Duplicating a data frame and replacing values

Question

If i have two data frames:

Df1:
Name1 Name2 Destination1
  A     I       London
  B     J       Paris
  C     K       New York
  D     L       Bangkok
  E     M       Singapore

Df2:
Theme      Pattern
Luxury      luxury hotels in {d} 
City        city hotels {d}
Break        breaks in {d} 
Package      {d} packages

Essentially, i want a new data frame where for each destination1 in Df1 i have every pattern from Df2 while retaining the Theme column and both Name 1 Name 2 columns from Df1.

E.g. Desired output:

Df3:
Name 1      Name 2     Destination 1  Theme     Pattern
A            I            London      Luxury     luxury hotels in {London} 
A            I            London      City       city hotels {London}
A            I            London      Break       breaks in {London} 
A            I            London      Packages    {London} packages
B            J            Paris       Luxury       luxury hotels in {Paris} 
B            J            Paris       City         city hotels {Paris}
B            J            Paris       Break        breaks in {Paris} 
B            J            Paris       Packages     {Paris} packages
C etc....

Answer 1

You can use dplyr and tidyr solution for this: First, reshape Df2 to wide format and cbind with Df1; then gather to the original long format. Then using gsub with regular expression replace {d} with the destination.

library(dplyr)
library(tidyr)

Df1 <- data.frame(name1 = LETTERS[1:5],
                  name2 = LETTERS[9:13],
                  Destination1 = c("London", "Paris", "New York", "Bangkok", "Singapore")
                  )

Df2 <- data.frame(Theme = c("Luxury", "City", "Break", "Package"),
                  Pattern = c("Luxury hotels in {d}",
                          "City hotels in {d}",
                          "Breaks in {d}",
                          "{d} packages")
                 )

Df3 <- Df1 %>% 
  # reshape Df2 to wide format and combine it with Df1
  cbind(spread(data = Df2, key = Theme, value = Pattern)) %>%
  # convert back to long format
  gather(key = Theme, value = Pattern, Break:Package) %>%
  # replace {d} with Destination
  mutate(Pattern = gsub(pattern = "\\{d\\}",
                        replacement = Destination1,
                        x = Pattern))

Answer 2

Not exactly the same data (you should provide the code to generate the data), but this do the things you are looking for! Though not very elegantly I must admit...

A=data.frame(c1=c("A", "B", "C"), c2=c("london", "paris", "berlin"))
B=data.frame(c3=c("a", "b", "c"), c4=c("la{d}", "{d}lala", "lala{d}la"))
# aggregate the df
AB <- data.frame(c1=rep(A$c1, nrow(B)), c2=rep(A$c2, nrow(B)), 
                 c3=rep(B$c3, each=nrow(A)), c4=rep(B$c4, each=nrow(A)))
# change {d} in city names
AB$c4 <- sapply(1:nrow(AB), function(x) gsub("\\{d\\}", 
                                        paste(" ", AB[x,"c2"], " "), AB[x,"c4"])) 
# regroup by city names
AB <- AB[order(AB$c2),] 
AB # enjoy

Answer 3

you can create a new variable for each of the data set and then remove it after the join. You can do below.

library(dplyr)
Df1$new <- "lol"

Df2$new <- "lol"

Df3 <- full_join(Df1,Df2) %>% select(-new)


**example:
df1 <- data.frame(a=c(1:5),b=c(7:11))

df2 <- data.frame(c=c(12:16),d=c(17:21))

df1$new <- "lol"
df2$new <- "lol"
library(dplyr)

full_join(df1,df2) %>% select(-new)**