I am still learning how to use R for analysis, so would be really appreciated if anyone knows how to do that in R :)
CodePudding user response：
There is a good functionality available in data.table package in R
dcast(table, Test ~ Column1, value.var = "Preference")
You can check the functionality of the function
here.
There is also option to return back to the initial long version of the table using melt function.
CodePudding user response：
pivot_wider from the tidyr package should do the trick
library(tidyverse)
foo <- tibble(
ID = paste0('Female00', c(1, 1, 1, 2, 2, 3, 3, 3, 4, 5, 5, 5, 6)),
Test = c('Food', 'Beverage', 'Color', 'Beverage', 'Food', 'Color', 'Food', 'Beverage', 'Food', 'Beverage', 'Color', 'Food', 'Color'),
Preference = c('Strong', 'Strong', 'Medium', 'Low', 'Medium', 'Medium', 'Strong', 'Low', 'Low', 'Strong', 'Low', 'Medium', 'Medium')
)
foo %>%
pivot_wider(
names_from = ID,
values_from = Preference,
values_fill = NA
)
CodePudding user response：
It is just a matter of transposing the data frame :
df
Id Test Preference
1 Female001 Food Strong
2 Female001 Beverage Strong
3 Female001 Color Medium
4 Female002 Food Medium
5 Female002 Beverage Low
6 Female003 Color Medium
7 Female003 Food Strong
8 Female003 Beverage Low
> library(tidyr)
> df %>% spread(Id,Preference)
Test Female001 Female002 Female003
1 Beverage Strong Low Low
2 Color Medium <NA> Medium
3 Food Strong Medium Strong
