h2o-py/h2o/pipeline/mojo_pipeline.py
def transform(self, data, allow_timestamps=False):
        """
        Transform H2OFrame using a MOJO Pipeline.

        :param data: Frame to be transformed.
        :param allow_timestamps: Allows datetime columns to be used directly with MOJO pipelines. It is recommended
        to parse your datetime columns as Strings when using pipelines because pipelines can interpret certain datetime
        formats in a different way. If your H2OFrame is parsed from a binary file format (eg. Parquet) instead of CSV
        it is safe to turn this option on and use datetime columns directly.

        :returns: A new H2OFrame.
        """
        assert_is_type(data, H2OFrame)
        assert_is_type(allow_timestamps, bool)
        return H2OFrame._expr(ExprNode("mojo.pipeline.transform", self.pipeline_id[0], data, allow_timestamps))
def transform(self, data, allow_timestamps=False):
        assert_is_type(data, H2OFrame)
        assert_is_type(allow_timestamps, bool)
        return H2OFrame._expr(ExprNode("mojo.pipeline.transform", self.pipeline_id[0], data, allow_timestamps))
def transform ( self , data , allow_timestamps = False ) : assert_is_type ( data , H2OFrame ) assert_is_type ( allow_timestamps , bool ) return H2OFrame . _expr ( ExprNode ( "mojo.pipeline.transform" , self . pipeline_id [ 0 ] , data , allow_timestamps ) )
Transform H2OFrame using a MOJO Pipeline.

        :param data: Frame to be transformed.
        :param allow_timestamps: Allows datetime columns to be used directly with MOJO pipelines. It is recommended
        to parse your datetime columns as Strings when using pipelines because pipelines can interpret certain datetime
        formats in a different way. If your H2OFrame is parsed from a binary file format (eg. Parquet) instead of CSV
        it is safe to turn this option on and use datetime columns directly.

        :returns: A new H2OFrame.
Transform H2OFrame using a MOJO Pipeline .