Allow import via python datatable. (#3272)

* Allow import via python datatable.

* Write unit tests

* Refactor dt API functions

* Refactor python code

* Lint fixes

* Address review comments

tests/python/test_dt.py

@@ -0,0 +1,47 @@
+# -*- coding: utf-8 -*-
+import unittest
+
+import testing as tm
+import xgboost as xgb
+
+try:
+    import datatable as dt
+    import pandas as pd
+except ImportError:
+    pass
+
+tm._skip_if_no_dt()
+tm._skip_if_no_pandas()
+
+
+class TestDataTable(unittest.TestCase):
+
+    def test_dt(self):
+        df = pd.DataFrame([[1, 2., True], [2, 3., False]], columns=['a', 'b', 'c'])
+        dtable = dt.Frame(df)
+        labels = dt.Frame([1, 2])
+        dm = xgb.DMatrix(dtable, label=labels)
+        assert dm.feature_names == ['a', 'b', 'c']
+        assert dm.feature_types == ['int', 'float', 'i']
+        assert dm.num_row() == 2
+        assert dm.num_col() == 3
+
+        # overwrite feature_names
+        dm = xgb.DMatrix(dtable, label=pd.Series([1, 2]),
+                         feature_names=['x', 'y', 'z'])
+        assert dm.feature_names == ['x', 'y', 'z']
+        assert dm.num_row() == 2
+        assert dm.num_col() == 3
+
+        # incorrect dtypes
+        df = pd.DataFrame([[1, 2., 'x'], [2, 3., 'y']], columns=['a', 'b', 'c'])
+        dtable = dt.Frame(df)
+        self.assertRaises(ValueError, xgb.DMatrix, dtable)
+
+        df = pd.DataFrame({'A=1': [1, 2, 3], 'A=2': [4, 5, 6]})
+        dtable = dt.Frame(df)
+        dm = xgb.DMatrix(dtable)
+        assert dm.feature_names == ['A=1', 'A=2']
+        assert dm.feature_types == ['int', 'int']
+        assert dm.num_row() == 3
+        assert dm.num_col() == 2