DOCS-#3719: Improve documentation for pandas_on_python execution (#…

…3775)

Signed-off-by: Alexey Prutskov <alexey.prutskov@intel.com>

docs/flow/modin/core/execution/python/implementations/pandas_on_python/index.rst

@@ -1,5 +1,33 @@
+PandasOnPython Execution
+========================
+
+Queries that perform data transformation, data ingress or data egress using the `pandas on Python` execution
+pass through the Modin components detailed below.
+
+`pandas on Python` execution is sequential and it's used for the debug purposes. To enable `pandas on Python` execution,
+please refer to the usage section in :doc:`pandas on Python </UsingPandasonPython/index>`.
+
+Data Transformation
+'''''''''''''''''''
+
+.. image:: /img/pandas_on_python_data_transform.svg
+   :align: center
+
+When a user calls any :py:class:`~modin.pandas.dataframe.DataFrame` API, a query starts forming at the `API` layer
+to be executed at the `Execution` layer. The `API` layer is responsible for processing the query appropriately,
+for example, determining whether the final result should be a ``DataFrame`` or ``Series`` object. This layer is also responsible for sanitizing the input to the
+:py:class:`~modin.core.storage_formats.pandas.query_compiler.PandasQueryCompiler`, e.g. validating a parameter from the query
+and defining specific intermediate values to provide more context to the query compiler.
+The :py:class:`~modin.core.storage_formats.pandas.query_compiler.PandasQueryCompiler` is responsible for
+processing the query, received from the :py:class:`~modin.pandas.dataframe.DataFrame` `API` layer,
+to determine how to apply it to a subset of the data - either cell-wise or along an axis-wise partition backed by the `pandas`
+storage format. The :py:class:`~modin.core.storage_formats.pandas.query_compiler.PandasQueryCompiler` maps the query to one of the :doc:`Core Algebra Operators </flow/modin/core/dataframe/algebra>` of
+the :py:class:`~modin.core.execution.python.implementations.pandas_on_python.dataframe.dataframe.PandasOnPythonDataframe` which inherits
+generic functionality from the :py:class:`~modin.core.dataframe.pandas.dataframe.dataframe.PandasDataframe`.
+
+
 PandasOnPython Dataframe implementation
-=======================================
+---------------------------------------
 
 This page describes implementation of :doc:`Modin PandasDataframe Objects </flow/modin/core/dataframe/pandas/index>`
 specific for `PandasOnPython` execution. Since Python engine doesn't allow computation parallelization,
@@ -17,4 +45,32 @@ perfomance speed-up, so ``PandasOnPython`` is used for testing purposes only.
     dataframe
     partitioning/partition
     partitioning/axis_partition
-    partitioning/partition_manager
+    partitioning/partition_manager
+
+
+Data Ingress
+''''''''''''
+
+.. image:: /img/pandas_on_python_data_ingress.svg
+   :align: center
+
+Data Egress
+'''''''''''
+
+.. image:: /img/pandas_on_python_data_egress.svg
+   :align: center
+
+
+When a user calls any IO function from the ``modin.pandas.io`` module, the `API` layer queries the
+:py:class:`~modin.core.execution.dispatching.factories.dispatcher.FactoryDispatcher` which defines a factory specific for
+the execution, namely, the :py:class:`~modin.core.execution.dispatching.factories.factories.PandasOnPythonFactory`. The factory, in turn,
+exposes the :py:class:`~modin.core.execution.python.implementations.pandas_on_python.io.PandasOnPythonIO` class
+whose responsibility is a read/write from/to a file.
+
+When reading data from a CSV file, for example, the :py:class:`~modin.core.execution.python.implementations.pandas_on_python.io.io.PandasOnPythonIO` class
+reads the data using corresponding `pandas` function (``pandas.read_csv()`` in this case). After the reading is complete, a new query compiler is created from `pandas` object
+using :py:meth:`~modin.core.execution.python.implementations.pandas_on_python.io.io.PandasOnPythonIO.from_pandas` and returned.
+
+When writing data to a CSV file, for example, the :py:class:`~modin.core.execution.python.implementations.pandas_on_python.io.PandasOnPythonIO` converts a query compiler
+to `pandas` object using :py:meth:`~modin.core.storage_formats.base.query_compiler.BaseQueryCompiler.to_pandas`. After that, `pandas` writes the data to the file using
+corresponding function (``pandas.to_csv()`` in this case).