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Extracts the value from a column that is a specified number of rows before the current value.

  • The row from which to extract a value is determined by the order in which the rows are organized at the time that the transform is executed. 

  • If the previous value is missing or null, this function generates a missing value.
  • You can use the group and order parameters to define the groups of records and the order of those records to which this transform is applied. 
  • This function works with the following transforms:

Basic Usage

window value:PREV(myNumber, 1) order:Date

Output: Generates the new column, which contains the value in the row in the myNumber column immediately preceding the current row, when ordered by Date.

Syntax

window value:PREV(col_ref, k_integer) order: order_col [group: group_col]

ArgumentRequired?Data TypeDescription
col_refYstringName of column whose values are applied to the function
k_integerYinteger (positive)Number of rows before the current one from which to extract the value

For more information on the order and group parameters, see Window Transform.

For more information on syntax standards, see Language Documentation Syntax Notes.

col_ref

Name of the column whose values are used to extract the value that is k-integer values before the current one.

  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
YesString (column reference)myColumn

k_integer

Integer representing the number of rows before the current one from which to extract the value.

  • Value must be a positive integer. For negative values, see NEXT Function.
  • k=1 represents the immediately preceding row value.
  • If k is greater than or equal to the number of values in the column, all values in the generated column are missing. If a group parameter is applied, then this parameter should be no more than the maximum number of rows in the groups.
  • If the range provided to the function exceeds the limits of the dataset, then the function generates a null value.
  • If the range of the function is valid but includes missing values, the function generates a missing, non-null value.

Usage Notes:

 

Required?Data TypeExample Value
YesInteger4

Examples

Example - Examine prior order history

The following dataset contains orders for multiple customers over a period of a few days, listed in no particular order. You want to assess how order size has changed for each customer over time and to provide offers to your customers based on changes in order volume.

Source:

DateCustIdOrderIdOrderValue
1/4/16C001Ord002500
1/11/16C003Ord005200
1/20/16C002Ord007300
1/21/16C003Ord008400
1/4/16C001Ord001100
1/7/16C002Ord003600
1/8/16C003Ord004700
1/21/16C002Ord009200
1/15/16C001Ord006900

Transform:

When the data is loaded into the Transformer page, you can use the PREV function to gather the order values for the previous two orders into a new column. The trick is to order the window transform by the date and group it by customer:

window value: PREV(OrderValue, 1) order: Date group: CustId

window value: PREV(OrderValue, 2) order: Date group: CustId

rename col: window to: 'OrderValue_1'

rename col: window1 to: 'OrderValue_2'

You should now have the following columns in your dataset: DateCustIdOrderIdOrderValueOrderValue_1OrderValue_2.

The two new columns represent the previous order and the order before that, respectively. Now, each row contains the current order (OrderValue) as well as the previous orders. Now, you want to take the following customer actions:

  • If the current order is more than 20% greater than the sum of the two previous orders, send a rebate.
  • If the current order is less than 90% of the sum of the two previous orders, send a coupon. 
  • Otherwise, send a holiday card.

To address the first one, you might add the following, which uses the IF function to test the value of the current order compared to the previous ones: 

derive value: IF(OrderValue >= (1.2 * (OrderValue_1 + OrderValue_2))),'send rebate','no action') as:'CustomerAction'

You can now see which customers are due a rebate. Now, edit the above and replace it with the following, which addresses the second condition. If neither condition is valid, then the result is send holiday card.

derive value:IF(OrderValue >= (1.2 * (OrderValue_1 + OrderValue_2)),'send rebate', IF(OrderValue <= (0.9 * (OrderValue_1 + OrderValue_2)), 'send coupon', send holiday card')) as:'CustomerAction'

Results:

After you drop the OrderValue_1 and OrderValue_2 columns, your dataset should look like the following. Note that since the transforms with PREV functions grouped by CustId, the order of records has changed.

DateCustIdOrderIdOrderValueCustomerAction
1/4/16C001Ord001100send rebate
1/7/16C001Ord002500send rebate
1/15/16C001Ord006900send rebate
1/8/16C003Ord004700send rebate
1/11/16C003Ord005200send rebate
1/21/16C003Ord008400send coupon
1/7/16C002Ord003600send rebate
1/20/16C002Ord007300send rebate
1/21/16C002Ord009200send coupon

 

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