将所有行与R数据帧中的特定行进行比较

Question

I would like to know how to most efficiently compare all values in a dataframe to a specific value conditional. In this example:

In this example:

id <- c("a","a","b","b")
t <- c(2000,2018,2000,2018)
value <- c(10,20,5,30)
test0 <- data.frame(id,value,t,row.names = paste0(id,"_",t))
test  <- test0

which gives:

       id value    t
a_2000  a    10 2000
a_2018  a    20 2018
b_2000  b     5 2000
b_2018  b    30 2018

I would like to compare values to another id, or another t, or even by row names.

The best way I found so far was to create a second data frame, containing only the data for id and then joining that column to use it.

In this case, the example would be:

tmp <- test0 %>%
  subset(id =="a") %>%
  select(value,t) %>%
  rename(ref=value)

test %>%
  left_join(tmp,by="t") %>%
  mutate(vsRef = value/ref)

which gives:

  id value    t ref vsRef
1  a    10 2000  10   1.0
2  a    20 2018  20   1.0
3  b     5 2000  10   0.5
4  b    30 2018  20   1.5

I am sure there must be a simple answer, but could not find it easily. Could you help?

Answer 1

Finally found an easy way to do this (when I finally decided to write the post!):

test0 %>%
   ddply(.(t),mutate,vsRef=value/value[id=="a"])

  id value    t vsRef
1  a    10 2000   1.0
2  b     5 2000   0.5
3  a    20 2018   1.0
4  b    30 2018   1.5

test0 %>%
   ddply(.(id),mutate,vsRef=value/value[t==2000])

  id value    t vsRef
1  a    10 2000     1
2  a    20 2018     2
3  b     5 2000     1
4  b    30 2018     6

test0 %>%
   mutate(vsRef=value/value[rownames(test0)=="a_2000"])

  id value    t vsRef
1  a    10 2000   1.0
2  a    20 2018   2.0
3  b     5 2000   0.5
4  b    30 2018   3.0