This section provides an overview of how to perform mathematical operations between columns. |
Before you begin, you should verify that the data types of the two columns match. Check the icon in the upper left of each column to verify that they match.
To change the data type, you can:
After setting data types, you should address any missing or mismatched values in the column. For example, if you change a column's data type from Decimal to Integer, values that contain decimal points may be reported as mismatched values. Use the ROUND
function to round them to the nearest integer.
Tip: You can use the |
You can express mathematical operations using numeric operators or function references. The following two examples perform the same operation, creating a third column that sums the first two.
Numeric Operators:
Math Functions:
NOTE: Expressions containing numeric operators can contain more than two column references or values, as well as nested expressions. Math functions support two references only. |
To perform math operations, you can use the Edit column with formula transformation to update values in a column based on a math operation. The following transformation multiplies the column by 10 and adds the value of colB
:
All values in colA
are modified based on this operation.
You can use the Edit column with formula transformation to perform math operations based on a condition you define. In the following step, the Cost
column is replaced reduced by 10% if the Qty
column is more than 100. The expression is rounded down to the nearest integer, so that the type of the column (Integer) is not changed:
For rows in which Qty
is less than 100, the value of Cost
is written back to the column (no change).
To create a new column in which a math operation is performed on two other columns, use the New Formula transformation. The following multiplies Qty
and UnitPrice to yield Cost:
If you need to work with more than two columns, numeric operators allow you to reference any number of columns and static values in a single expression.
However, you should be careful to avoid making expressions that are too complex, as they can be difficult to parse and debug.
Tip: When performing complex mathematic operations, you may want to create a new column to contain the innermost computations of your expression. Then, you can reference this column in the subsequent step, which generates the full expression. In this manner, you can build complex equations in a way that is easier to understand for other users of the recipe. The final step is to delete the generated column. |
If you are concatenating string-based content between multiple columns, use the Merge Columns transformation. In the following example, the Merge Columns transformation is used to bring together the order ID (ordId
) and product ID (prodId
) columns, with the dash character used as the delimiter between the two column values:
Tip: This method can be used for columns of virtually any type. Change the data type of each column to String and then perform the merge operation. |
Array column types can be concatenated with the ARRAYCONCAT function.
Tip: You can also use the MERGE function to accomplish the above actions. The function method is useful if you are performing a separate transformation action on the data involved. For example, you could use the function if you are using the Edit formula column to modify a column in place. |
You can use aggregate functions to perform mathematic operations on sets of rows. Aggregated rows are collapsed and grouped based on the functions that you apply to them.