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SUM Function

Computes the sum of all values found in all row values in a column. Input column can be of Integer or Decimal.

  • If a row contains a missing or null value, it is not factored into the calculation. If no numeric values are found in the source column, the function returns0.

  • When used in apivottransform, the function is computed for each instance of the value specified in thegroupparameter. See Pivot Transform.

For a version of this function computed over a rolling window of rows, see ROLLINGSUM 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

sum(myRating)

Output: Returns the sum of the group of values from the myRating column.

Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

Syntax and Arguments

sum(function_col_ref) [group:group_col_ref] [limit:limit_count]

Argument

Required?

Data Type

Description

function_col_ref

Y

string

Name of column to which to apply the function

For more information on the group and limit parameters, see Pivot Transform.

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

function_col_ref

Name of the column the values of which you want to calculate the sum. Column must contain Integer or Decimal values.

  • Literal values are not supported as inputs.

  • Multiple columns and wildcards are not supported.

Usage Notes:

Required?

Data Type

Example Value

Yes

String (column reference)

myValues

Examples

Dica

For additional examples, see Common Tasks.

This example demonstrates you to extract values from one column of an array into a new column.

Functions:

Item

Description

LIST Function

Extracts the set of values from a column into an array stored in a new column. This function is typically part of an aggregation.

UNIQUE Function

Extracts the set of unique values from a column into an array stored in a new column. This function is typically part of an aggregation.

DATEFORMAT Function

Formats a specified Datetime set of values according to the specified date format. Source values can be a reference to a column containing Datetime values.

You have the following set of orders for two months, and you are interested in identifying the set of colors that have been sold for each product for each month and the total quantity of product sold for each month.

Source:

OrderId

Date

Item

Qty

Color

1001

1/15/15

Pants

1

red

1002

1/15/15

Shirt

2

green

1003

1/15/15

Hat

3

blue

1004

1/16/15

Shirt

4

yellow

1005

1/16/15

Hat

5

red

1006

1/20/15

Pants

6

green

1007

1/15/15

Hat

7

blue

1008

4/15/15

Shirt

8

yellow

1009

4/15/15

Shoes

9

brown

1010

4/16/15

Pants

1

red

1011

4/16/15

Hat

2

green

1012

4/16/15

Shirt

3

blue

1013

4/20/15

Shoes

4

black

1014

4/20/15

Hat

5

blue

1015

4/20/15

Pants

6

black

Transformation:

To track by month, you need a column containing the month value extracted from the date:

Transformation Name

Edit column with formula

Parameter: Columns

Date

Parameter: Formula

DATEFORMAT(Date, 'MMM yyyy')

You can use the following transform to check the list of unique values among the colors:

Transformation Name

Pivot columns

Parameter: Row labels

Date

Parameter: Values

unique(Color, 1000)

Parameter: Max number of columns to create

10

Date

unique_Color

Jan 2015

["green","blue","red","yellow"]

Apr 2015

["brown","blue","red","yellow","black","green"]

Delete the above transform.

You can aggregate the data in your dataset, grouped by the reformatted Date values, and apply the LIST function to the Color column. In the same aggregation, you can include a summation function for the Qty column:

Transformation Name

Pivot columns

Parameter: Row labels

Date

Parameter: Values

list(Color, 1000),sum(Qty)

Parameter: Max number of columns to create

10

Results:

Date

list_Color

sum_Qty

Jan 2015

["green","blue","blue","red","green","red","yellow"]

28

Apr 2015

["brown","blue","red","yellow","black","blue","black","green"]

38