Extracts the value from a column that is a specified number of rows after 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 you are working on a randomly generated sample of your dataset, the values that you see for this function might not correspond to the values that are generated on the full dataset during job execution.
- If the next value is missing or null, this function generates a missing value.
- You can use the
orderparameters 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:
window value:NEXT(myNumber, 1) order:Date
Output: Generates the new column, which contains the value in the row in the
myNumber column immediately after the current row when the dataset is ordered by
window value:NEXT(col_ref, k_integer) order: order_col [group: group_col]
|col_ref||Y||string||Name of column whose values are applied to the function|
|k_integer||Y||integer (positive)||Number of rows after the current one from which to extract the value|
For more information on the
group parameters, see Window Transform.
For more information on syntax standards, see Language Documentation Syntax Notes.
Name of the column whose values are used to extract the value that is
k-integer values after the current one.
- Multiple columns and wildcards are not supported.
|Required?||Data Type||Example Value|
|Yes||String (column reference)|
Integer representing the number of rows after the current one from which to extract the value.
- Value must be a positive integer. For negative values, see PREV Function.
k=1represents the immediately following 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
groupparameter 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.
|Required?||Data Type||Example Value|
Example - Examine prior order history
The following dataset contains order information for the preceding 12 months. You want to compare the current month's average against the preceding quarter.
ROLLINGAVERAGE function, you can generate a column containing the rolling average of the current month and the two previous months:
Note the sign of the second parameter and the
window value: ROLLINGAVERAGE(Amount, 3, 0) order: -Date
orderparameter. The sort is in the reverse order of the
Dateparameter, which preserves the current sort order. As a result, the second parameter, which identifies the number of rows to use in the calculation, must be positive to capture the previous months.
Technically, this computation does not capture the prior quarter, since it includes the current quarter as part of the computation. You can use the following column to capture the rolling average of the preceding month, which then becomes the true rolling average for the prior quarter. The
window column refers to the name of the column generated from the previous step:
Note that the order parameter must be preserved. This new column,
window value: NEXT(window, 1) order: -Date
window1, contains your prior quarter rolling average:
You can reformat this numeric value:
rename col:window1 to:'Amount_PriorQtr'
You can use the following transform to calculate the net change. This formula computes the change as a percentage of the prior quarter and then formats it as a two-digit percentage.
set col:Amount_PriorQtr value:NUMFORMAT(Amount_PriorQtr, '###.00')
derive value:NUMFORMAT(((Amount - Amount_PriorQtr) / Amount_PriorQtr) * 100, '##.##') as:'NetChangePct_PriorQtr'
NOTE: You might notice that there are computed values for
Amount_PriorQtr for February and March. These values do not factor in a full three months because the data is not present. The January value does not exist since there is no data preceding it.