How to Replace NULL Values in a Row with a Previous Known Value in SQL
In database management, situations may arise where NULL values need to be replaced with meaningful data. One common scenario is when data is missing in a column and needs to be inferred from neighboring rows.
Consider a table with two columns, 'date' and 'number':
date number ---- ------ 1 3 2 NULL 3 5 4 NULL 5 NULL 6 2
The goal is to replace the NULL values in the 'number' column with the most recent non-NULL value from the 'date' column. This implies that if the 'number' for date 2 is NULL, it should be replaced with 3 (the previous known value). Similarly, the NULL values in date 4 and 5 should be replaced with 5.
In SQL Server, the following query can be used to achieve this:
DECLARE @Table TABLE( ID INT, Val INT ) INSERT INTO @Table (ID,Val) SELECT 1, 3 INSERT INTO @Table (ID,Val) SELECT 2, NULL INSERT INTO @Table (ID,Val) SELECT 3, 5 INSERT INTO @Table (ID,Val) SELECT 4, NULL INSERT INTO @Table (ID,Val) SELECT 5, NULL INSERT INTO @Table (ID,Val) SELECT 6, 2 SELECT *, ISNULL(Val, (SELECT TOP 1 Val FROM @Table WHERE ID <p>The query employs a subquery to find the first non-NULL value in the 'Val' column for each row with a NULL value. The ISNULL function is then used to replace the NULL value with the selected non-NULL value.</p><p>The result of the query is as follows:</p><pre class="brush:php;toolbar:false">date number ---- ------ 1 3 2 3 3 5 4 5 5 5 6 2
The NULL values in the 'number' column have been successfully replaced with the most recent non-NULL value from the 'date' column. This technique can be useful for filling in missing data and ensuring data integrity in various database scenarios.
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