changes

lux/action/enhance.py

@@ -51,8 +51,15 @@ def enhance(ldf):
             "description": f"Further breaking down current {intended_attrs} intent by additional attribute.",
             "long_description": f"Enhance adds an additional attribute as the color to break down the {intended_attrs} distribution",
         }
+    if (
+        filter(lambda x: ldf.data_type[x] == "ordinal", attr_str)
+        and lux.config.plotting_backend == "matplotlib"
+    ):
+        recommendation[
+            "long_description"
+        ] += f"The Box Plot Visualizations in the 'Enhance' tab are rendered using <a href='https://altair-viz.github.io/'>Altair</a>. Lux does not currently support box plots with Matplotlib. If you would like this feature, please leave us a comment at <a href='https://github.com/lux-org/lux/issues/240'>issue #240</a> to let us know!"
     # if there are too many column attributes, return don't generate Enhance recommendations
-    else:
+    if len(attr_specs) > 2:
         recommendation = {"action": "Enhance"}
         recommendation["collection"] = []
         return recommendation

lux/action/univariate.py

@@ -62,6 +62,7 @@ def univariate(ldf, *args):
         if len(ldf) < 5:
             ignore_rec_flag = True
     elif data_type_constraint == "nominal":
+        # possible attributes are only nominal/ordinal data types for categorical data
         possible_attributes = [
             c
             for c in ldf.columns

lux/vislib/altair/BoxPlot.py

@@ -26,6 +26,7 @@ def __repr__(self):
         return f"BoxPlot <{str(self.vis)}>"
 
     def initialize_chart(self):
+
         x_attr = self.vis.get_attr_by_channel("x")[0]
         y_attr = self.vis.get_attr_by_channel("y")[0]