Contents:
Generates a new column containing the row number as sorted by the
order parameter and optionally grouped by the group parameter.Tip: To generate row identifiers by the original order in the source data, use the $sourcerownumber reference. See Source Metadata References.
This function works with the following transforms:
Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.
Basic Usage
Example:
rownumber()
Output: Returns the row number of each row.
Example with grouping:
rownumber() order:Date group:QTR
Output: Returns the row number of each row as ordered by the values in the Date column grouped by the QTR values. For each quarter value, the row number counter resets.
Syntax and Arguments
rownumber() order: order_col [group: group_col]
For more information on the order and group parameters, see Window Transform.
For more information on syntax standards, see Language Documentation Syntax Notes.
Tip: For additional examples, see Common Tasks.
Examples
Example - Rolling window functions
Functions:
| Item | Description |
|---|---|
| ROLLINGSUM Function | Computes the rolling sum of values forward or backward of the current row within the specified column. |
| ROLLINGAVERAGE Function | Computes the rolling average of values forward or backward of the current row within the specified column. |
| ROWNUMBER Function |
Generates a new column containing the row number as sorted by the order parameter and optionally grouped by the group parameter.
|
Also:
| Item | Description |
|---|---|
| MONTH Function | Derives the month integer value from a Datetime value. Source value can be a a reference to a column containing Datetime values or a literal. |
| FLOOR Function | Computes the largest integer that is not more than the input value. Input can be an Integer, a Decimal, a column reference, or an expression. |
| ROWNUMBER Function |
Generates a new column containing the row number as sorted by the order parameter and optionally grouped by the group parameter.
|
The following dataset contains sales data over the final quarter of the year.
Source:
| Date | Sales |
|---|---|
| 10/2/16 | 200 |
| 10/9/16 | 500 |
| 10/16/16 | 350 |
| 10/23/16 | 400 |
| 10/30/16 | 190 |
| 11/6/16 | 550 |
| 11/13/16 | 610 |
| 11/20/16 | 480 |
| 11/27/16 | 660 |
| 12/4/16 | 690 |
| 12/11/16 | 810 |
| 12/18/16 | 950 |
| 12/25/16 | 1020 |
| 1/1/17 | 680 |
Transformation:
First, you want to maintain the row information as a separate column. Since data is ordered already by the Date column, you can use the following:
| Transformation Name | Window |
|---|---|
| Parameter: Formulas | ROWNUMBER() |
| Parameter: Order by | Date |
Rename this column to rowId for week of quarter.
Now, you want to extract month and week information from the Date values. Deriving the month value:
| Transformation Name | New formula |
|---|---|
| Parameter: Formula type | Single row formula |
| Parameter: Formula | MONTH(Date) |
| Parameter: New column name | 'Month' |
Deriving the quarter value:
| Transformation Name | New formula |
|---|---|
| Parameter: Formula type | Single row formula |
| Parameter: Formula | (1 + FLOOR(((month-1)/3))) |
| Parameter: New column name | 'QTR' |
Deriving the week-of-quarter value:
| Transformation Name | Window |
|---|---|
| Parameter: Formulas | ROWNUMBER() |
| Parameter: Group by | QTR |
| Parameter: Order by | Date |
Rename this column WOQ (week of quarter).
Deriving the week-of-month value:
| Transformation Name | Window |
|---|---|
| Parameter: Formulas | ROWNUMBER() |
| Parameter: Group by | Month |
| Parameter: Order by | Date |
Rename this column WOM (week of month).
Now, you perform your rolling computations. Compute the running total of sales using the following:
| Transformation Name | Window |
|---|---|
| Parameter: Formulas | ROLLINGSUM(Sales, -1, 0) |
| Parameter: Group by | QTR |
| Parameter: Order by | Date |
The -1 parameter is used in the above computation to gather the rolling sum of all rows of data from the current one to the first one. Note that the use of the QTR column for grouping, which moves the value for the 01/01/2017 into its own computational bucket. This may or may not be preferred.
Rename this column QTD (quarter to-date). Now, generate a similar column to compute the rolling average of weekly sales for the quarter:
| Transformation Name | Window |
|---|---|
| Parameter: Formulas | ROUND(ROLLINGAVERAGE(Sales, -1, 0)) |
| Parameter: Group by | QTR |
| Parameter: Order by | Date |
Since the ROLLINGAVERAGE function can compute fractional values, it is wrapped in the ROUND function for neatness. Rename this column avgWeekByQuarter.
Results:
When the unnecessary columns are dropped and some reordering is applied, your dataset should look like the following:
| Date | WOQ | Sales | QTD | avgWeekByQuarter |
|---|---|---|---|---|
| 10/2/16 | 1 | 200 | 200 | 200 |
| 10/9/16 | 2 | 500 | 700 | 350 |
| 10/16/16 | 3 | 350 | 1050 | 350 |
| 10/23/16 | 4 | 400 | 1450 | 363 |
| 10/30/16 | 5 | 190 | 1640 | 328 |
| 11/6/16 | 6 | 550 | 2190 | 365 |
| 11/13/16 | 7 | 610 | 2800 | 400 |
| 11/20/16 | 8 | 480 | 3280 | 410 |
| 11/27/16 | 9 | 660 | 3940 | 438 |
| 12/4/16 | 10 | 690 | 4630 | 463 |
| 12/11/16 | 11 | 810 | 5440 | 495 |
| 12/18/16 | 12 | 950 | 6390 | 533 |
| 12/25/16 | 13 | 1020 | 7410 | 570 |
| 1/1/17 | 1 | 680 | 680 | 680 |
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