Turn field names into column names for specific variables and fill them with certain logic - r

Question

I have the dataframe below:
product<-c("ab","ab","ab","ac","ac","ac")
shop<-c("sad","sad","sad","sadas","fghj","xzzv")
category<-c("a","a","a","c","b","b")
tempr<-c(35,35,14,24,14,5)
value<-c(0,0,-6,8,4,0)
store<-data.frame(product,shop,category,tempr,value)
product shop category tempr value
1 ab sad a 35 0
2 ab sad a 35 0
3 ab sad a 14 -6
4 ac sadas c 24 8
5 ac fghj b 14 4
6 ac xzzv b 5 0
I want to transform this dataframe in a way that I will keep the unique product names and turn shop names from field values to column names (and the opposite). I want to fill this data frame with a combination of tempr and its relative value but only for the value that is not 0 otherwise the cells should be empty. However, as you noticed I have records that have the same product and shop, but different tempr and value numbers (ab-sad). The problem is that they overwrite each other. In that case (same name,same shop but different tmpr-value) the non-zero case should prevail. For example 170(62) should be dispalyed instead of 170(0) if they both exist.The cells should also be empty in case that a product does not exist in a shop. An example of the final form is:
store2
product sad sadas fghj xzzv
1 ab 14(-6)
2 ac 24(8) 14(4)
1st possible approach:
store2 <- matrix(NA,ncol=length(unique(store$shop)),nrow=length(unique(store$product)))
colnames(store2) <- unique(store$shop)
rownames(store2) <- unique(store$product)
for(i in 1:ncol(store)) {
store2[store[i,'product'],store[i,'shop']] <- paste0(store[i,c('tempr')],'(',store[i,'value'],')')
}
2nd possible approach:
library(tidyverse)
store %>%
mutate(shop = factor(shop, levels = unique(shop))) %>%
filter(value != 0) %>%
mutate(val = sprintf("%s(%s)", tempr, value)) %>%
select(product, shop, val) %>%
group_by(product) %>%
complete(shop) %>%
spread(shop, val)
Except from this result I want to be able to use category as well with the same logic. The picture below shows all the possible combinations that I wish with the same filling logic.

Answer 1

Not sure I fully understand the question, but the code below produces your example dataframe.
library(tidyverse)
product<-c("ab","ab","ab","ac","ac","ac")
shop<-c("sad","sad","sad","sadas","fghj","xzzv")
category<-c("a","a","a","c","b","b")
tempr<-c(35,35,14,24,14,5)
value<-c(0,0,-6,8,4,0)
store<-data.frame(product,shop,category,tempr,value)
store %>% filter(value != 0 ) %>% # Remove 0 values
mutate(combined = paste0(tempr,"(",value,")")) %>% # Combine columns for spread
select(-tempr,-value) %>% #
spread(shop,combined) # spread to create shop columns and temr/value values.
# product category fghj sad sadas
# 1 ab a <NA> 14(-6) <NA>
# 2 ac b 14(4) <NA> <NA>
# 3 ac c <NA> <NA> 24(8)

Answer 2

store$shop<-factor(store$shop,levels=c("sad","sadas","fghj","xzzv"))
#to avoid the change of column sequence of final outcome
store$tv<-ifelse(store$value==0,"",paste(store$tempr,"(",store$value,")",sep=""))
cast(store[,c(-3,-4,-5)],product~shop,function(x) paste(x,sep="",collapse=""), value="tv")
#due to one colname of the original store dataset is "value", firstly masked
#the original "value" column,otherwise, it automatically used as value-fill
# column
product sad sadas fghj xzzv
ab 14(-6)
ac 24(8) 14(4)"