derive type:single value:IF(State == 'NY','New York, New York!','some other place') as:'isNewYork'
Output: Generates a new
isNewYork column, in which each row contains the value
New York, New York! when the corresponding value in the
State column is
NY. Otherwise, the value in
some other place.
Nested IF Example:
You can build
IF statements within
IF statements as in the following example, in which the second
IF is evaluated if the first one evaluates to
derive type:single value:IF(State == 'NY',0.05,IF(State=='CA',0.08,0)) as:'CoTaxRatesByState'
A more detailed nested example is available below.
In the following, if the
test expression evaluates to
true_expression is executed. Otherwise, the
false_expression is executed.
|test_expression||Y||string||Expression that is evaluated. Must resolve to |
|true_expression||Y||string||Expression that is executed if |
|false_expression||N||string||Expression that is executed if |
All of these expressions can be constants (strings, integers, or any other supported literal value) or sophisticated elements of logic, although the test expression must evaluate to a Boolean value.
|D s lang notes|
This parameter contains the expression to evaluate. This expression must resolve to a Boolean (
|Required?||Data Type||Example Value|
|Yes||String (expression that evaluates to |
true_expression determines the value or conditional that is generated if the
test_expression evaluates to
true. If the test is
false, then the
These expressions typically generate output values and can use a combination of literals, functions, and column references.
- A true expression is required. You can insert a blank expression (
- If a false expression is not provided, false results yield a value of
|Required?||Data Type||Example Value|
See examples below.
Example - Basic Usage
derive type:single value:IF((X == Y), 'yes','no') as: 'equals'
Your output looks like the following:
Example - Stock Quotes
This example demonstrates how you can chain together multiple if/then/else conditions within a single transform step.
You have a set of stock prices that you want to analyze. Based on a set of rules, you want to determine any buy, sell, or hold action to take.
You can perform evaluations of this data using the
IF function to determine if you want to take action.
NOTE: For a larger dataset, you might maintain your buy, sell, and hold evaluations for each stock in a separate reference dataset that you join to the source dataset before performing comparisons between column values. See Join Page.
To assist in evaluation, you might first want to create columns that contain the cost (
Basis) and the current value (
CurrentValue) for each stock:
derive type:single value:(Qty * BuyPrice) as:'Basis'
derive type:single value:(Qty * CurrentPrice) as:'CurrentValue'
Now, you can build some rules based on the spread between
IF version: In this case, the most important action is determining if it is time to sell. The following rule writes a
sell notification if the current value is $1000 or more than the cost. Otherwise, no value is written to the action column.
derive type:single value: IF((CurrentValue - 1000 > Basis), 'sell','') as:'action'
IF version: But what about buying more? The following transform is an edit to the previous one. In this new version, the sell test is performed, and if
false, writes a
buy action if the
CurrentPrice is within 10% of the
This second evaluation is performed after the first one, as it replaces the else clause, which did nothing in the previous version. In the Recipe Panel, click the previous transform and edit it, replacing it with the new version:
derive type:single value: IF((CurrentValue - 1000 > Basis), 'sell', IF((abs(CurrentValue - Basis) <= (Basis * 0.1)),'buy','hold')) as:'action'
If neither test evaluates to
true, the written action is
You might want to format some of your columns using dollar formatting, as in the following:
NOTE: The following formatting inserts a dollar sign ($) in front of the value, which changes the data type to String.
set col:BuyPrice value:NUMFORMAT(BuyPrice, '$ ##,###.00')
After moving your columns, your dataset should look like the following, if you completed the number formatting steps:
|GOOG||10||705.25||$ 674.50||$ 7,052.50||$ 6,745.00||buy|
|FB||100||84.00||$ 101.13||$ 8,400.00||$ 10,112.50||sell|
|AAPL||50||125.25||$ 97.38||$ 6,262.50||$ 4,868.75||hold|
|MSFT||100||38.88||$ 45.25||$ 3,887.50||$ 4,525.00||hold|
|D s also|