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 returns
0
.When used in a
pivot
transform, the function is computed for each instance of the value specified in thegroup
parameter. 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
Tip
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 


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 


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 


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 