How do I aggregate the sum of infected individuals at each particular time?

Question

I want to have a dataframe with each time and the sum of the infected individuals.

First I create the vectors that will be in a data frame.

 status<-(c("h","h","h","h","i","h","h","h","i","i","h","h","h","i","i","h","h","i","i","i"))
 time<-c(0,0,0,0,0,2,2,2,2,2,5,5,5,5,5,8,8,8,8,8)

Then I create the dataframe

 test<-data.frame(time,status)

What do I do next? I am open to packages and alternative methods.

Many thanks.

Answer 1

I am not sure which kind of result is the expected output. Below are two options with aggregate in base R:

• list all status

> aggregate(.~time,test,list)
  time        status
1    0 h, h, h, h, i
2    2 h, h, h, i, i
3    5 h, h, h, i, i
4    8 h, h, i, i, i

• summarize status in terms of number of i and h

> aggregate(.~time,test,table)
  time status.h status.i
1    0        4        1
2    2        3        2
3    5        3        2
4    8        2        3

Answer 2

An option with data.table

library(data.table)
setDT(df)[, .(n = .N), .(time, status)]

Or with count

library(dplyr)
df %>%
   count(time, status)

---

Or in base R with table

table(df[c('time', 'status')])

Answer 3

Not quite sure what the time variable is representing, but here's an attempt, if I am interpreting your variables correctly.

library(tidyverse)
testB <- test %>% 
  group_by(status) %>% 
  summarise(sum = sum(time))

Answer 4

I suppose you want the number of people that are of status h or i by time:

library(dplyr)

df %>% group_by(time,status) %>% summarise(n = n())
# A tibble: 8 x 3
# Groups:   time [4]
   time status     n
  <dbl> <chr>  <int>
1     0 h          4
2     0 i          1
3     2 h          3
4     2 i          2
5     5 h          3
6     5 i          2
7     8 h          2
8     8 i          3

If you are only interested in infected people

df %>% group_by(time,status) %>% summarise(n = n()) %>% filter(status == "i")