DOC: fix more typos in stats docstrings

phobson · phobson · commit a47556ab04bf · 2016-10-23T08:39:31.000-07:00
diff --git a/examples/statistics/boxplot_demo.py b/examples/statistics/boxplot_demo.py
@@ -4,10 +4,10 @@
 =========================================
 
 This example demonstrates how to use the various kwargs
-to fully customize box plots. The first figure demostrates
+to fully customize box plots. The first figure demonstrates
 how to remove and add individual components (note that the
 mean is the only value not shown by default). The second
-figure demonstrates how the styles of the artists of can
+figure demonstrates how the styles of the artists can
 be customized. It also demonstrates how to set the limit
 of the whiskers to specific percentiles (lower right axes)
 """
diff --git a/examples/statistics/bxp_demo.py b/examples/statistics/bxp_demo.py
@@ -4,7 +4,7 @@
 ===================================
 
 This example demonstrates how to pass pre-computed box plot
-statistics to the box plot drawer. The first figure demostrates
+statistics to the box plot drawer. The first figure demonstrates
 how to remove and add individual components (note that the
 mean is the only value not shown by default). The second
 figure demonstrates how the styles of the artists can
diff --git a/examples/statistics/customized_violin_demo.py b/examples/statistics/customized_violin_demo.py
@@ -7,7 +7,7 @@
 The first plot shows the default style by providing only
 the data. The second plot first limits what matplotlib draws
 with additional kwargs. Then a simplified representation of
-a box plot in drawn on top. Lastly, the styles of the artists
+a box plot is drawn on top. Lastly, the styles of the artists
 of the violins are modified.
 """
 
@@ -91,7 +91,7 @@ def adjacent_values(vals):
 for ax in [ax1, ax2]:
     ax.get_xaxis().set_tick_params(direction='out')
     ax.xaxis.set_ticks_position('bottom')
-    ax.set_xticks([x for x in np.arange(1, len(lab) + 1)])
+    ax.set_xticks(np.arange(1, len(lab) + 1))
     ax.set_xticklabels(lab)
     ax.set_xlim(0.25, len(lab) + 0.75)
     ax.set_xlabel('Sample name')
diff --git a/examples/statistics/histogram_demo_cumulative.py b/examples/statistics/histogram_demo_cumulative.py
@@ -11,7 +11,7 @@
 A couple of other options to the ``hist`` function are demonstrated.
 Namely, we use the ``normed`` parameter to normalize the histogram and
 a couple of different options to the `cumulative` parameter. Normalizing
-a histogram means that the heights bins are scaled such that
+a histogram means that the bin heights are scaled such that
 the total area is 1. Since we're showing a normalized and
 cumulative histogram, the max value at the end of the series is 1.
 The ``normed`` parameter takes a boolean value.
