Compute mean of control - spotfire

Question

I'm migrating an analysis from R to Spotfire, and what's trivial in dplyr seems hard in Spotfire. I have a table with several experimental groups, each with treatments and controls. I want to compute the mean of controls for each experimental group.
Here's a sample:
+-------+------+-------+
| group | trmt | value |
+-------+------+-------+
| a | cont | 32 |
| a | cont | 28 |
| a | t1 | 65 |
| a | t1 | 57 |
| a | t2 | 23 |
| a | t2 | 19 |
| b | cont | 132 |
| b | cont | 128 |
| b | t1 | 165 |
| b | t1 | 157 |
| b | t2 | 123 |
| b | t2 | 119 |
+-------+------+-------+
and the desired output:
+-------+------+-------+-------------+
| group | trmt | value | meanControl |
+-------+------+-------+-------------+
| a | cont | 32 | 30 |
| a | cont | 28 | 30 |
| a | t1 | 65 | 30 |
| a | t1 | 57 | 30 |
| a | t2 | 23 | 30 |
| a | t2 | 19 | 30 |
| b | cont | 132 | 130 |
| b | cont | 128 | 130 |
| b | t1 | 165 | 130 |
| b | t1 | 157 | 130 |
| b | t2 | 123 | 130 |
| b | t2 | 119 | 130 |
+-------+------+-------+-------------+
In R, the logic is trivial:
library(dplyr)
df <- read.csv('xx.csv', as.is=T)
controls <- df %>%
filter(trmt == "cont") %>%
group_by(group) %>%
summarize(meanControl=mean(value))
result <- df %>%
inner_join(controls, by="group")
What's a good approach to do this in Spotfire? Obviously I can do this with TERR but I want pure native Spotfire.

Answer 1

You can insert a calculated column with this formula
Avg(if([trmt]="cont",[value])) over ([group])
Since you understand R, I assume you'll easily understand this formula or be able to understand it after reading about the OVER function but let me know if it needs explaining.