change constructor calls

python/cudf/cudf/core/column/methods.py

@@ -84,7 +84,7 @@ def _return_or_inplace(
                     idx.names = None
                     return idx
                 else:
-                    return self._parent._constructor_expanddim(
+                    return self._parent._constructor_expanddim._from_data(
                         data=table._data, index=self._parent.index
                     )
             elif isinstance(self._parent, cudf.Series):

python/cudf/cudf/core/dataframe.py

@@ -349,7 +349,7 @@ class _DataFrameIlocIndexer(_DataFrameIndexer):
     def _getitem_tuple_arg(self, arg):
         # Iloc Step 1:
         # Gather the columns specified by the second tuple arg
-        columns_df = DataFrame(self._frame._get_columns_by_index(arg[1]))
+        columns_df = self._frame._get_columns_by_index(arg[1])
 
         columns_df._index = self._frame._index
 
@@ -399,7 +399,7 @@ def _getitem_tuple_arg(self, arg):
 
     @annotate("ILOC_SETITEM", color="blue", domain="cudf_python")
     def _setitem_tuple_arg(self, key, value):
-        columns = DataFrame(self._frame._get_columns_by_index(key[1]))
+        columns = self._frame._get_columns_by_index(key[1])
 
         for col in columns:
             self._frame[col].iloc[key[0]] = value
@@ -569,9 +569,10 @@ def __init__(
                     }
                 )
         elif isinstance(data, ColumnAccessor):
-            result = self._from_data(data, index, columns)
-            self._data = result._data
-            self._index = result._index
+            raise TypeError(
+                "Use cudf.Series._from_data for constructing a Series from "
+                "ColumnAccessor"
+            )
         elif hasattr(data, "__cuda_array_interface__"):
             arr_interface = data.__cuda_array_interface__
 

python/cudf/cudf/core/frame.py

@@ -563,7 +563,7 @@ def _get_columns_by_index(self, indices):
 
         """
         data = self._data.select_by_index(indices)
-        return self.__class__(
+        return self.__class__._from_data(
             data, columns=data.to_pandas_index(), index=self.index
         )
 

python/cudf/cudf/core/reshape.py

@@ -239,7 +239,7 @@ def concat(objs, axis=0, join="outer", ignore_index=False, sort=None):
 
         if ignore_index:
             if axis == 1:
-                result = cudf.DataFrame(
+                result = cudf.DataFrame._from_data(
                     data=obj._data.copy(deep=True),
                     index=obj.index.copy(deep=True),
                 )
@@ -249,13 +249,17 @@ def concat(objs, axis=0, join="outer", ignore_index=False, sort=None):
                 # after construction.
                 result.columns = pd.RangeIndex(len(obj._data.names))
             elif axis == 0:
-                if isinstance(obj, (pd.Series, cudf.Series)):
-                    result = cudf.Series(
+                if isinstance(obj, cudf.Series):
+                    result = cudf.Series._from_data(
                         data=obj._data.copy(deep=True),
                         index=cudf.RangeIndex(len(obj)),
                     )
+                elif isinstance(obj, pd.Series):
+                    result = cudf.Series(
+                        data=obj, index=cudf.RangeIndex(len(obj)),
+                    )
                 else:
-                    result = cudf.DataFrame(
+                    result = cudf.DataFrame._from_data(
                         data=obj._data.copy(deep=True),
                         index=cudf.RangeIndex(len(obj)),
                     )
@@ -370,7 +374,7 @@ def concat(objs, axis=0, join="outer", ignore_index=False, sort=None):
             return cudf.DataFrame()
         elif len(objs) == 1:
             obj = objs[0]
-            result = cudf.DataFrame(
+            result = cudf.DataFrame._from_data(
                 data=None if join == "inner" else obj._data.copy(deep=True),
                 index=cudf.RangeIndex(len(obj))
                 if ignore_index

python/cudf/cudf/core/series.py

@@ -408,7 +408,10 @@ def __init__(
             if dtype is not None:
                 data = data.astype(dtype)
         elif isinstance(data, ColumnAccessor):
-            name, data = data.names[0], data.columns[0]
+            raise TypeError(
+                "Use cudf.Series._from_data for constructing a Series from "
+                "ColumnAccessor"
+            )
 
         if isinstance(data, Series):
             index = data._index if index is None else index
@@ -579,7 +582,7 @@ def _get_columns_by_label(self, labels, downcast=False):
         new_data = super()._get_columns_by_label(labels, downcast)
 
         return (
-            self.__class__(data=new_data, index=self.index)
+            self.__class__._from_data(data=new_data, index=self.index)
             if len(new_data) > 0
             else self.__class__(dtype=self.dtype, name=self.name)
         )

python/cudf/cudf/tests/test_pack.py

@@ -62,7 +62,7 @@ def assert_packed_frame_equality(df):
     packed = pack(df)
     del df
     tbl = unpack(packed)
-    unpacked = DataFrame(tbl._data, tbl._index)
+    unpacked = DataFrame._from_data(tbl._data, tbl._index)
 
     assert_eq(unpacked, pdf)
 
@@ -198,14 +198,14 @@ def check_packed_pickled_equality(df):
         for b in buffers:
             assert isinstance(b, pickle.PickleBuffer)
         tbl = unpack(pickle.loads(serialbytes, buffers=buffers))
-        loaded = DataFrame(tbl._data, tbl._index)
+        loaded = DataFrame._from_data(tbl._data, tbl._index)
         assert_eq(loaded, df)
 
 
 def assert_packed_frame_picklable(df):
     serialbytes = pickle.dumps(pack(df))
     tbl = unpack(pickle.loads(serialbytes))
-    loaded = DataFrame(tbl._data, tbl._index)
+    loaded = DataFrame._from_data(tbl._data, tbl._index)
     assert_eq(loaded, df)
 
 
@@ -271,7 +271,7 @@ def assert_packed_frame_serializable(df):
     packed = pack(df)
     header, frames = packed.serialize()
     tbl = unpack(packed.deserialize(header, frames))
-    loaded = DataFrame(tbl._data, tbl._index)
+    loaded = DataFrame._from_data(tbl._data, tbl._index)
     assert_eq(loaded, df)