From f8cade3afc7c75eebecc82e4ba10e0f66b09decc Mon Sep 17 00:00:00 2001 From: Jason Swails Date: Tue, 8 Sep 2015 13:18:31 -0400 Subject: [PATCH] Fix repeated typo in documentation: documenation -> documentation --- doc/source/visualization.rst | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/doc/source/visualization.rst b/doc/source/visualization.rst index 2eaf143a3e0b8..8785a8d092d48 100644 --- a/doc/source/visualization.rst +++ b/doc/source/visualization.rst @@ -375,7 +375,7 @@ For example, horizontal and custom-positioned boxplot can be drawn by See the :meth:`boxplot ` method and the -`matplotlib boxplot documenation `__ for more. +`matplotlib boxplot documentation `__ for more. The existing interface ``DataFrame.boxplot`` to plot boxplot still can be used. @@ -601,7 +601,7 @@ Below example shows a bubble chart using a dataframe column values as bubble siz plt.close('all') See the :meth:`scatter ` method and the -`matplotlib scatter documenation `__ for more. +`matplotlib scatter documentation `__ for more. .. _visualization.hexbin: @@ -665,7 +665,7 @@ given by column ``z``. The bins are aggregated with numpy's ``max`` function. plt.close('all') See the :meth:`hexbin ` method and the -`matplotlib hexbin documenation `__ for more. +`matplotlib hexbin documentation `__ for more. .. _visualization.pie: @@ -761,7 +761,7 @@ If you pass values whose sum total is less than 1.0, matplotlib draws a semicirc @savefig series_pie_plot_semi.png series.plot(kind='pie', figsize=(6, 6)) -See the `matplotlib pie documenation `__ for more. +See the `matplotlib pie documentation `__ for more. .. ipython:: python :suppress: @@ -1445,7 +1445,7 @@ Finally, there is a helper function ``pandas.tools.plotting.table`` to create a plt.close('all') -**Note**: You can get table instances on the axes using ``axes.tables`` property for further decorations. See the `matplotlib table documenation `__ for more. +**Note**: You can get table instances on the axes using ``axes.tables`` property for further decorations. See the `matplotlib table documentation `__ for more. .. _visualization.colormaps: