I have grouped data that I want to convert to ungrouped data.
year<-c(rep(2014,4),rep(2015,4))
Age<-rep(c(22,23,24,25),2)
n<-c(1,1,3,2,0,2,3,1)
mydata<-data.frame(year,Age,n)
I would like to have a dataset like the one below created from the previous one.
year Age
1 2014 22
2 2014 23
3 2014 24
4 2014 24
5 2014 24
6 2014 25
7 2014 25
8 2015 23
9 2015 23
10 2015 24
11 2015 24
12 2015 24
13 2015 25
CodePudding user response:
Try
mydata[rep(1:nrow(mydata),mydata$n),]
year Age n
1 2014 22 1
2 2014 23 1
3 2014 24 3
3.1 2014 24 3
3.2 2014 24 3
4 2014 25 2
4.1 2014 25 2
6 2015 23 2
6.1 2015 23 2
7 2015 24 3
7.1 2015 24 3
7.2 2015 24 3
8 2015 25 1
CodePudding user response:
You can also use tidyr
syntax for this:
library(tidyr)
year<-c(rep(2014,4),rep(2015,4))
Age<-rep(c(22,23,24,25),2)
n<-c(1,1,3,2,0,2,3,1)
mydata<-data.frame(year,Age,n)
uncount(mydata, n)
#> year Age
#> 1 2014 22
#> 2 2014 23
#> 3 2014 24
#> 4 2014 24
#> 5 2014 24
#> 6 2014 25
#> 7 2014 25
#> 8 2015 23
#> 9 2015 23
#> 10 2015 24
#> 11 2015 24
#> 12 2015 24
#> 13 2015 25
But of course you shouldn't use tidyr
just because it is tidyr
:) An alternate view of the Tidyverse "dialect" of the R language, and its promotion by RStudio.
CodePudding user response:
Here's a tidyverse solution:
library(tidyverse)
mydata %>%
uncount(n)
which gives:
year Age
1 2014 22
2 2014 23
3 2014 24
4 2014 24
5 2014 24
6 2014 25
7 2014 25
8 2015 23
9 2015 23
10 2015 24
11 2015 24
12 2015 24
13 2015 25
CodePudding user response:
We can use tidyr::complete
library(tidyr)
library(dplyr)
mydata %>% group_by(year, Age) %>%
complete(n = seq_len(n)) %>%
select(-n) %>%
ungroup()
# A tibble: 14 × 2
year Age
<dbl> <dbl>
1 2014 22
2 2014 23
3 2014 24
4 2014 24
5 2014 24
6 2014 25
7 2014 25
8 2015 23
9 2015 23
10 2015 24
11 2015 24
12 2015 24
13 2015 25
14 2015 22