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Release 6.8.2

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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 the `group` parameter. See Pivot Transform.

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

## Basic Usage

sum(myRating)

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

## Syntax and Arguments

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

ArgumentRequired?Data TypeDescription
function_col_refYstringName of column to which to apply the function

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

### 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 TypeExample Value
YesString (column reference)`myValues`

## Examples

This example illustrates the following functions:
• `LIST` - Extracts up to 1000 values from one column into an array in a new column. See LIST Function.
• `UNIQUE` - Extracts up to 1000 unique values from one column into an array in a new column. See UNIQUE Function.

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:

OrderIdDateItemQtyColor
10011/15/15Pants1red
10021/15/15Shirt2green
10031/15/15Hat3blue
10041/16/15Shirt4yellow
10051/16/15Hat5red
10061/20/15Pants6green
10071/15/15Hat7blue
10084/15/15Shirt8yellow
10094/15/15Shoes9brown
10104/16/15Pants1red
10114/16/15Hat2green
10124/16/15Shirt3blue
10134/20/15Shoes4black
10144/20/15Hat5blue
10154/20/15Pants6black

Transformation:

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

Transformation Name `Edit column with formula` `Date` `DATEFORMAT(Date, 'MMM yyyy')`

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

Transformation Name `Pivot columns` `Date` `unique(Color, 1000)` `10`

Dateunique_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` `Date` `list(Color, 1000),sum(Qty)` `10`

Results:

Datelist_Colorsum_Qty
Jan 2015["green","blue","blue","red","green","red","yellow"]28
Apr 2015
["brown","blue","red","yellow","black","blue","black","green"]
38