plotnine changelog

Changelog History

Page 3

• v0.3.0 Changes

  November 08, 2017

  🚀 Big release with known bugs fixed and new features.

  A copy of the changelog is pasted below.

  ---

  API Changes

  • ~plotnine.geoms.geom_smooth gained an extra parameter
    legend_fill_ratio that control the area of the legend that is
    filled to indicate confidence intervals. (32)
  • plotnine.ggplot.save gained an extra parameter verbose. It no
    🖨 longer guesses when to print information and when not to.
  • plotnine.ggplot.draw gained an extra parameter return_ggplot.
  • If the minor_breaks parameter of scales is a callable, it now
    expects one argument, the limits. Previously it accepted breaks
    and limits.

  🆕 New Features

  • ➕ Added ~plotnine.animation.PlotnineAnimation for animations.
  • ➕ Added ~plotnine.watermark.watermark for watermarks.
  • ➕ Added datetime scales for alpha, colour, fill and size
    aesthetics

  ✨ Enhancements

  🔄 Changed parameter settings for ~plotnine.stats.stat_smooth.

  1. Default span=0.75 instead of 2/3
  2. When using loess smoothing, the control parameter surface is
     only set to the value 'direct' if predictions will be made
     outside the data range.

  👍 Better control of scale limits. You can now specify individual
  limits of a scale.

  scale_y_continuous(limits=(0, None))
  xlim(None, 100)
  

  You can also use ~plotnine.scales.expand_limits

  Low and high ~plotnine.scales.scale limits can now be expanded
  separately with different factors multiplicative and additive
  factors.

  The layer parameter show_legend can now accept a dict for finer
  grained control of which aesthetics to exclude in the legend.

  🚚 Infinite values are removed before statistical computations stats
  (40).

  stats also gained new parameter na_rm, that controls whether
  🚚 missing values are removed before statistical computations.

  ~plotnine.qplot can now use the name and a Pandas series to label
  the scales of the aesthetics.

  You can now put stuff to add to a ggplot object into a list and add
  that that instead. No need to wrap the list around the internal
  class Layers.

  lst = [geom_point(), geom_line()]
  g = ggplot(df, aes('x', 'y'))
  print(g + lst)
  

  Using a list allows you to bundle up objects. It can be convenient
  👀 when creating some complicated plots. See the Periodic Table
  Example.

  🐛 Bug Fixes

  • 🛠 Fixed bug where facetting led to a reordering of the data. This
    would manifest as a bug for geoms where order was important. (26)
  • 🛠 Fix bug where facetting by a column whose name (eg. class) is a
    👻 python keyword resulted in an exception. (28)
  • 🛠 Fix bug where y-axis scaling was calculated from the xlim
    argument.
  • 🛠 Fix bug where initialising geoms from stats, and positions from
    geoms, when passed as classes (e.g. stat_smooth(geom=geom_point),
    would fail.
  • 🛠 Fixed bug in plotnine.ggplot.save where s

• v0.2.1

  June 22, 2017

• v0.2.0 Changes

  May 18, 2017

  🛠 Fixes

  • Fixed bug in scale_x_discrete and scale_y_discrete where if they were instantiated with parameter limits that is either a numpy array or a pandas series, plotting would fail with a ValueError.
  • 🛠 Fixed exceptions when using pandas.pivot_table() for Pandas v0.20.0. The API was fixed.
  • 🛠 Fixed issues where lines/paths with segments that all belonged in the same group had joins that in some cases were “butted”.

  API Changes

  • geom_text now uses ha and va as parameter names for the horizontal and vertical alignment. This is what matplotlib users expect. The previous names hjust and vjust are silently accepted.
  • Layers() can now be used to bundle up geoms and stats. This makes it easy to reuse geoms and stats or organise them in sensible bundles when making complex plots.

• v0.1.0 Changes

  April 28, 2017

  🚀 First public release

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