From fa3a537488c6de7073671c69918fede6a4d84dc1 Mon Sep 17 00:00:00 2001 From: Joris Van den Bossche Date: Sun, 14 Feb 2016 13:25:20 +0100 Subject: [PATCH] DOC/DEPR: remove remaining occurences of mpl_style from docs (GH12190) --- doc/source/dsintro.rst | 5 +---- doc/source/visualization.rst | 12 ++---------- 2 files changed, 3 insertions(+), 14 deletions(-) diff --git a/doc/source/dsintro.rst b/doc/source/dsintro.rst index d67e31b576654..599724d88bf63 100644 --- a/doc/source/dsintro.rst +++ b/doc/source/dsintro.rst @@ -10,10 +10,7 @@ pd.options.display.max_rows = 15 import matplotlib - try: - matplotlib.style.use('ggplot') - except AttributeError: - pd.options.display.mpl_style = 'default' + matplotlib.style.use('ggplot') import matplotlib.pyplot as plt plt.close('all') diff --git a/doc/source/visualization.rst b/doc/source/visualization.rst index c3c49e62703a9..b1d400cae156b 100644 --- a/doc/source/visualization.rst +++ b/doc/source/visualization.rst @@ -10,10 +10,7 @@ np.set_printoptions(precision=4, suppress=True) pd.options.display.max_rows = 15 import matplotlib - try: - matplotlib.style.use('ggplot') - except AttributeError: - pd.options.display.mpl_style = 'default' + matplotlib.style.use('ggplot') import matplotlib.pyplot as plt plt.close('all') @@ -34,11 +31,6 @@ The plots in this document are made using matplotlib's ``ggplot`` style (new in import matplotlib matplotlib.style.use('ggplot') -If your version of matplotlib is 1.3 or lower, you can set ``display.mpl_style`` to ``'default'`` -with ``pd.options.display.mpl_style = 'default'`` -to produce more appealing plots. -When set, matplotlib's ``rcParams`` are changed (globally!) to nicer-looking settings. - We provide the basics in pandas to easily create decent looking plots. See the :ref:`ecosystem ` section for visualization libraries that go beyond the basics documented here. @@ -189,7 +181,7 @@ For labeled, non-time series data, you may wish to produce a bar plot: @savefig bar_plot_ex.png df.ix[5].plot.bar(); plt.axhline(0, color='k') -Calling a DataFrame's :meth:`~DataFrame.plot.bar` method produces a multiple +Calling a DataFrame's :meth:`plot.bar() ` method produces a multiple bar plot: .. ipython:: python