In teradatamlspk, the output column name for the columns passed as column expression to unpivot is different in the output DataFrame compared with PySpark.
PySpark
>>> df.unpivot(df.accounts, [(df.Jan*2)+df.Feb], "var", "val").show()
+----------+-----------------+-----+ | accounts| var| val| +----------+-----------------+-----+ | Red Inc|((Jan * 2) + Feb)|500.0| | Alpha Co|((Jan * 2) + Feb)|610.0| |Yellow Inc|((Jan * 2) + Feb)| NULL| |Orange Inc|((Jan * 2) + Feb)| NULL| | Blue Inc|((Jan * 2) + Feb)|190.0| | Jones LLC|((Jan * 2) + Feb)|500.0| +----------+-----------------+-----+
teradatamlspk
>>> df.unpivot(df.accounts, [(df.Jan*2)+df.Feb], "var", "val").show()
+----------+-------------+-----+ | accounts| var| val| +----------+-------------+-----+ | Red Inc|Jan * 2 + Feb|500.0| | Alpha Co|Jan * 2 + Feb|610.0| |Yellow Inc|Jan * 2 + Feb| None| |Orange Inc|Jan * 2 + Feb| None| | Blue Inc|Jan * 2 + Feb|190.0| | Jones LLC|Jan * 2 + Feb|500.0| +----------+-------------+-----+