• If the source value does not include a valid input for this function, a missing value is returned.

• When a NUMFORMAT transform is applied, the column can be re-typed to a different data type. For example, if your format string (second parameter) is '#' (a single hash mark), then all values are rounded to the nearest integer, and the column is re-typed as Integer.

  Tip
  Tip: In general, you should format your numeric data after you have completed your computations on it. In some cases, you might lose numeric precision in converting formats, or your data can be re-typed to a different data type (e.g. Decimal to Integer).

• For more information on formatting date values, see DATEFORMAT Function.

Output: Generates a column of values from the MyNum column converted to a price format.

numeric_col

Name of the column whose Integer or Decimal data is to be formatted.

• Values with more than 20 digits after the decimal point are truncated by this function.

• Missing values for this function in the source data result in missing values in the output.
• Multiple columns and wildcards are not supported.

number_format_string

String value indicating the number format to apply to the input values.

Some key codes:

Missing values for this function in the source data result in missing values in the output.

Example - formatting price and percentages

This example steps through how to manage number formatting for price and percentage data when you have to perform some computations on the data in the application.

Source:

In this case, you need to compute sub-total and totals columns.

When this data is first imported into the Transformer page, you might notice the following:

• The data type for OrderId is an Integer, when it should be treated as String data.
• The UnitPrice, Discount , and TaxRate columns are typed as String data because of the unit characters in the values.

You can re-type the OrderId column to String without issue. If you retype the other three columns, all values are mismatched. You can use the following transforms to remove the currency and percentage notation. The first transform removes the trailing % sign from every value across all columns using a 

You can use a similar one to remove the $ sign at the beginning of values:

When both are applied, you can see that the data types of each column is updated to a numeric type: Integer or Decimal. Now, you can perform the following computations:

You can use the new SubTotal column as the basis for computing the DiscountedTotal column, which factors in discounts:

The Total column applies the tax to the DiscountedTotal column:

Because of the math operations that have been applied to the original data, your values might no longer look like dollar information. You can now apply price formatting to your columns. The following changes the number format for the SubTotal column:

Note that the leading $ was not added back to the data, which changes the data type to String. You can apply this transform to the Price, DiscountedTotal, and Total columns.

The Discount and TaxRate values should be converted to decimals. The following adjusts the Discount column:

Results:

The output data should look like the following: