Empty dataframe data type error (#376) (#377)

lux/executor/Executor.py

@@ -73,6 +73,8 @@ def compute_data_type(self):
 
     def mapping(self, rmap):
         group_map = {}
+        if rmap == {}:
+            return {}
         for val in ["quantitative", "id", "nominal", "temporal", "geographical"]:
             group_map[val] = list(filter(lambda x: rmap[x] == val, rmap))
         return group_map

lux/processor/Compiler.py

@@ -164,13 +164,11 @@ def populate_data_type_model(ldf, vlist):
         from lux.utils.date_utils import is_datetime_string
 
         data_model_lookup = lux.config.executor.compute_data_model_lookup(ldf.data_type)
-
         for vis in vlist:
             for clause in vis._inferred_intent:
                 if clause.description == "?":
                     clause.description = ""
                 # TODO: Note that "and not is_datetime_string(clause.attribute))" is a temporary hack and breaks the `test_row_column_group` example
-                # and not is_datetime_string(clause.attribute):
                 if clause.attribute != "" and clause.attribute != "Record":
                     if clause.data_type == "":
                         clause.data_type = ldf.data_type[clause.attribute]

tests/test_nan.py

@@ -164,3 +164,12 @@ def test_numeric_with_nan():
     #     len(a.recommendation["Distribution"]) == 2
     # ), "Example where dtype might be off after dropna(), check if histograms are still displayed"
     assert "" in a._message.to_html(), "No warning message for NaN should be displayed"
+
+
+def test_empty_filter(global_var):
+    df = pytest.car_df
+    df["Year"] = pd.to_datetime(df["Year"], format="%Y")
+    fdf = df[df["Origin"] == "U"]
+    fdf._ipython_display_()
+    assert fdf.data_type == None
+    assert len(df[df["Origin"] == "U"]) == 0