Suppose I have the following data.frame:
foo <- data.frame(CONTACT_DATE = c(rep(as.Date("2015-09-15"),3), rep(as.Date("2015-09-16"),3)), ISSUE = c("abc", "def", "xyz", "abc", "xyz", "def"), ISSUE_COUNT = c(1000,750,100,1500,200,100), RANK = c(1,2,3,1,2,3))
> foo
  CONTACT_DATE ISSUE ISSUE_COUNT RANK
1   2015-09-15   abc        1000    1
2   2015-09-15   def         750    2
3   2015-09-15   xyz         100    3
4   2015-09-16   abc        1500    1
5   2015-09-16   xyz         200    2
6   2015-09-16   def         100    3     
How do I go from the above to:
CONTACT_DATE ISSUE_RANK_1 ISSUE_RANK_2 ISSUE_RANK_3
2015-09-15   abc (1000)   def (750)    xyz (100)
2015-09-16   abc (1500)   xyz (200)    def (100)
I believe I have I have to use melt & dcast from reshape2 but I haven't been able to figure out how.
You could use dplyr and tidyr:
library(dplyr)
library(tidyr)
foo %>%
  mutate(ISSUE_COUNT = paste0("(", ISSUE_COUNT, ")"),
         RANK = paste0("ISSUE_RANK_", RANK)) %>%
  unite(VAR, ISSUE, ISSUE_COUNT, sep = " ") %>%
  spread(RANK, VAR)
Which gives:
#  CONTACT_DATE ISSUE_RANK_1 ISSUE_RANK_2 ISSUE_RANK_3
#1   2015-09-15   abc (1000)    def (750)    xyz (100)
#2   2015-09-16   abc (1500)    xyz (200)    def (100)
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