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DOCS-#6860: Add an ecosystem page to the docs #6861

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49 changes: 49 additions & 0 deletions docs/ecosystem.rst
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Ecosystem
=========

There is a constantly growing number of users and packages using pandas
to address their specific needs in data preparation, analysis and visualization.
pandas is being used ubiquitously and is a good choise to handle small-sized data.
However, pandas scales poorly and is non-interactive on moderate to large datasets.
Modin provides a drop-in replacement API for pandas and scales computation across nodes and
CPUs available. What you need to do to switch to Modin is just replace a single line of code.

.. code-block:: python

# import pandas as pd
import modin.pandas as pd

While most packages can consume a pandas DataFrame and operate it efficiently,
this is not the case with a Modin DataFrame due to its distributed nature.
Thus, some packages may lack support for handling Modin DataFrame(s) correctly and,
moreover, efficiently. Modin implements such methods as ``__array__``, ``__dataframe__``, etc.
to facilitate other libraries to consume a Modin DataFrame. If you feel that a certain library
can operate efficiently with a specific format of data, it is possible to convert a Modin DataFrame
to the format preferred.

to_pandas
---------

You can refer to `pandas ecosystem`_ page to get more details on
where pandas can be used and what libraries it powers.

.. code-block:: python

from modin.pandas.io import to_pandas

pandas_df = to_pandas(modin_df)

to_numpy
--------

You can refer to `NumPy ecosystem`_ section of NumPy documentation to get more details on
where NumPy can be used and what libraries it powers.

.. code-block:: python

from modin.pandas.io import to_numpy

numpy_arr = to_numpy(modin_df)

.. _pandas ecosystem: https://pandas.pydata.org/community/ecosystem.html
.. _NumPy ecosystem: https://numpy.org
1 change: 1 addition & 0 deletions docs/index.rst
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usage_guide/index
supported_apis/index
development/index
ecosystem
contact

.. raw:: html
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