v0.5.0 (November 2014)

This is a major release from 0.4. Highlights include new functions for plotting heatmaps, possibly while applying clustering algorithms 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 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

• Added the heatmap function for visualizing a matrix of data by
  color-encoding the values. See the docs for more
  information.
• Added the clustermap function for clustering and visualizing a
  matrix of data, with options to label individual rows and columns by
  colors. See the docs for more information. This work
  was lead by Olga Botvinnik.
• lmplot and pairplot get a new keyword argument, markers. This can
  be a single kind of marker or a list of different markers for each
  level of the hue variable. Using different markers for different
  hues should let plots be more comprehensible when reproduced to
  black-and-white (i.e. when printed). See the github pull
  request for examples.
• More generally, there is a new keyword argument in FacetGrid and
  PairGrid, hue_kws. This similarly lets plot aesthetics vary across
  the levels of the hue variable, but more flexibily. hue_kws should
  be a dictionary that maps the name of keyword arguments to lists of
  values that are as long as the number of levels of the hue variable.
• The argument subplot_kws has been added to FacetGrid. This
  allows for faceted plots with custom projections, including maps
  with
  Cartopy.

Color palettes

• Added two new functions to create custom color palettes. For
  sequential palettes, you can use the light_palette function, which
  takes a seed color and creates a ramp from a very light, desaturated
  variant of it. For diverging palettes, you can use the
  diverging_palette function to create a balanced ramp between two
  endpoints to a light or dark midpoint. See the
  palette tutorial <palette_tutorial> for more information.
• Added the ability to specify the seed color for light_palette and
  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:
  choose_colorbrewer_palette, choose_light_palette,
  choose_dark_palette, and choose_diverging_palette. For
  consistency, renamed the cubehelix widget to
  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 or this
  notebook (download it to use the
  widgets) for more
  information.
• Overhauled the color 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 in PairGrid that gave incorrect results (or a crash)
  when the input DataFrame has a non-default index.
• Fixed a bug in PairGrid where passing columns with a date-like
  datatype raised an exception.
• Fixed a bug where 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 boxplot
  to appear as blue.
• kdeplot now accepts pandas Series for the data and data2
  arguments.
• Using a non-default correlation method in corrplot now implies
  sig_stars=False as the permutation test used to significance
  values for the correlations uses a pearson metric.
• Removed pdf.fonttype from the style definitions, as the value used
  in version 0.4 resulted in very large PDF files.