Calculating Survival rate from month to month without losing starting values - r

Question

I have a set of code that divides the number of alive specimens from the initial count.
I am trying to determine the survival rate for the entire 5 month experiment but, there seems to be an issue with the computation each month. For the initial month, the code computes the correct survival rate (ie: 48/50 - 96%). But, the issue comes in when computing for the next month where the code will compute the survival rate from 48 instead of 50 (ie: 46/48 survived, instead of 46/50 which is what I need). It continues this way for the remainder of the experiment (30/46 month 3, then 20/30 for month 4).
Additionally, each of the "dead" specimens are then added to an NA group automatically (There should be no NA groups). I think if the first issue is taken care of then the NA issue wont happen. Is there a way to fix this with the code I have or do I need to rearrange the data in excel?
I have 2 species in 4 habitats that need this code for analysis.
Thanks!
Month 1
| Species | Cage || nStart | nAlive || PropAlive
| -------- | -------------- || | |
| X | 1 || 10 | 9 | .9
| Y | 2 || 10 | 8 | .8
| -------- | -------------- || | |
Month 2
| Species | Cage || nStart | nAlive || PropAlive (nAlive/nStart)
| -------- | -------------- || | |
| X | 1 || 9 | 8 | .89
| Y | 2 || 8 | 7 | .875
| -------- | -------------- || | |
month 2 should be 8/10 and 7/10 for Prop Alive not 8/9 and 7/8.
library(readxl)
library(tidyverse)
library(lme4)
library(car)
library(emmeans)
JulyData<- read_excel("~/R/Cage Data Final 2016 EMV 1.20.xlsx", sheet="7.1.2016")
str(JulyData)
summary(JulyData$Lice)
AllCages<- distinct(JulyData, Cage, Species)
AllCages$nStart<- rep(10,nrow(AllCages))
Alive<- JulyData%>%
filter(!is.na(Lice))%>%
group_by(Cage, Species)%>%
summarise(nAlive=n())
CleanData<-merge(AllCages,Alive, all=TRUE)
CleanData$nAlive[is.na(CleanData$nAlive)]<-0
CleanData$nAlive[CleanData$nAlive>10]<-10
CleanData<-CleanData %>%
separate(Cage,c("Habitat", "Rep"),1,remove=FALSE) %>%
mutate(nDead=nStart-nAlive)
CleanData
CleanData%>%
group_by(Species,Habitat)%>%
summarize(nStart=sum(nStart),
nAlive=sum(nAlive),
PropAlive = nAlive/nStart)

Answer 1

So, the issue was related to formatting within the data. The code is right - a simple labeling error was the issue.