Update datatable usage

python-package/xgboost/compat.py

@@ -49,7 +49,11 @@ class DataFrame(object):
 
 # dt
 try:
-    from datatable import DataTable
+    import datatable
+    if hasattr(datatable, "Frame"):
+        DataTable = datatable.Frame
+    else:
+        DataTable = datatable.DataTable
     DT_INSTALLED = True
 except ImportError:
 

python-package/xgboost/core.py

@@ -287,10 +287,10 @@ def _maybe_dt_data(data, feature_names, feature_types):
         return data, feature_names, feature_types
 
     data_types_names = tuple(lt.name for lt in data.ltypes)
-    if not all(type_name in DT_TYPE_MAPPER for type_name in data_types_names):
-        bad_fields = [data.names[i] for i, type_name in
-                      enumerate(data_types_names) if type_name not in DT_TYPE_MAPPER]
-
+    bad_fields = [data.names[i]
+                  for i, type_name in enumerate(data_types_names)
+                  if type_name not in DT_TYPE_MAPPER]
+    if bad_fields:
         msg = """DataFrame.types for data must be int, float or bool.
                 Did not expect the data types in fields """
         raise ValueError(msg + ', '.join(bad_fields))
@@ -317,7 +317,7 @@ def _maybe_dt_array(array):
 
     # below requires new dt version
     # extract first column
-    array = array.tonumpy()[:, 0].astype('float')
+    array = array.to_numpy()[:, 0].astype('float')
 
     return array
 
@@ -340,7 +340,7 @@ def __init__(self, data, label=None, missing=None,
         """
         Parameters
         ----------
-        data : string/numpy array/scipy.sparse/pd.DataFrame/DataTable
+        data : string/numpy.array/scipy.sparse/pd.DataFrame/dt.Frame
             Data source of DMatrix.
             When data is string type, it represents the path libsvm format txt file,
             or binary file that xgboost can read from.
@@ -497,16 +497,20 @@ def _init_from_npy2d(self, mat, missing, nthread):
 
     def _init_from_dt(self, data, nthread):
         """
-        Initialize data from a DataTable
+        Initialize data from a datatable Frame.
         """
-        cols = []
         ptrs = (ctypes.c_void_p * data.ncols)()
-        for icol in range(data.ncols):
-            col = data.internal.column(icol)
-            cols.append(col)
-            # int64_t (void*)
-            ptr = col.data_pointer
-            ptrs[icol] = ctypes.c_void_p(ptr)
+        if hasattr(data, "internal") and hasattr(data.internal, "column"):
+            # datatable>0.8.0
+            for icol in range(data.ncols):
+                col = data.internal.column(icol)
+                ptr = col.data_pointer
+                ptrs[icol] = ctypes.c_void_p(ptr)
+        else:
+            # datatable<=0.8.0
+            from datatable.internal import frame_column_data_r
+            for icol in range(data.ncols):
+                ptrs[icol] = frame_column_data_r(data, icol)
 
         # always return stypes for dt ingestion
         feature_type_strings = (ctypes.c_char_p * data.ncols)()