how do you group and merge columns in R

Question

I have this data frame:

d

structure(list(Product = structure(c(3L, 1L, 2L, 4L, 4L, 6L, 
4L, 5L), .Label = c("App_Servers ", "Db_servers,application ", 
"Server1,Serve2,Server4", "Server1,Serve2,Server4 ", "Server1,Serve2,Server4  ", 
"Server1,Serve2,Sever4 "), class = "factor"), Day = structure(c(3L, 
5L, 4L, 5L, 2L, 4L, 1L, 1L), .Label = c("Mon ", "Thu ", "Tue", 
"Tue ", "Wed "), class = "factor"), Date = structure(c(1L, 2L, 
3L, 4L, 5L, 6L, 7L, 7L), .Label = c(" 2015-01-06 ", "2015-01-07 ", 
"2015-01-13 ", "2015-01-14 ", "2015-01-15 ", "2015-01-20 ", "2015-02-16 "
), class = "factor"), Month = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 1L, 1L), .Label = c("Feb", "Jan"), class = "factor")), .Names = c("Product", 
"Day", "Date", "Month"), class = "data.frame", row.names = c(NA, 
-8L))

I need to be able to put dates in one cell separated by comma that are grouped by Product, Day and Month. For example,

Server1,Serve2,Server4 appears on 2015-01-06, 2015-01-14, 2015-01-15, 2015-01-20 for the month of Jan.

my new df needs to look like this:

Product                Day  Date    Month  Day_list
Server1,Serve2,Server4 Tues 2015-01-06 Jan 2015-01-06,2015-01-13,2015-01-20 

Any packages that can help me do this in R?

I tried using data.table package:

d[,d:=paste(Date,Date), c("Product","Day","Month")]

not working

Answer 1

There are a couple of things here.

First, your columns have additional spaces in them. You'd have to remove so that you can group them together.

require(data.table)
setDT(d)[, `:=`(Product = gsub("[ ]", "", Product),
                Date    = gsub("[ ]", "", Date))]

Second, you're using paste() and := wrongly.

d[, Date_list := paste(Date, collapse=","), by=c("Product", "Month")]
d
#                   Product  Day       Date Month                        Date_list
# 1: Server1,Serve2,Server4  Tue 2015-01-06   Jan 2015-01-06,2015-01-14,2015-01-15
# 2:            App_Servers Wed  2015-01-07   Jan                       2015-01-07
# 3: Db_servers,application Tue  2015-01-13   Jan                       2015-01-13
# 4: Server1,Serve2,Server4 Wed  2015-01-14   Jan 2015-01-06,2015-01-14,2015-01-15
# 5: Server1,Serve2,Server4 Thu  2015-01-15   Jan 2015-01-06,2015-01-14,2015-01-15
# 6:  Server1,Serve2,Sever4 Tue  2015-01-20   Jan                       2015-01-20
# 7: Server1,Serve2,Server4 Mon  2015-02-16   Feb            2015-02-16,2015-02-16
# 8: Server1,Serve2,Server4 Mon  2015-02-16   Feb            2015-02-16,2015-02-16

Have a look at the Introduction to data.table and Reference semantics vignettes.

Edit: I just realised that the 6th row has a typo for Product . It has Sever4 instead of Server4 .

Answer 2

Here is one solution using dplyr :

 d %>% mutate(
  Product = gsub("[ ]", "", Product),
  Day = gsub("[ ] ", "", Day )
  ) %>%
  group_by(Product, Month) %>%
  mutate(
    Day_list = paste(Date, collapse = "")
    )

                 Product  Day         Date Month                           Day_list
1 Server1,Serve2,Server4  Tue  2015-01-06    Jan  2015-01-06 2015-01-14 2015-01-15 
2            App_Servers Wed   2015-01-07    Jan                        2015-01-07 
3 Db_servers,application Tue   2015-01-13    Jan                        2015-01-13 
4 Server1,Serve2,Server4 Wed   2015-01-14    Jan  2015-01-06 2015-01-14 2015-01-15 
5 Server1,Serve2,Server4 Thu   2015-01-15    Jan  2015-01-06 2015-01-14 2015-01-15 
6  Server1,Serve2,Sever4 Tue   2015-01-20    Jan                        2015-01-20 
7 Server1,Serve2,Server4 Mon   2015-02-16    Feb             2015-02-16 2015-02-16 
8 Server1,Serve2,Server4 Mon   2015-02-16    Feb             2015-02-16 2015-02-16