LuxSeriesGroupBy apply bugfix (#390)

* bugfix LuxSeriesGroupBy

* black

lux/core/frame.py

@@ -851,12 +851,6 @@ def tail(self, n: int = 5):
         ret_val._history.append_event("tail", n=5)
         return ret_val
 
-    def describe(self, *args, **kwargs):
-        ret_val = super(LuxDataFrame, self).describe(*args, **kwargs)
-        ret_val._pandas_only = True
-        ret_val._history.append_event("describe", *args, **kwargs)
-        return ret_val
-
     def groupby(self, *args, **kwargs):
         history_flag = False
         if "history" not in kwargs or ("history" in kwargs and kwargs["history"]):

lux/core/groupby.py

@@ -67,13 +67,6 @@ def apply(self, *args, **kwargs):
         ret_val.pre_aggregated = False  # Returned LuxDataFrame isn't pre_aggregated
         return ret_val
 
-    def apply(self, *args, **kwargs):
-        ret_val = super(LuxDataFrameGroupBy, self).apply(*args, **kwargs)
-        for attr in self._metadata:
-            ret_val.__dict__[attr] = getattr(self, attr, None)
-        ret_val.pre_aggregated = False  # Returned LuxDataFrame isn't pre_aggregated
-        return ret_val
-
     def size(self, *args, **kwargs):
         ret_val = super(LuxGroupBy, self).size(*args, **kwargs)
         for attr in self._metadata:

tests/test_pandas.py

@@ -42,6 +42,13 @@ def test_describe(global_var):
     assert len(summary.columns) == 10
 
 
+def test_groupby_describe(global_var):
+    df = pytest.college_df
+    result = df.groupby("FundingModel")["AdmissionRate"].describe()
+    result._ipython_display_()
+    assert result.shape == (3, 8)
+
+
 def test_convert_dtype(global_var):
     df = pytest.college_df
     cdf = df.convert_dtypes()