Formats a numeric set of values according to the specified number formatting. Source values can be a literal value, a function returning a numeric value, or reference to a column containing Integer or Decimal values. |
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: 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). |
supports a wide variety of number formats, following Java standards. For more information, please see Java's documentation.
NOTE: This function just changes how the underlying cell value is displayed. If you round the value to a specific level of precision, please use the ROUND function. See ROUND Function. |
numformat(MyPrice, '$###,###.##') |
Output: Returns the values from the MyPrice column converted to a price format.
numformat(numeric_val, number_format_string) |
| Argument | Required? | Data Type | Description |
|---|---|---|---|
| numeric_val | Y | string, integer, or decimal | Literal value, function returning a numeric value, or name of Integer or Decimal column whose values are to be formatted |
| number_format_string | Y | string | Literal value of the number formatting string to apply |
Literal numeric value, a function that returns a numeric value, or the 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.
| Required? | Data Type | Example Value |
|---|---|---|
| Yes | String (column reference), function, or Integer or Decimal literal | MyPrice |
String value indicating the number format to apply to the input values.
NOTE: You cannot create number format strings in which a |
Some key codes:
| Code | Description | Example Format String | Example Inputs | Example Outputs |
|---|---|---|---|---|
| # | Insert a digit if it is present in the data. |
| 99 999 1000 10000 | 99 999 1,000 10,000 |
| 0 | Insert a digit even if it is not present in a data. | '00.##' | 20 7.1 | 20 07.1 |
| $ | You can add constants values to the expression. Whitespace is respected. For example, you can insert currency markers at the beginning of your expression. | '$ ##.##' | 20 2514.22 6.6666 | $ 20 $ 2514.22 $ 6.67 |
| % | Percentage expressions can be at the back of the number formatting expression. | '##.## %' | 20 2514.22 6.6666 | 20 % 2514.22 % 6.67% |
supports Java number formatting strings, with some exceptions.
Missing values for this function in the source data result in missing values in the output.
| Required? | Data Type | Example Value |
|---|---|---|
| Yes | String | '#.#' |
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.
| OrderId | Qty | UnitPrice | Discount | TaxRate |
|---|---|---|---|---|
| 1001 | 5 | $25.00 | 0% | 8.25% |
| 1002 | 15 | $39.99 | 5% | 8.25% |
| 1003 | 2 | $99.99 | 15% | 8.25% |
| 1004 | 100 | $999.99 | 0% | 8.25% |
Transformation:
When this data is first imported into the Transformer page, you might notice the following:
OrderId is an Integer, when it should be treated as String data.UnitPrice, Discount , and TaxRate columns are typed as String data because of the unit characters in the values.NOTE: Where possible, remove currency and three-digit separators from your numeric data prior to import. |
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.
NOTE: The data types for your columns should match the expected inputs for your downstream analytics system. |
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:
| OrderId | Qty | UnitPrice | SubTotal | Discount | DiscountedTotal | TaxRate | Total |
|---|---|---|---|---|---|---|---|
| 1001 | 5 | 25.00 | 125.00 | 0 | 125.00 | 0.0825 | 135.31 |
| 1002 | 15 | 39.99 | 599.85 | 0.05 | 569.86 | 0.0825 | 616.87 |
| 1003 | 2 | 99.99 | 199.98 | 0.15 | 169.98 | 0.0825 | 184.01 |
| 1004 | 100 | 999.99 | 99999.00 | 0 | 99999.00 | 0.0825 | 108248.92 |
See Also |