How to implement column to row in sql
There are two ways to implement column-to-line conversion operations in SQL: use the UNION operator to realize column-to-line conversion by vertically merging the query results. Use the PIVOT function to convert column data into row data, where the syntax of the PIVOT function is: PIVOT ( aggregate_function(column_name) FOR pivot_column_name IN (value1, value2, ...) ) FROM table_name
Implement column-to-line operation in SQL
Column-to-row operation, also known as "deconstruction" or "cross-tab", refers to converting multiple columns of data in a table into single column row data. In SQL, this operation can be achieved through the UNION operator or the PIVOT function.
Use UNION operator
The UNION operator can vertically merge multiple query results to achieve the effect of column-to-line conversion. Here is an example:
<code class="sql">SELECT * FROM table_name UNION SELECT * FROM table_name WHERE column_name1 IS NOT NULL UNION SELECT * FROM table_name WHERE column_name2 IS NOT NULL;</code>
Using PIVOT functions
The PIVOT function is specifically used to convert data layouts and can convert column data into row data. The syntax is as follows:
<code class="sql">PIVOT ( aggregate_function(column_name) FOR pivot_column_name IN (value1, value2, ...) ) FROM table_name;</code>
in:
-
aggregate_function
: The aggregate function to be applied to the transform column data, such as SUM, COUNT, or MAX. -
pivot_column_name
: The column name used as the row header. -
value1
,value2
, ...: Specifies the column value to be converted.
Example
Suppose we have a table called orders
with the following columns:
-
order_id
-
product_name
-
quantity
-
sale_date
To convert product_name
column to a row, use the PIVOT
function:
<code class="sql">SELECT order_id, sale_date, SUM(quantity) AS quantity FROM orders PIVOT ( SUM(quantity) FOR product_name IN ('Product A', 'Product B', 'Product C') );</code>
This will produce the following output:
order_id | sale_date | quantity_Product A | quantity_Product B | quantity_Product C |
---|---|---|---|---|
1 | 2023-01-01 | 10 | 15 | 20 |
2 | 2023-01-02 | 5 | 10 | 15 |
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