Outputting Different Rows from Different Columns of the Same SQL Table

Introduction

When working with SQL tables, it’s not uncommon to encounter requirements where you need to retrieve data from specific columns while excluding rows that contain zeros or other values you don’t want to consider. In this article, we’ll delve into a problem where we need to output different rows from different columns of the same table, but only for those rows that have non-zero values.

Problem Statement

The given problem statement is as follows:

I’m trying to calculate running averages of past 4th month. So I need to get the 4th value of each month. Here’s an example SQL table:

The expected output would be:

Solution Approach

One possible approach to solve this problem is by using window functions. The idea is to assign a rank to each row within its respective group (i.e., Month 1, Month 2, etc.) based on non-zero values. Then, we can use conditional aggregation to extract the desired output.

Here’s a step-by-step explanation of the solution:

Assigning Ranks

First, we need to assign a rank to each row within its respective group (Month 1, Month 2, etc.). We can do this using the MIN function with a CASE statement that checks for non-zero values. This will give us the minimum rank for each column.

min(case when month1 <> 0 then rank end) over () as month1_rank0,
min(case when month2 <> 0 then rank end) over () as month2_rank0,
min(case when month3 <> 0 then rank end) over () as month3_rank0,
min(case when month4 <> 0 then rank end) over () as month4_rank0

Conditional Aggregation

Next, we’ll use conditional aggregation to extract the desired output. We want to get the fourth value of each month, but only for rows that have non-zero values in at least one column.

We can achieve this by using the MAX function with a CASE statement that checks if the rank is equal to 0 (i.e., no non-zero values). If so, we add 3 to the original value and take the maximum. This effectively “shifts” the fourth value to the desired position.

max(case when rank = month1_rank0 + 3 then month1 end) as month1,
max(case when rank = month2_rank0 + 3 then month2 end) as month2,
max(case when rank = month3_rank0 + 3 then month3 end) as month3,
max(case when rank = month4_rank0 + 3 then month4 end) as month4

Full SQL Query

Here’s the complete SQL query that solves the problem:

SELECT 
  max(case when rank = month1_rank0 + 3 then month1 end) as month1,
  max(case when rank = month2_rank0 + 3 then month2 end) as month2,
  max(case when rank = month3_rank0 + 3 then month3 end) as month3,
  max(case when rank = month4_rank0 + 3 then month4 end) as month4
FROM 
(
  SELECT t.*,
         min(case when month1 <> 0 then rank end) over () as month1_rank0,
         min(case when month2 <> 0 then rank end) over () as month2_rank0,
         min(case when month3 <> 0 then rank end) over () as month3_rank0,
         min(case when month4 <> 0 then rank end) over () as month4_rank0
  FROM t
) t

Conclusion

In this article, we explored a problem where we needed to output different rows from different columns of the same SQL table, but only for those rows that have non-zero values. We solved this problem using window functions and conditional aggregation. By assigning ranks to each row within its respective group and then using maximum values with case statements, we were able to extract the desired output.

This approach can be applied to various real-world scenarios where you need to process data in a specific way based on certain conditions. It’s an essential skill for any SQL developer or data analyst to master.

Last modified on 2023-07-29