats.ttest_ind](generated/dask.array.stats.ttest_ind.html.md): This docstring was copied from scipy.stats.ttest_ind.
- [dask.array.stats.ttest_rel](generated/dask.array.stats.ttest_rel.html.md): This docstring was copied from scipy.stats.ttest_rel.
- [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 using the specified method.
- [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 a 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 from frame. 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 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 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 using the specified method.
- [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 boolean if values in the object are monotonically decreasing.
- [dask.dataframe.Index.is_monotonic_increasing](generated/dask.dataframe.Index.is_monotonic_increasing.html.md): Return boolean 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 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 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.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.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): Page content
- [dask.dataframe.Series.dt.hour](generated/dask.dataframe.Series.dt.hour.html.md): The hours of the datetime.
- [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 using the specified method.
- [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 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 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 entry of each column within each group.
- [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 entry of each column within each group.
- [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): <a id="dataframe-performance"></a>
- [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): You can create a Dask DataFrame from various data storage formats
- [Dask DataFrame Design](dataframe-design.html.md): <a id="dataframe-design"></a>
- [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): <a id="dataframe-hive"></a>
- [Indexing into Dask DataFrames](dataframe-indexing.html.md): <a id="dataframe-indexing"></a>
- [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): <a id="dataframe-parquet"></a>
- [Dask Dataframe and SQL](dataframe-sql.html.md): SQL is a method for executing tabular computation on database servers.
- [Dask DataFrame](dataframe.html.md): Dask DataFrame helps you process large tabular data by parallelizing pandas,
- [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): Sometimes problems don’t fit into one of the collections like `dask.array` or
- [Command Line](deploying-cli.html.md): <a id="deploying-cli"></a>
- [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 supports a real-time task framework that extends Python’s
- [GPUs](gpu.html.md): Dask works with GPUs in a few ways.
- [Advanced graph manipulation](graph_manipulation.html.md): <a id="graph-manipulation"></a>
- [Task Graphs](graphs.html.md): <a id="graphs"></a>
- [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): <a id="high-level-graphs"></a>
- [Dask Installation](install.html.md): You can install Dask with `conda`, with `pip`, or install from source.
- [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): <a id="optimization"></a>
- [Ordering](order.html.md): <a id="order"></a>
- [Stages of Computation](phases-of-computation.html.md): <a id="phases-of-computation"></a>
- [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): <a id="scheduling-policy"></a>
- [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 disptaching 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.