Update release notes and introduction

doc/introduction.rst

@@ -11,6 +11,7 @@ Some of the features that seaborn offers are
 - Tools for choosing :ref:`color palettes <palette_tutorial>` to make beautiful plots that reveal patterns in your data
 - Functions for visualizing :ref:`univariate <distplot_options>` and :ref:`bivariate <joint_kde>` distributions or for :ref:`comparing <violinplots>` them between subsets of data
 - Tools that fit and visualize :ref:`linear regression <anscombes_quartet>` models for different kinds of :ref:`independent <pointplot_anova>` and :ref:`dependent <logistic_regression>` variables
+- Functions that visualize :ref:`matrices of data <heatmap_annotation>` and use clustering algorithms to :ref:`discover structure <structured_heatmap>` in those matrices
 - A function to plot :ref:`statistical timeseries <timeseries_from_dataframe>` data with flexible estimation and :ref:`representation <timeseries_bootstrapped>` of uncertainty around the estimate
 - High-level abstractions for structuring :ref:`grids of plots <faceted_histogram>` that let you easily build :ref:`complex <many_facets>` visualizations
 

doc/releases/v0.5.0.txt

@@ -1,6 +1,8 @@
 
-v0.5.0 (Unreleased)
--------------------
+v0.5.0 (November 2014)
+--------------------------
+
+This is a major release from 0.4. Highlights include new functions for :ref:`plotting heatmaps <network_correlations>`, possibly while :ref:`applying clustering algorithms <structured_heatmap>` to discover structured relationships. These functions are complemented by new custom colormap functions and a full set of IPython widgets that allow interactive selection of colormap parameters. The :ref:`palette tutorial <palette_tutorial>` has been rewritten to cover these new tools and more generally provide guidance on how to use color in visualizations. There are also a number of smaller changes and bugfixes.
 
 Plotting functions
 ~~~~~~~~~~~~~~~~~~
@@ -22,19 +24,18 @@ Color palettes
 
 - Added the ability to specify the seed color for :func:`light_palette` and :func:`dark_palette` as a tuple of ``husl`` or ``hls`` space values or as a named ``xkcd`` color. The interpretation of the seed color is now provided by the new ``input`` parameter to these functions.
 
-- Added several new interactive palette widgets: :func:`choose_colorbrewer_palette`, :func:`choose_light_palette`, :func:`choose_dark_palette`, and :func:`choose_diverging_palette`. For consistency, renamed the cubehelix widget to :func:`choose_cubehelix_palette` (and fixed a bug where the cubehelix palette was reversed). These functions also now return either a color palette list or a matplotlib colormap when called, and that object will be live-updated as you play with the widget. This should make it easy to iterate over a plot until you find a good representation for the data. See the `Github pull request <https://github.com/mwaskom/seaborn/pull/286>`_ for more information.
+- Added several new interactive palette widgets: :func:`choose_colorbrewer_palette`, :func:`choose_light_palette`, :func:`choose_dark_palette`, and :func:`choose_diverging_palette`. For consistency, renamed the cubehelix widget to :func:`choose_cubehelix_palette` (and fixed a bug where the cubehelix palette was reversed). These functions also now return either a color palette list or a matplotlib colormap when called, and that object will be live-updated as you play with the widget. This should make it easy to iterate over a plot until you find a good representation for the data. See the `Github pull request <https://github.com/mwaskom/seaborn/pull/286>`_ or `this notebook (download it to use the widgets) <http://nbviewer.ipython.org/381a5f5f7e38f8e45bd6>`_ for more information.
 
 - Overhauled the color :ref:`palette tutorial <palette_tutorial>` to organize the discussion by class of color palette and provide more motivation behind the various choices one might make when choosing colors for their data.
 
 Bug fixes
 ~~~~~~~~~
-
-- Fixed a bug where :func:`lmplot` would show a legend when the hue variable was also used on either the rows or columns (making the legend redundant).
-
 - Fixed a bug in :class:`PairGrid` that gave incorrect results (or a crash) when the input DataFrame has a non-default index.
 
 - Fixed a bug in :class:`PairGrid` where passing columns with a date-like datatype raised an exception.
 
+- Fixed a bug where :func:`lmplot` would show a legend when the hue variable was also used on either the rows or columns (making the legend redundant).
+
 - Worked around a matplotlib bug that was forcing outliers in :func:`boxplot` to appear as blue.
 
 - :func:`kdeplot` now accepts pandas Series for the ``data`` and ``data2`` arguments.