search for: colusions

...# we do not want use loops we do not use apply (not very fast) x <-c(0 ,1,2,3,4,5,6,7,8,NA,NA,1 ,1 ,NA,2 ,2) y <-c(0 ,0,0,1,0,0,0,1,1,1 ,NA,0 ,0 ,0 ,0 ,1) Must_be<-c(1 ,1,1,3,5,5,5,7,8,NA,NA,1.5,1 ,NA,1.5,2) (df<-as.data.frame(cbind(x,y)) ) # I have traied many bad colusions based on cumsum, pmin, pmax, ... (mean_dfx_if_yIs0<-y*cumsum(x*y)/(cumsum(y)*y) ) # how to do this? # thans for any advice # E [[alternative HTML version deleted]]

Hello, I'm trying to plot a graph of blood glucose versus date. I also record conditions, such as missing the previous night's medications, and missing exercise on the previous day. My data looks like: > b2[68:74,] # A tibble: 7 ? 5 Date Time bg missed_meds no_exercise <date> <time> <dbl> <lgl> <lgl> 1 2023-10-17 08:50

...gt; >> x <-c(0 ,1,2,3,4,5,6,7,8,NA,NA,1 ,1 ,NA,2 ,2) >> y <-c(0 ,0,0,1,0,0,0,1,1,1 ,NA,0 ,0 ,0 ,0 ,1) >> Must_be<-c(1 ,1,1,3,5,5,5,7,8,NA,NA,1.5,1 ,NA,1.5,2) >> >> (df<-as.data.frame(cbind(x,y)) ) >> >> # I have traied many bad colusions based on cumsum, pmin, pmax, ... >> (mean_dfx_if_yIs0<-y*cumsum(x*y)/(cumsum(y)*y) ) >> >> # how to do this? >> # thans for any advice >> # E [[alternative HTML version deleted]]