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Comment: Published by Scroll Versions from space DEV and version r095

D toc

Excerpt

Computes the rolling mode (most common value) forward or backward of the current row within the specified column. Input values can be Integer, Decimal, or Datetime data type.

• If an input value is missing or null, it is not factored in the computation. For example, for the first row in the dataset, the rolling mode of previous values is undefined.
• The row from which to extract a value is determined by the order in which the rows are organized based on the `order` parameter.

• 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.

• The function takes a column name and two optional integer parameters that determine the window backward and forward of the current row.
• The default integer parameter values are `-1` and `0`, which computes the rolling function from the current row back to the first row of the dataset.
• This function works with the Window transform. See Window Transform.

For more information on a non-rolling version of this function, see MODE Function.

D s lang vs sql

D s
snippet Basic

Column example:

D lang syntax
RawWrangle true ref true derive type:single value:rollingmode(myCol)

rollingmode(myCol)

Output: Returns the rolling mode of all values in the `myCol` column.

Rows before example:

D lang syntax
RawWrangle true ref true window value:rollingmode(myNumber, 3)

rollingmode(myNumber, 3)

Output: Returns the rolling mode of the current row and the three previous row values in the `myNumber` column.

Rows before and after example:

D lang syntax
RawWrangle true ref true window value:rollingmode(myNumber, 3, 2)

rollingmode(myNumber, 3, 2)

Output: Returns the rolling mode of the three previous row values, the current row value, and the two rows after the current one in the `myNumber` column.

D s
snippet Syntax

D lang syntax
RawWrangle true syntax true window value:rollingmode(col_ref, rowsBefore_integer, rowsAfter_integer) order: order_col [group: group_col]

rollingmode(col_ref, rowsBefore_integer, rowsAfter_integer) order: order_col [group: group_col]

ArgumentRequired?Data TypeDescription
col_refYstringName of column whose values are applied to the function
rowsBefore_integerNintegerNumber of rows before the current one to include in the computation
rowsAfter_integerNintegerNumber of rows after the current one to include in the computation

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

D s lang notes

### col_ref

Name of the column whose values are used to compute the function.

Info

NOTE: If the input is in Datetime type, the output is in unixtime format. You can wrap these outputs in the DATEFORMAT function to generate the results in the appropriate Datetime format. See DATEFORMAT Function.

Multiple columns and wildcards are not supported.

D s
snippet usage

Required?Data TypeExample Value
YesString (column reference to Integer or Decimal values)`myColumn`

### rowsBefore_integer, rowsAfter_integer

Integers representing the number of rows before or after the current one from which to compute the rolling function, including the current row. For example, if the first value is `5`, the current row and the five rows before it are used in the computation. Negative values for `rowsAfter_integer` compute the rolling function from rows preceding the current one.

• `rowBefore=0` generates the current row value only.
• `rowBefore=-1`  uses all rows preceding the current one.
• If `rowsAfter` is not specified, then the value `0` is applied.
• If a `group` parameter is applied, then these parameter values should be no more than the maximum number of rows in the groups.

D s
snippet usage

Required?Data TypeExample Value
NoInteger`4`

D s
snippet Examples

### Example - Counting most common coin flips

In the following table, 20 coin flips are tabulated. You want to capture a rolling evaluation of the most common value.

Source:

TurnResult
3tails
6tails
7tails
9tails
11tails
13tails
16tails
17tails
18tails

Transformation:

To use the `ROLLINGMODE` function, the results need to be converted to numeric values:

D trans
RawWrangle true step set col: Result value: if(Result == 'heads', 0, 1) Columns Result Formula if(Result == 'heads', 0, 1) Edit column with formula

Now calculate the `ROLLINGMODE` for the preceding five values for each row:

D trans
RawWrangle true Turn step derive type: multiple value: rollingmode(Result, 4, 0) order: Turn as: 'mostCommonLast5' Formula type Multiple row formula Formula rollingmode(Result, 4, 0) Sort rows by 'mostCommonLast5' New column name New formula

You can now convert the binary values back to text information:

D trans
RawWrangle true step set col: mostCommonLast5 value: if(mostCommonLast5 == 0, 'heads-last5', 'tails-last5') Columns mostCommonLast5 Formula if(mostCommonLast5 == 0, 'heads-last5', 'tails-last5') Edit column with formula

Results:

TurnResultmostCommonLast5
7tailstails-last5
9tailstails-last5