Unpivoting data can be regarded as the opposite to the pivoting process. This might not come as a surprise considering the unpivoting process is all about rotating the data to get rows from a given number of columns. However, the original columns names are stored as a value in the rows of a new, unpivoted column.
For your data science project code to be prepared for multiple database management systems, it is highly advisable that you make use of the standard ANSI SQL expressions only. Fortunately, you can pull this off successfully with a cross join of the original table using tabular expression in the FROM clause. It is then that you can make use of the CASE expression if you’re to extract the correct value for each year.
Remember, the design of the UNPIVOT operator entails an implicit elimination of results rows having a NULL in the values column. The good news is you may not have to do anything special to get done with everything. What will suit you perfectly is if the UNPIVOT operator had an optional clause that allows you to specify whether you want to keep NULLS or remove it.
The Bottom Line
There you have it, some of the things you need to know about UNPIVOT data for data science in SQL server. If you are still having doubts, then it would be better to seek the help of experts in the field. Through this action, you’re certainly going to get every piece of information you need. Be sure to ask any question you might have in mind before moving on to the next step.