Update dataframe page.

mrocklin · Dec 15, 2023 · c8989d9 · c8989d9
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diff --git a/docs/source/dataframe-api.rst b/docs/source/dataframe-api.rst
@@ -1,5 +1,5 @@
-API
----
+Dask DataFrame API
+==================
 
 .. currentmodule:: dask.dataframe
 

diff --git a/docs/source/dataframe-create.rst b/docs/source/dataframe-create.rst
@@ -1,5 +1,5 @@
-Create and Store Dask DataFrames
-================================
+Load and Save Data with Dask DataFrames
+=======================================
 
 .. meta::
     :description: Learn how to create DataFrames and store them. Create a Dask DataFrame from various data storage formats like CSV, HDF, Apache Parquet, and others.
@@ -67,7 +67,7 @@ Read from CSV
 
 You can use :func:`read_csv` to read one or more CSV files into a Dask DataFrame.
 It supports loading multiple files at once using globstrings:
-  
+
 .. code-block:: python
 
    >>> df = dd.read_csv('myfiles.*.csv')
@@ -76,7 +76,7 @@ You can break up a single large file with the ``blocksize`` parameter:
 
 .. code-block:: python
 
-   >>> df = dd.read_csv('largefile.csv', blocksize=25e6)  # 25MB chunks  
+   >>> df = dd.read_csv('largefile.csv', blocksize=25e6)  # 25MB chunks
 
 Changing the ``blocksize`` parameter will change the number of partitions (see the explanation on
 :ref:`partitions <dataframe-design-partitions>`). A good rule of thumb when working with

diff --git a/docs/source/dataframe-design.rst b/docs/source/dataframe-design.rst
@@ -1,7 +1,7 @@
 .. _dataframe.design:
 
-Internal Design
-===============
+Dask DataFrame Design
+=====================
 
 Dask DataFrames coordinate many Pandas DataFrames/Series arranged along an
 index.  We define a Dask DataFrame object with the following components:

diff --git a/docs/source/dataframe-extra.rst b/docs/source/dataframe-extra.rst
@@ -0,0 +1,14 @@
+Additional Information
+======================
+
+.. toctree::
+   :maxdepth: 1
+
+   Parquet <dataframe-parquet.rst>
+   Indexing <dataframe-indexing.rst>
+   SQL <dataframe-sql.rst>
+   Join Performance <dataframe-joins.rst>
+   Shuffling Performance <dataframe-groupby.rst>
+   dataframe-categoricals.rst
+   Extend <dataframe-extend.rst>
+   Hive Partitioning <dataframe-hive.rst>
diff --git a/docs/source/dataframe-groupby.rst b/docs/source/dataframe-groupby.rst
@@ -1,5 +1,5 @@
-Shuffling for GroupBy and Join
-==============================
+Shuffling Performance
+=====================
 
 .. currentmodule:: dask.dataframe