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Answers
I have a work around using R, so you can easily integrate into your pipeline with Execute R scripting extension
use the na.locf() function from the zoo package to carry the last observation forward to replace your NA values.
~*~*~*sample R~*~*~*~*
library(zoo)
bz <- c(2,NA,NA,1,NA,1,4,5,NA,NA,NA,2)
na.locf(bz)
~*~*~*END R~*~*~*~*
Another possible option, within Rapidminer
In the time series extension, there is an operator for replacing missing values using various combination like previous value, next value, value(hardcoded) or linear interpolation.
I tried a simple use case and seems to do what you are looking for
Attached is the example data set and the process
You can download the extension from marketplace in your studio or from here
https://marketplace.rapidminer.com/UpdateServer/faces/product_details.xhtml?productId=rmx_series
Please note that the "generate copy" is just for easier comparison if it is doing the right thing, you can ignore it in actual process