diff --git a/python/docs/source/user_guide/sql/creating_dataframes.rst b/python/docs/source/user_guide/sql/creating_dataframes.rst
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@@ -0,0 +1,223 @@
+..  Licensed to the Apache Software Foundation (ASF) under one
+    or more contributor license agreements.  See the NOTICE file
+    distributed with this work for additional information
+    regarding copyright ownership.  The ASF licenses this file
+    to you under the Apache License, Version 2.0 (the
+    "License"); you may not use this file except in compliance
+    with the License.  You may obtain a copy of the License at
+
+..    http://www.apache.org/licenses/LICENSE-2.0
+
+..  Unless required by applicable law or agreed to in writing,
+    software distributed under the License is distributed on an
+    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+    KIND, either express or implied.  See the License for the
+    specific language governing permissions and limitations
+    under the License.
+
+
+===================
+Creating DataFrames
+===================
+
+.. currentmodule:: pyspark.sql
+
+PySpark allows you to create :class:`DataFrame`\s in several ways. Let's explore these methods with simple examples.
+
+Creating a :class:`DataFrame` from Lists
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+    :emphasize-lines: 5
+
+    >>> # when the schema is not provided, the resulting DataFrame has _1 and _2 as the schema
+    >>> df = spark.createDataFrame([['Alice', 1], ['Bob', 5]])
+    >>> df.show()
+    +-----+---+
+    |   _1| _2|
+    +-----+---+
+    |Alice|  1|
+    |  Bob|  5|
+    +-----+---+
+
+
+Creating a :class:`DataFrame` with a Specified Schema
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Define a schema and use it to create a :class:`DataFrame`. A schema describes the column names and types.
+
+.. code-block:: python
+
+    >>> from pyspark.sql.types import StructType, StructField, StringType, IntegerType
+    >>> schema = StructType([
+    ...     StructField("name", StringType(), True),
+    ...     StructField("age", IntegerType(), True)
+    ... ])
+    >>> df = spark.createDataFrame([('Alice', 1), ('Bob', 5)], schema)
+    >>> df.show()
+    +-----+---+
+    | name|age|
+    +-----+---+
+    |Alice|  1|
+    |  Bob|  5|
+    +-----+---+
+
+Use DDL-formatted string schema to create a :class:`DataFrame`.
+
+.. code-block:: python
+
+    >>> df = spark.createDataFrame([('Alice', 1), ('Bob', 5)], schema = "name string, age int")
+    >>> df.show()
+    +-----+---+
+    | name|age|
+    +-----+---+
+    |Alice|  1|
+    |  Bob|  5|
+    +-----+---+
+
+
+Creating a :class:`DataFrame` from Dictionaries
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Dictionaries with keys as column names can also be used.
+
+.. code-block:: python
+
+    >>> df = spark.createDataFrame([{'name': 'Alice', 'age': 1}])
+    >>> df.show()
+    +---+-----+
+    |age| name|
+    +---+-----+
+    |  1|Alice|
+    +---+-----+
+
+
+Creating a :class:`DataFrame` from :class:`Row`\s
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Use the :class:`Row` type to define rows of a :class:`DataFrame`.
+
+.. code-block:: python
+
+    >>> from pyspark.sql import Row
+    >>> Person = Row('name', 'age')
+    >>> df = spark.createDataFrame([Person("Alice", 1), Person("Bob", 5)])
+    >>> df.show()
+    +-----+---+
+    | name|age|
+    +-----+---+
+    |Alice|  1|
+    |  Bob|  5|
+    +-----+---+
+
+
+Creating a :class:`DataFrame` from a :class:`pandas.DataFrame` or a :class:`numpy.ndarray`
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    >>> import pandas as pd
+    >>> df = spark.createDataFrame(pd.DataFrame([[1, 2]]))
+    >>> df.show()
+    +---+---+
+    |  0|  1|
+    +---+---+
+    |  1|  2|
+    +---+---+
+
+
+.. code-block:: python
+
+    >>> import numpy as np
+    >>> import pandas as pd
+    >>> df = spark.createDataFrame(pd.DataFrame(data=np.array([[1, 2], [3, 4]]),
+    ...     columns=['a', 'b']))
+    >>> df.show()
+    +---+---+
+    |  a|  b|
+    +---+---+
+    |  1|  2|
+    |  3|  4|
+    +---+---+
+
+
+Reading Data from Files
+-----------------------
+
+Example with **JSON**
+~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    >>> df = spark.read.format("json").load("python/test_support/sql/people.json")
+    >>> df.show()
+    +----+-------+
+    | age|   name|
+    +----+-------+
+    |NULL|Michael|
+    |  30|   Andy|
+    |  19| Justin|
+    +----+-------+
+
+
+Example with **CSV**
+~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    >>> df = spark.read.format("csv").option("header", "true").load(
+    ...     "python/test_support/sql/people.csv")
+    >>> df.show()
+    +----+-------+
+    | age|   name|
+    +----+-------+
+    |NULL|Michael|
+    |  30|   Andy|
+    |  19| Justin|
+    +----+-------+
+
+
+Example with **PARQUET**
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    >>> # Write a Parquet file to a temporary directory and read it back.
+    >>> import tempfile
+    >>> with tempfile.TemporaryDirectory() as d:
+    ...     # Overwrite the path with a new Parquet file
+    ...     spark.createDataFrame(
+    ...         [{"age": None, "name": "Michael"}, {"age": 30, "name": "Andy"}]
+    ...     ).write.mode("overwrite").format("parquet").save(d)
+    ...     # Read the Parquet file as a DataFrame
+    ...     df = spark.read.format("parquet").load(d)
+    ...     df.show()
+    +----+-------+
+    | age|   name|
+    +----+-------+
+    |  30|   Andy|
+    |NULL|Michael|
+    +----+-------+
+
+Example with **ORC**
+~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    >>> # Write an ORC file to a temporary directory and read it back.
+    >>> import tempfile
+    >>> with tempfile.TemporaryDirectory() as d:
+    ...     # Overwrite the path with a new Orc file
+    ...     spark.createDataFrame(
+    ...         [{"age": None, "name": "Michael"}, {"age": 30, "name": "Andy"}]
+    ...     ).write.mode("overwrite").format("orc").save(d)
+    ...     # Read the ORC file as a DataFrame
+    ...     df = spark.read.format("orc").load(d)
+    ...     df.show()
+    +----+-------+
+    | age|   name|
+    +----+-------+
+    |  30|   Andy|
+    |NULL|Michael|
+    +----+-------+
+
diff --git a/python/docs/source/user_guide/sql/index.rst b/python/docs/source/user_guide/sql/index.rst
index 118cf139d9b38..1d3c9057f99e5 100644
--- a/python/docs/source/user_guide/sql/index.rst
+++ b/python/docs/source/user_guide/sql/index.rst
@@ -16,13 +16,14 @@
     under the License.
 
 
-=========
-Spark SQL
-=========
+========================
+Spark SQL and DataFrames
+========================
 
 .. toctree::
    :maxdepth: 2
 
+   creating_dataframes
    arrow_pandas
    python_udtf
    type_conversions