Overview
Calculated Data Series allows you to chart custom calculations while still leveraging all of the benefits of Data Explorer: dynamic groupings and date ranges, chart transforms, and dashboard filtering.
When adding a Calculated Data Series, you can enter complex formulas referencing the columns in your transactional table of data. These calculations are dynamic, when the date grouping or date range of your metric changes, the expression is rerun and the chart displays the correct results.
Expressions in Calculated Data Series follow a Google Sheet like syntax for aggregations and mathematical operators. For example, if you wanted to calculate Average Deal Size, you would enter this expression:
SUM([Deal Amount])/COUNT([id])
You can also leverage conditional aggregations like SUMIFS and COUNTIFS, so that you can create advanced calculations without SQL knowledge.
How to Add a Calculated Data Series
Calculated Data Series are only supported in the Data Explorer Metric Builder.
To add a Calculated Data Series, select "+Add data series" on the Chart Tab of the Metric Builder. Instead of selecting a column from your table of data, select "Calculate a Data Series" at the bottom of the dropdown. This will open the "Calculate a Data Series" modal where you enter the calculation you would like to add to the chart.
Enter Your Calculation
In the Calculated Data Series modal, start typing in the box to enter your expression. Grow provides a helpful autofill to help guide you in entering a valid expression. You can start typing aggregations or column names and the autofill will suggest the correct syntax.
Please note that any column you want to reference from your transactional table of data must be wrapped by an aggregation (with the exception of criteria columns in conditional aggregations). Columns must be wrapped by an aggregation because of the dynamic groupings in Data Explorer, you must tell Grow what aggregation you want to use when grouping your transactional data.
Column Title
You must enter a Column Title in order to save a Calculated Data Series. Column Titles must be unique from both the column names in the table of data and the names of other Calculated Data Series.
Supported Syntax and Examples
Calculated Data Series uses Google Sheets like syntax for all Basic Aggregations and Conditional Aggregations. However, please note that the syntax for column names and syntax highlighting for different arguments is the same as Calculated Columns on the Data Tab. Calculated Data Series also supports the same operators as the Filter Transform.
The following operators and aggregations are currently supported in Calculated Data Series:
Basic Aggregations
Syntax  Description 
SUM([column_name]) 
sum of range 
COUNT([column_name]) 
count of range (includes blanks) 
AVERAGE([column_name]) 
average of range 
MAX([column_name]) 
maximum of range 
MIN([column_name]) 
minimum of range 
COUNTUNIQUE([column_name]) 
unique count of range (does not count blanks) 
Mathematical Operators
When using multiple mathematical operators in the same expression, please note the calculation will respect order of operations.
Syntax  Description 
+ 
addition 
 
subtraction 
* 
multiplication 
/ 
division 
Expression Examples
MAX([Deal Amount])
This expression finds the largest sale value over the selected grouping
SUM([Deal Amount])/COUNT([id])
This expression runs the sum of sales divided by the total number of orders over the selected grouping, calculating average order value.
Conditional Aggregations
Syntax  Description 
SUMIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the sum of a column depending on the criteria specified 
COUNTIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the count of values in a column depending on the criteria specified 
AVERAGEIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the average of a column depending on the criteria specified 
MAXIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the max value of a column depending on the criteria specified 
MINIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the min value of a column depending on the criteria specified 
COUNTUNIQUEIFS([column_name],[criteria_column1], "criteria1",[criteria_column2],"criteria2",...) 
returns the unique count of values in a column depending on the criteria specified 
Parameter Definitions

[column_name]
the column to perform the aggregation on (ex: the column to be summed or counted) 
[criteria_column]
the column (or range) to check the specified criteria against 
"criteria1"
the specified criteria to run against the criteria column 
[criteria_column2],"criteria2",...
additional columns (or ranges) and criteria to check
Filter Operators
Syntax  Description 
= 
equals 
<> 
does not equal 
> 
greater than 
>= 
greater than or equal to 
< 
less than 
<= 
less than or equal to 
CONTAINS("criteria") 
checks for cells that contain defined string criteria 
DOESNOTCONTAINS("criteria") 
checks for cells that do not contain defined string criteria 
ISONEOF("criteria1","criteria2",...) 
checks for cells that equal defined criteria 
ISNOTONEOF("criteria1","criteria2",...) 
checks for cells that do not equal defined criteria 
ISBLANK 
checks for empty cells 
ISNOTBLANK 
checks for nonempty cells 
Syntax Notes
 Criteria specified in
CONTAINS()
,DOESNOTCONTAIN()
,ISONEOF()
,ISNOTONEOF()
is not case sensitive 
You can apply the
CONTAINS()
orDOESNOTCONTAIN()
operator on any data type (text, numeric, or date column).
Expression Examples
SUMIFS([sales], [sales_rep], "Austin")
This expression sums Austin's sales over the selected grouping.
SUMIFS([order_id], [lead_source], ISONEOF("Social", "Paid"))
This expression sums the number of orders where the lead source equals "Social" or "Paid."
COUNTIFS([order_id], [sale_amount], ">100", [type], CONTAINS("New"))
This expression counts the number of orders where the sale amount is greater than 100 and the customer type contains the string "New"
COUNTIFS([order_id], [sales_amount], ">100", [customer_type], ISNOTBLANK)
This expression counts the number of orders where the sale amount is greater than 100 and customer type is not blank
COUNTIFS([Deal Amount], ">100")
This expressions counts the number of deals where the deal amount is greater than 100

You will notice this expression does not explicitly define the criteria_column. If you are entering a single criteria conditional aggregation, and the column you are aggregating is the same column you wish to run your criteria against, you do not need to specify the criteria_column.
Edit a Calculated Data Series Expression
To edit a Calculated Data Series expression, simply click the pencil of the Data Series you would like to edit. Upon clicking the pencil, you will be presented with the Calculated Data Series modal where you can edit your expression or Column Title. You must click "Save" or "Cancel" to exit the modal. Clicking "Cancel" will not save any changes made to the expression or the title.
Calculated Data Series and Data Explorer Compatibility
Here is the list of Chart Types and Chart Transforms that you can use while leveraging Calculated Data Series:
Chart Types

All Series Charts

Pie, Donut, & Funnel Charts

Table Charts
Chart Transforms

Date Range

Filter

Compare Dates

Sort & Limit

Goal Line