# DENSERANK Function

Computes the rank of an ordered set of value within groups. Tie values are assigned the same rank, and the next ranking is incremented by 1.

• Rank values start at 1 and increment.

• Ranking order varies depending on the data type of the source data.

• You must use the group and order parameters to define the groups of records and the order of those records to which this function is applied.

• This function works with the following transforms:

• This function assigns ranking of the next value of a set of ties as a single increment more. For more discrete ranking, see RANK Function.

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

denserank() order:Times group:Racer

Output: Returns the dense ranking of Times values, grouped by the Racer column.

## Syntax and Arguments

denserank() order: order_col group: group_col

Examples

Sugerencia

### Example - Rank Functions

This example demonstrates you to generate a ranked order of values.

Functions:

Item

Description

RANK Function

Computes the rank of an ordered set of value within groups. Tie values are assigned the same rank, and the next ranking is incremented by the number of tie values.

DENSERANK Function

Computes the rank of an ordered set of value within groups. Tie values are assigned the same rank, and the next ranking is incremented by 1.

Source:

The following dataset contains lap times for three racers in a four-lap race. Note that for some racers, there are tie values for lap times.

Runner

Lap

Time

Dave

1

72.2

Dave

2

73.31

Dave

3

72.2

Dave

4

70.85

Mark

1

71.73

Mark

2

71.73

Mark

3

72.99

Mark

4

70.63

Tom

1

74.43

Tom

2

70.71

Tom

3

71.02

Tom

4

72.98

Transformation:

You can apply the RANK() function to the Time column, grouped by individual runner:

 Transformation Name Window RANK() Runner Time

You can use the DENSERANK() function on the same column, grouping by runner:

 Transformation Name Window DENSERANK() Runner Time

Results:

After renaming the columns, you have the following output:

Runner

Lap

Time

Rank

Rank-Dense

Mark

4

70.63

1

1

Mark

1

71.73

2

2

Mark

2

71.73

2

2

Mark

3

72.99

4

3

Tom

2

70.71

1

1

Tom

3

71.02

2

2

Tom

4

72.98

3

3

Tom

1

74.43

4

4

Dave

4

70.85

1

1

Dave

1

72.2

2

2

Dave

3

72.2

2

2

Dave

2

73.31

4

3