--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-2-4ccc77889de6> in <module>() 2 (Vectors.dense([0.0, 0.0])), 3 (Vectors.dense([0.6, -1.1]))], ----> 4 ["features"]) /databricks/spark/python/pyspark/sql/context.pyc in createDataFrame(self, data, schema, samplingRatio) 423 rdd, schema = self._createFromRDD(data, schema, samplingRatio) 424 else: --> 425 rdd, schema = self._createFromLocal(data, schema) 426 jrdd = self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd()) 427 jdf = self._ssql_ctx.applySchemaToPythonRDD(jrdd.rdd(), schema.json()) /databricks/spark/python/pyspark/sql/context.pyc in _createFromLocal(self, data, schema) 339 340 if schema is None or isinstance(schema, (list, tuple)): --> 341 struct = self._inferSchemaFromList(data) 342 if isinstance(schema, (list, tuple)): 343 for i, name in enumerate(schema): /databricks/spark/python/pyspark/sql/context.pyc in _inferSchemaFromList(self, data) 239 warnings.warn("inferring schema from dict is deprecated," 240 "please use pyspark.sql.Row instead") --> 241 schema = reduce(_merge_type, map(_infer_schema, data)) 242 if _has_nulltype(schema): 243 raise ValueError("Some of types cannot be determined after inferring") /databricks/spark/python/pyspark/sql/types.pyc in _infer_schema(row) 831 raise TypeError("Can not infer schema for type: %s" % type(row)) 832 --> 833 fields = [StructField(k, _infer_type(v), True) for k, v in items] 834 return StructType(fields) 835 /databricks/spark/python/pyspark/sql/types.pyc in _infer_type(obj) 808 return _infer_schema(obj) 809 except TypeError: --> 810 raise TypeError("not supported type: %s" % type(obj)) 811 812 TypeError: not supported type: <type 'numpy.ndarray'>