Fix bool_only argument functions (#125)

* Fixed functions with bool_only arguments

* Fixed formatting

* Fixed any to have same behavior as all and consolidated to have one helper

* formatting

* Fixed default value for any

* Created processing function to keep all and any as attributes of PandasDataFrames

modin/data_management/data_manager.py

@@ -1116,21 +1116,40 @@ def all(self, **kwargs):
         """Returns whether all the elements are true, potentially over an axis.
 
         Return:
-            Pandas Series containing boolean values.
+            Pandas Series containing boolean values or boolean.
         """
-        axis = kwargs.get("axis", 0)
-        func = self._prepare_method(pandas.DataFrame.all, **kwargs)
-        return self.full_axis_reduce(func, axis)
+        return self._process_all_any(pandas.DataFrame.all, **kwargs)
 
     def any(self, **kwargs):
-        """Returns whether any element is true over the requested axis.
+        """Returns whether any the elements are true, potentially over an axis.
+
+        Return:
+            Pandas Series containing boolean values or boolean.
+        """
+        return self._process_all_any(pandas.DataFrame.any, **kwargs)
+
+    def _process_all_any(self, func, **kwargs):
+        """Calculates if any or all the values are true.
 
         Return:
-            Pandas Series containing boolean values.
+            Pandas Series containing boolean values or boolean.
         """
         axis = kwargs.get("axis", 0)
-        func = self._prepare_method(pandas.DataFrame.any, **kwargs)
-        return self.full_axis_reduce(func, axis)
+        bool_only = kwargs.get("bool_only", None)
+        index = self.index if axis else self.columns
+        if bool_only:
+            not_bool = []
+            for index, dtype in zip(index, self.dtypes):
+                if dtype != bool:
+                    not_bool.append(index)
+            if axis:
+                data_manager = self.drop(index=not_bool)
+            else:
+                data_manager = self.drop(columns=not_bool)
+        else:
+            data_manager = self
+        func = data_manager._prepare_method(func, **kwargs)
+        return data_manager.full_axis_reduce(func, axis)
 
     def first_valid_index(self):
         """Returns index of first non-NaN/NULL value.

modin/pandas/dataframe.py

@@ -658,7 +658,6 @@ def all(self, axis=0, bool_only=None, skipna=None, level=None, **kwargs):
             axis = pandas.DataFrame()._get_axis_number(axis)
         else:
             axis = None
-
         result = self._data_manager.all(
             axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
         )
@@ -667,18 +666,24 @@ def all(self, axis=0, bool_only=None, skipna=None, level=None, **kwargs):
         else:
             return result.all()
 
-    def any(self, axis=None, bool_only=None, skipna=None, level=None, **kwargs):
+    def any(self, axis=0, bool_only=None, skipna=None, level=None, **kwargs):
         """Return whether any elements are True over requested axis
 
         Note:
             If axis=None or axis=0, this call applies on the column partitions,
                 otherwise operates on row partitions
         """
-        axis = pandas.DataFrame()._get_axis_number(axis) if axis is not None else 0
-
-        return self._data_manager.any(
+        if axis is not None:
+            axis = pandas.DataFrame()._get_axis_number(axis)
+        else:
+            axis = None
+        result = self._data_manager.any(
             axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
         )
+        if axis is not None:
+            return result
+        else:
+            return result.any()
 
     def append(self, other, ignore_index=False, verify_integrity=False, sort=None):
         """Append another DataFrame/list/Series to this one.