I am currently learning the tidyr and dplyr. Went in the following issue I am not sure how to appropiatly face:
Imaging the following dataset:
Factor 1 Factor 2 Year value
A green 2016 1.2
A green 2017 1.9
B yellow 2017 3
B yellow 2018 8
An trying to obtain:
Factor 1 Factor 2 Year.2016 Year.2017 Year.2018
A green 1.2 1.9 NA
B yellow NA 3 8
I have basic R knowledge in this aspect and tried several options using default R fuctions but withouth results
library(dplyr)
library(tidyr)
# example data
dt = read.table(text = "
Factor1 Factor2 Year value
A green 2016 1.2
A green 2017 1.9
B yellow 2017 3
B yellow 2018 8
", header=T)
dt %>% spread(Year, value, sep=".")
# Factor1 Factor2 Year.2016 Year.2017 Year.2018
# 1 A green 1.2 1.9 NA
# 2 B yellow NA 3.0 8
In case you have two or more value columns you can use this approach that involves a little bit more reshaping:
library(dplyr)
library(tidyr)
# example data
dt = read.table(text = "
Factor1 Factor2 Year value value2
A green 2016 1.2 5
A green 2017 1.9 5
B yellow 2017 3 5
B yellow 2018 8 5
", header=T)
dt %>%
gather(v, value, -Factor1, -Factor2, -Year) %>%
unite(Year, Year, v) %>%
spread(Year, value, sep = ".")
# Factor1 Factor2 Year.2016_value Year.2016_value2 Year.2016_value3 Year.2017_value
# 1 A green 1.2 5 9 1.9
# 2 B yellow NA NA NA 3.0
# Year.2017_value2 Year.2017_value3 Year.2018_value Year.2018_value2 Year.2018_value3
# 1 5 9 NA NA NA
# 2 5 9 8 5 9