I wonder how to split my data
below such that I get a list of smaller dataf.rames each of which containing a unique pair of type
in it?
My desired_output
is shown below.
Note that this is just a toy data, so type
can be any other variable. Also, note that if a particular type
has just one row (like type == 4
), I want to exclude that with a warning that says:
type 4 has just one row thus is excluded.
m=
"
obs type
1 1
2 1
3 a
4 a
5 3
6 3
7 4
"
data <- read.table(text = m, h=T)
desired_output <-list(
data.frame(obs=1:4, type=c(1,1,"a","a")),
data.frame(obs=c(1,2,5,6), type=c(1,1,3,3)),
data.frame(obs=3:6, type=c("a","a",3,3))
)
# warning: type 4 has just one row thus is excluded.
CodePudding user response:
Here is base R function -
return_list_data <- function(data, type) {
unique_counts <- table(data[[type]])
single_count <- names(unique_counts[unique_counts == 1])
if(length(single_count)) {
warning(sprintf('%s %s has just one row thus is excluded.', type, toString(single_count)))
}
multiple_count <- names(unique_counts[unique_counts > 1])
combn(multiple_count, 2, function(x) {
data[data[[type]] %in% x, ]
}, simplify = FALSE)
}
This returns -
return_list_data(data, 'type')
#[[1]]
# obs type
#1 1 1
#2 2 1
#5 5 3
#6 6 3
#[[2]]
# obs type
#1 1 1
#2 2 1
#3 3 a
#4 4 a
#[[3]]
# obs type
#3 3 a
#4 4 a
#5 5 3
#6 6 3
#Warning message:
#In return_list_data(data, "type") :
# type 4 has just one row thus is excluded.
No warning is generated if there is no type
with single row i.e return_list_data(data[-7, ], 'type')
.
CodePudding user response:
You may try using dplyr
,
df1 <- read.table(text = m, h=T)
fun <- function(df1){
df2 <- df1 %>%
group_by(type) %>%
filter(n() > 1)
df3 <- combn(unique(df2$type), 2) %>% as.data.frame
df4 <- lapply(df3, function(x){
df2 %>%
filter(type %in% x)
})
war <- df1 %>%
group_by(type) %>%
filter(n()<= 1) %>%
pull(type)%>%
unique
if (length(war)>0){
warning(paste("type", war, "has just one row thus is excluded"))}
return(df4)
}
fun(df1)
result:
$V1
# A tibble: 4 x 2
# Groups: type [2]
obs type
<int> <chr>
1 1 1
2 2 1
3 3 a
4 4 a
$V2
# A tibble: 4 x 2
# Groups: type [2]
obs type
<int> <chr>
1 1 1
2 2 1
3 5 3
4 6 3
$V3
# A tibble: 4 x 2
# Groups: type [2]
obs type
<int> <chr>
1 3 a
2 4 a
3 5 3
4 6 3
Warnings: In fun(df1) : type 4 has just one row thus is excluded