diff --git a/miscplot/variability.py b/miscplot/variability.py
index 364b196..aff667d 100644
--- a/miscplot/variability.py
+++ b/miscplot/variability.py
@@ -62,12 +62,12 @@ def variability_plot(
     df = polars.DataFrame(data_table)
 
     # Drop nulls and nans so that the boxplots don't disappear
-    df = df.drop_nulls(subset=[data_col]).drop_nans(subset=[data_col])
+    df = polars.drop_nulls(subset=[data_col]).drop_nans(subset=[data_col])
 
     # Assign category indicies (x_pos)
     df = df.sort(groups)
     df_groups = df.select(groups).unique(maintain_order=True).with_row_index(name='x_pos')
-    df = df.join(df_groups, on=groups, maintain_order='left', nulls_equal=True)
+    df = df.join(df_groups, on=groups, maintain_order='left')
     max_group_length = df.group_by(groups).len().select('len').max()[0, 0]   # How many points in the largest x_pos
 
     # Add jitter to the scatterplots-plots
@@ -90,7 +90,7 @@ def variability_plot(
     y_ratios = [mainplot_ratios[1]] + get_label_y_ratios(groups, vert_groups, size_lists)
 
     # Build the figure and all axes
-    fig = pyplot.figure(figsize=(16, 9))
+    fig = pyplot.figure()
     gs = gridspec.GridSpec(
         nrows = 1 + len(groups),
         ncols = 2,
@@ -117,16 +117,14 @@ def variability_plot(
             dotprops = {}
         dotprops.setdefault('alpha', 0.7)
         dotprops.setdefault('color', 'black')
-        dotprops.setdefault('zorder', 5)
         _dotplt = ax.scatter(x_data, y_data, s=numpy.ones_like(y_data), **dotprops)
     if boxprops:
         if not isinstance(boxprops, dict):
             boxprops = {}
         boxprops.setdefault('showfliers', False)
-        boxprops.setdefault('medianprops', dict(linewidth=3, color='darkred', alpha=0.5, zorder=2))
-        boxprops.setdefault('boxprops', dict(linewidth=0.5, color='black', zorder=3))
-        boxprops.setdefault('whiskerprops', dict(linewidth=0.5, color='black', zorder=3))
-        boxprops.setdefault('zorder', 3)
+        boxprops.setdefault('medianprops', dict(linewidth=3, color='darkred', alpha=0.8))
+        boxprops.setdefault('boxprops', dict(linewidth=0.5, color='black'))
+        boxprops.setdefault('whiskerprops', dict(linewidth=0.5, color='black'))
         _boxplt = ax.boxplot(y_lists, positions=range(num_dsets), **boxprops)
     if meanprops:
         means = [yl.mean() for yl in y_lists]
@@ -142,7 +140,6 @@ def variability_plot(
         meanprops.setdefault('color', 'blue')
         meanprops.setdefault('alpha', 0.8)
         meanprops.setdefault('linewidth', 0.5)
-        meanprops.setdefault('zorder', 3)
         _meanplt = ax.plot(xy[:, 0], xy[:, 1], **meanprops)
 
 
@@ -214,8 +211,8 @@ def variability_plot(
     ax.set_xticklabels([], minor=False)
     ax.set_xticklabels([], minor=True)
     ax.tick_params('x', which='both', bottom=False)
-    ax.grid(alpha=0.2, which='minor', zorder=0)
-    ax.grid(alpha=1, which='major', zorder=0)
+    ax.grid(alpha=0.2, which='minor')
+    ax.grid(alpha=1, which='major')
     ax.set_ylabel(data_col)
     ax.set_title(data_col)
     ax.yaxis.set_minor_locator(ticker.AutoMinorLocator())
@@ -287,8 +284,7 @@ def get_label_stack(df_groups: polars.DataFrame, groups: Sequence[str], wrap_fn:
         label_row = []
         for row in spans.to_dicts():
             # df row is plot column
-            rl = row[level]
-            text_value = wrap_fn(rl) if isinstance(rl, str) else wrap_fn(str(rl).removesuffix('.0'))
+            text_value = wrap_fn(str(row[level]))
             label_row.append((row['xmin'], row['xmax'], text_value))
         label_stack.append(label_row)
     return label_stack