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docs: fix typos and style (macOS, conda-forge, combinations); update conda example; remove NBSP#7677

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10 changes: 5 additions & 5 deletionsREADME.md
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Expand Up@@ -48,15 +48,15 @@ In the GIFs below, Modin (left) and pandas (right) perform *the same pandas oper
</tbody>
</table>

The charts below show the speedup you get by replacing pandas with Modin based on the examples above. The example notebooks can be found [here](examples/jupyter). To learn more about the speedups you could get with Modin and try out some examples on your own, check out our [10-minute quickstart guide](https://modin.readthedocs.io/en/latest/getting_started/quickstart.html) to try out some examples on your own!
The charts below show the speedup you get by replacing pandas with Modin based on the examples above. The example notebooks can be found [here](examples/jupyter). To learn more about the speedups you could get with Modin and try out some examples on your own, check out our [10-minute quickstart guide](https://modin.readthedocs.io/en/latest/getting_started/quickstart.html).

<img src="https://github.com/modin-project/modin/raw/7c009c747caa90554607e30b9ac2bd1b190b8c7d/docs/img/Modin_Speedup.svg" style="display: block;margin-left: auto;margin-right: auto;" width="100%"></img>

### Installation

#### From PyPI

Modin can be installed with `pip` on Linux, Windows andMacOS:
Modin can be installed with `pip` on Linux, Windows andmacOS:

```bash
pip install "modin[all]" # (Recommended) Install Modin with Ray and Dask engines.
Expand DownExpand Up@@ -84,7 +84,7 @@ Modin automatically detects which engine(s) you have installed and uses that for

#### From conda-forge

Installing from [condaforge](https://github.com/conda-forge/modin-feedstock) using `modin-all`
Installing from [conda-forge](https://github.com/conda-forge/modin-feedstock) using `modin-all`
will install Modin and three engines: [Ray](https://github.com/ray-project/ray), [Dask](https://github.com/dask/dask) and
[MPI through unidist](https://github.com/modin-project/unidist).

Expand DownExpand Up@@ -114,7 +114,7 @@ To speed up conda installation we recommend using libmamba solver. To do this in
conda install -n base conda-libmamba-solver
```

and then use it duringistallation either like:
and then use it duringinstallation either like:

```bash
conda install -c conda-forge modin-ray --experimental-solver=libmamba
Expand DownExpand Up@@ -161,7 +161,7 @@ _Note: You should not change the engine after your first operation with Modin as

#### Which engine should I use?

On Linux,MacOS, and Windows you can install and use either Ray, Dask or MPI through unidist. There is no knowledge required
On Linux,macOS, and Windows you can install and use either Ray, Dask or MPI through unidist. There is no knowledge required
to use either of these engines as Modin abstracts away all of the complexity, so feel
free to pick either!

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2 changes: 1 addition & 1 deletiondocs/flow/modin/core/execution/dispatching.rst
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Expand Up@@ -8,7 +8,7 @@ Factories Module Description

Brief description
'''''''''''''''''
Modin has several execution engines and storage formats, combining themtogetherforms certain executions. 
Modinhas several executionengines and storage formats; combining them forms certain executions.
Calling any :py:class:`~modin.pandas.dataframe.DataFrame` API function will end up in some execution-specific method. The responsibility of dispatching high-level API calls to
execution-specific function belongs to the :ref:`QueryCompiler <query_compiler_def>`, which is determined at the time of the dataframe's creation by the factory of
the corresponding execution. The mission of this module is to route IO function calls from
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Expand Up@@ -27,7 +27,7 @@ the :py:class:`~modin.core.execution.ray.implementations.pandas_on_ray.dataframe
generic functionality from the ``GenericRayDataframe`` and the :py:class:`~modin.core.dataframe.pandas.dataframe.dataframe.PandasDataframe`.

..
TODO: insert a link to ``GenericRayDataframe`` once we add animplementatiton of the class
TODO: insert a link to ``GenericRayDataframe`` once we add animplementation of the class

PandasOnRay Dataframe implementation
------------------------------------
Expand DownExpand Up@@ -79,4 +79,4 @@ and a new query compiler with the data read is returned.
When writing data to a CSV file, for example, the :py:class:`~modin.core.execution.ray.implementations.pandas_on_ray.io.PandasOnRayIO` processes
the user query to execute it on Ray workers. Then, the :py:class:`~modin.core.execution.ray.implementations.pandas_on_ray.io.PandasOnRayIO` asks the
:py:class:`~modin.core.execution.ray.implementations.pandas_on_ray.dataframe.PandasOnRayDataframe` to decompose the data into row-wise partitions
that will be written into the file in parallel in Ray workers.
that will be written into the file in parallel in Ray workers.
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Expand Up@@ -28,7 +28,7 @@ the :py:class:`~modin.core.execution.unidist.implementations.pandas_on_unidist.d
generic functionality from the ``GenericUnidistDataframe`` and the :py:class:`~modin.core.dataframe.pandas.dataframe.dataframe.PandasDataframe`.

..
TODO: insert a link to ``GenericUnidistDataframe`` once we add animplementatiton of the class
TODO: insert a link to ``GenericUnidistDataframe`` once we add animplementation of the class

PandasOnUnidist Dataframe implementation
----------------------------------------
Expand DownExpand Up@@ -80,4 +80,4 @@ and a new query compiler with the data read is returned.
When writing data to a CSV file, for example, the :py:class:`~modin.core.execution.unidist.implementations.pandas_on_unidist.io.PandasOnUnidistIO` processes
the user query to execute it on Unidist workers. Then, the :py:class:`~modin.core.execution.unidist.implementations.pandas_on_unidist.io.PandasOnUnidistIO` asks the
:py:class:`~modin.core.execution.unidist.implementations.pandas_on_unidist.dataframe.PandasOnUnidistDataframe` to decompose the data into row-wise partitions
that will be written into the file in parallel in Unidist workers.
that will be written into the file in parallel in Unidist workers.
14 changes: 7 additions & 7 deletionsdocs/getting_started/installation.rst
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Expand Up@@ -17,7 +17,7 @@ Installing with pip
Stable version
""""""""""""""

Modin can be installed with ``pip`` on Linux, Windows andMacOS.
Modin can be installed with ``pip`` on Linux, Windows andmacOS.
To install the most recent stable release run the following:

.. code-block:: bash
Expand DownExpand Up@@ -96,7 +96,7 @@ Modin can be used with Google Colab_ via the ``pip`` command, by running the fol

!pip install "modin[all]"

Since Colab preloads several of Modin's dependencies by default, we need to restart the Colab environment once Modin is installed by either clicking on the :code:`"RESTART RUNTIME"` button in the installation output or byrun the following code:
Since Colab preloads several of Modin's dependencies by default, we need to restart the Colab environment once Modin is installed by either clicking on the :code:`"RESTART RUNTIME"` button in the installation output or byrunning the following code:

.. code-block:: python

Expand All@@ -120,13 +120,13 @@ it is possible to install modin with chosen engine(s) alongside. Current options
+---------------------------------+---------------------------+-----------------------------+
| **Package name in conda-forge** | **Engine(s)** | **Supported OSs** |
+---------------------------------+---------------------------+-----------------------------+
| modin | Dask_ | Linux, Windows,MacOS |
| modin | Dask_ | Linux, Windows,macOS |
+---------------------------------+---------------------------+-----------------------------+
| modin-dask | Dask | Linux, Windows,MacOS |
| modin-dask | Dask | Linux, Windows,macOS |
+---------------------------------+---------------------------+-----------------------------+
| modin-ray | Ray_ | Linux, Windows |
+---------------------------------+---------------------------+-----------------------------+
| modin-mpi | MPI_ through unidist_ | Linux, Windows,MacOS |
| modin-mpi | MPI_ through unidist_ | Linux, Windows,macOS |
+---------------------------------+---------------------------+-----------------------------+
| modin-all | Dask, Ray, Unidist | Linux |
+---------------------------------+---------------------------+-----------------------------+
Expand DownExpand Up@@ -156,7 +156,7 @@ or explicitly:
Refer to `Installing with conda`_ section of the unidist documentation
for more details on how to install a specific MPI implementation to run on.

``conda`` may be slow installing ``modin-all`` orcombitations of execution engines so we currently recommend using libmamba solver for the installation process.
``conda`` may be slow installing ``modin-all`` orcombinations of execution engines, so we currently recommend using the libmamba solver for the installation process.
To do this install it in a base environment:

.. code-block:: bash
Expand All@@ -167,7 +167,7 @@ Then it can be used during installation either like

.. code-block:: bash

conda install -c conda-forge modin-ray modin- --experimental-solver=libmamba
conda install -c conda-forge modin-ray modin-dask modin-mpi --experimental-solver=libmamba

or starting from conda 22.11 and libmamba solver 22.12 versions

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2 changes: 1 addition & 1 deletiondocs/release_notes/release_notes-0.16.0.rst
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Expand Up@@ -72,7 +72,7 @@ Key Features and Updates
* PERF-#4773: Compute `lengths` and `widths` in `put` method of Dask partition like Ray do (#4780)
* PERF-#4732: Avoid overwriting already-evaluated `PandasOnRayDataframePartition._length_cache` and `PandasOnRayDataframePartition._width_cache` (#4754)
* PERF-#4862: Don't call `compute_sliced_len.remote` when `row_labels/col_labels == slice(None)` (#4863)
* PERF-#4713: Stop overriding theray MacOS object store size limit (#4792)
* PERF-#4713: Stop overriding theRay macOS object store size limit (#4792)
* PERF-#4851: Compute `dtypes` for binary operations that can only return bool type and the right operand is not a Modin object (#4852)
* PERF-#4842: `copy` should not trigger any previous computations (#4843)
* PERF-#4849: Compute `dtypes` in `concat` also for ROW_WISE case when possible (#4850)
Expand Down
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