Update size= to height= in example gallery

examples/anscombes_quartet.py

@@ -12,5 +12,5 @@
 
 # Show the results of a linear regression within each dataset
 sns.lmplot(x="x", y="y", col="dataset", hue="dataset", data=df,
-           col_wrap=2, ci=None, palette="muted", size=4,
+           col_wrap=2, ci=None, palette="muted", height=4,
            scatter_kws={"s": 50, "alpha": 1})

examples/facets_with_custom_projection.py → examples/facet_projections.py

@@ -20,7 +20,7 @@
 
 # Set up a grid of axes with a polar projection
 g = sns.FacetGrid(df, col="speed", hue="speed",
-                  subplot_kws=dict(projection='polar'), size=4.5,
+                  subplot_kws=dict(projection='polar'), height=4.5,
                   sharex=False, sharey=False, despine=False)
 
 # Draw a scatterplot onto each axes in the grid

examples/factorplot_bars.py

@@ -12,6 +12,6 @@
 
 # Draw a nested barplot to show survival for class and sex
 g = sns.factorplot(x="class", y="survived", hue="sex", data=titanic,
-                   size=6, kind="bar", palette="muted")
+                   height=6, kind="bar", palette="muted")
 g.despine(left=True)
 g.set_ylabels("survival probability")

examples/joint_kde.py

@@ -18,4 +18,4 @@
 x2 = pd.Series(x2, name="$X_2$")
 
 # Show the joint distribution using kernel density estimation
-g = sns.jointplot(x1, x2, kind="kde", size=7, space=0)
+g = sns.jointplot(x1, x2, kind="kde", height=7, space=0)

examples/kde_ridgeplot.py

@@ -20,7 +20,7 @@
 
 # Initialize the FacetGrid object
 pal = sns.cubehelix_palette(10, rot=-.25, light=.7)
-g = sns.FacetGrid(df, row="g", hue="g", aspect=15, size=.5, palette=pal)
+g = sns.FacetGrid(df, row="g", hue="g", aspect=15, height=.5, palette=pal)
 
 # Draw the densities in a few steps
 g.map(sns.kdeplot, "x", clip_on=False, shade=True, alpha=1, lw=1.5, bw=.2)

examples/many_facets.py

@@ -23,7 +23,7 @@
 
 # Initialize a grid of plots with an Axes for each walk
 grid = sns.FacetGrid(df, col="walk", hue="walk", palette="tab20c",
-                     col_wrap=4, size=1.5)
+                     col_wrap=4, height=1.5)
 
 # Draw a horizontal line to show the starting point
 grid.map(plt.axhline, y=0, ls=":", c=".5")

examples/marginal_ticks.py

@@ -16,6 +16,6 @@
 x, y = rs.multivariate_normal(mean, cov, 100).T
 
 # Use JointGrid directly to draw a custom plot
-grid = sns.JointGrid(x, y, space=0, size=6, ratio=50)
+grid = sns.JointGrid(x, y, space=0, height=6, ratio=50)
 grid.plot_joint(plt.scatter, color="g")
 grid.plot_marginals(sns.rugplot, height=1, color="g")

examples/multiple_regression.py

@@ -12,7 +12,7 @@
 
 # Plot sepal with as a function of sepal_length across days
 g = sns.lmplot(x="sepal_length", y="sepal_width", hue="species",
-               truncate=True, size=5, data=iris)
+               truncate=True, height=5, data=iris)
 
 # Use more informative axis labels than are provided by default
 g.set_axis_labels("Sepal length (mm)", "Sepal width (mm)")

examples/paired_pointplots.py

@@ -12,7 +12,7 @@
 # Set up a grid to plot survival probability against several variables
 g = sns.PairGrid(titanic, y_vars="survived",
                  x_vars=["class", "sex", "who", "alone"],
-                 size=5, aspect=.5)
+                 height=5, aspect=.5)
 
 # Draw a seaborn pointplot onto each Axes
 g.map(sns.pointplot, scale=1.3, errwidth=4, color="xkcd:plum")

examples/pairgrid_dotplot.py

@@ -13,7 +13,7 @@
 # Make the PairGrid
 g = sns.PairGrid(crashes.sort_values("total", ascending=False),
                  x_vars=crashes.columns[:-3], y_vars=["abbrev"],
-                 size=10, aspect=.25)
+                 height=10, aspect=.25)
 
 # Draw a dot plot using the stripplot function
 g.map(sns.stripplot, size=10, orient="h",

examples/pointplot_anova.py

@@ -12,5 +12,5 @@
 
 # Draw a pointplot to show pulse as a function of three categorical factors
 g = sns.factorplot(x="time", y="pulse", hue="kind", col="diet", data=df,
-                   capsize=.2, palette="YlGnBu_d", size=6, aspect=.75)
+                   capsize=.2, palette="YlGnBu_d", height=6, aspect=.75)
 g.despine(left=True)

examples/regression_marginals.py

@@ -9,4 +9,4 @@
 
 tips = sns.load_dataset("tips")
 g = sns.jointplot("total_bill", "tip", data=tips, kind="reg",
-                  xlim=(0, 60), ylim=(0, 12), color="m", size=7)
+                  xlim=(0, 60), ylim=(0, 12), color="m", height=7)