Example

In this example, we will pass a NOT null value to the function transformation object using a Variables object.

Where,

val = ABCDEFG

In the output, you can see that the Boolean value, True, has been returned. This means the provided value is NOT null. There is data present in the Input field.

Example

In this example, we will pass a string value, not a real number, to the function transformation object using a Variables object.

Where,

value = -√5

In the output window, you can see that the Boolean value, False, has been returned as the specified value is not a real number, rather an irrational value.

Example

In this example, we will pass a valid date parameter to the function transformation object using a Variables object.

Where,

value = 01/01/2001

In the output, you can see that the Boolean value, True, has been returned. This means the provided value represents a valid date.

Example

We have a Customers dataset, with missing values in the Items and ShipCountry fields, which we will use for this function.

We will map these fields to value1 and value2 of the function transformation object.

Where,

value1 = Items

value2 = ShipCountry

Then, we will map the Output value field of the function transformation object and the remaining fields from our source file to an Excel Workbook Destination.

Right-click on the Excel Workbook Destination object and select Preview Output. You can see that Astera Data Stack has created a new column, and returned a value from either Items (value1), ShipCountry (value2), or null (if both specified parameters are null), in this particular order.

Example

We have a Customers dataset which we will use to evaluate and transform the Items field.

In this example we will use the Expression object to define the condition, and a Variables object to define a real thenValue and a real elseValue.

Where,

Condition: Items = “1”

thenValue = 1.23

elseValue ­ = 2.23

In the output, you can see that real values, 1.23 and 2.23, have been returned depending on whether the Items field condition was met.

Example

In this example, we will pass various SQL DateTime values to the function transformation object using a Variables object, along with the Normalize object so that different values can be passed to the function transformation object at once.

Where,

date1 = 1 January, 2003

date2 = January, 2003

date3 = 1/2/1991

date4 = 1991/2/4

date5 = 0000/00/00

In the output window, you can see that the Boolean value, True, has been returned for values that are present in the valid SQL server DateTime range, and the value, False, has been returned otherwise.

Example

In this example, we will pass a valid format parameter and a string date parameter to match the given format, to the function transformation object using a Variables object.

Where,

format = yyyy-MM-dd

str = 2023-09-23

In the output, you can see that the Boolean value, True, has been returned. This means the provided value represents a valid date which matches the provided date format.

Example

We have a Customers dataset which we will use to evaluate and transform the ShipDate field.

In this example we will use the Expression object to define the condition, and a Variables object to define thenValue and elseValue.

Where,

Condition: ShipDate = “1”

thenValue = 1/2/2022

elseValue ­ = 5/7/2023

In the output, you can see that DateTime values, 1/2/2022 and 5/7/2023, have been returned depending on whether the ShipDate field condition was met.

Example

We have a Customers dataset which we will use to evaluate whether the Country field consists of the value “Germany”.

We will use the Expression object to give this condition, and a Variables object to define thenValue and elseValue.

Where,

Condition: Country = “Germany”

thenValue = True

elseValue ­ = False

In the output, you can see that Boolean values, True and false, have been returned depending on whether the Country field condition was met.

Example

In this example, we are passing the required parameters to the function transformation object using a Variables object.

Where,

LookFor = C

LookIn = A,B,C,D,E,F,G

Right-click on the function transformation object and select Preview Output. You can see that Astera Data Stack has returned the Boolean value, True, indicating that the LookFor value exists in the comma separated LookIn string.

Conversely, if we replace the lookFor value with “3”, you can see that Astera Data Stack has returned the Boolean value, False.

Example

We have a Customers dataset which we will use to evaluate and transform the Items field.

In this example we will use the Expression object to define the condition, and a Variables object to define thenValue and elseValue.

Where,

Condition: Items = “1”

thenValue = 100

elseValue ­ = 200

In the output, you can see that Integer values, 100 and 200, have been returned depending on whether the Items field condition was met.

Example

We have a Customers dataset which we will use to evaluate and transform the Items field.

In this example we will use the Expression object to define the condition, and a Variables object to define a string thenValue and a string elseValue.

Where,

Condition: Items = “1”

thenValue = FirstItem

elseValue ­ = SecondItem

In the output, you can see that string values, FirstItem and SecondItem, have been returned depending on whether the Items field condition was met.

Example

In this example, we will pass a numeric, real value to the function transformation object using a Variables object.

Where,

value = 3.123456789

In the output window, you can see that the Boolean value, True, has been returned as the specified value is numeric.

Similarly, the Boolean value, False, will be returned if the specified value is not numeric, as shown in the example below:

Example

In this example, we will pass a null value to the function transformation object using a Variables object.

In the output, you can see that the Boolean value, True, has been returned as the passed value was empty or null.

Example

In this example, we will first pass an integer value and then a non-integer value to the function transformation object using a Variables object, to see the different outputs

Where first,

value = 12345678

then,

value = ABCDEFG

In the output windows, you can see that Boolean values, True and False, have been returned, depending on whether the provided value was an integer or a non-integer value.

Example

In this example, we will pass a NOT null value to the function transformation object using a Variables object.

Where,

val = ABCDEFG

In the output, you can see that the Boolean value, False, has been returned. This means the provided value is NOT null. There is data present in the Input field.

Example

In this example, we will pass a whitespace value to the function transformation object using a Variables object.

In the output, you can see that the Boolean value, True, has been returned as the passed value consisted of whitespaces. If the same variable was passed through the IsNullOrEmpty function, The output would be false.