Fixes Bugs in Describe (#140)

* fixing describe bug

* formatting

* formatting change

* removed comments

modin/data_management/data_manager.py

@@ -159,15 +159,17 @@ def helper(df, internal_indices=[]):
 
         return helper
 
-    def numeric_columns(self):
+    def numeric_columns(self, include_bool=True):
         """Returns the numeric columns of the Manager.
 
         Returns:
             List of index names.
         """
         columns = []
         for col, dtype in zip(self.columns, self.dtypes):
-            if is_numeric_dtype(dtype):
+            if is_numeric_dtype(dtype) and (
+                include_bool or (not include_bool and dtype != np.bool_)
+            ):
                 columns.append(col)
         return columns
 
@@ -1379,25 +1381,45 @@ def describe(self, **kwargs):
         Returns:
             DataFrame object containing the descriptive statistics of the DataFrame.
         """
-        # Only describe numeric if there are numeric
+        # Only describe numeric if there are numeric columns
         # Otherwise, describe all
-        columns_for_describe = self.numeric_columns()
-        if len(columns_for_describe) != 0 and "object" in kwargs["exclude"]:
+        new_columns = self.numeric_columns(include_bool=False)
+        if len(new_columns) != 0:
             numeric = True
+            exclude = kwargs.get("exclude", None)
+            if is_list_like(exclude):
+                exclude.append([np.timedelta64, np.datetime64])
+            else:
+                exclude = [exclude, np.timedelta64, np.datetime64]
+            kwargs["exclude"] = exclude
         else:
             numeric = False
-            # If no numeric dtypes, then do all
-            columns_for_describe = self.columns
+            # If only timedelta and datetime objects, only do the timedelta
+            # columns
+            if all(
+                (
+                    dtype
+                    for dtype in self.dtypes
+                    if dtype == np.datetime64 or dtype == np.timedelta64
+                )
+            ):
+                new_columns = [
+                    self.columns[i]
+                    for i in range(len(self.columns))
+                    if self.dtypes[i] != np.dtype("datetime64[ns]")
+                ]
+            else:
+                # Describe all columns
+                new_columns = self.columns
 
         def describe_builder(df, **kwargs):
             return pandas.DataFrame.describe(df, **kwargs)
 
         # Apply describe and update indices, columns, and dtypes
         func = self._prepare_method(describe_builder, **kwargs)
         new_data = self.full_axis_reduce_along_select_indices(
-            func, 0, columns_for_describe, False
+            func, 0, new_columns, False
         )
-        new_columns = columns_for_describe
         new_index = self.compute_index(0, new_data, False)
         if numeric:
             new_dtypes = pandas.Series(