R- reshape2 with aggregation min function - r

Question

I need to transpose a df in R and the aggregtion function has to be min.
Example:
library(reshape2)
N <- 20
df <- data.frame(rutcli=sample(101:103, N, replace=T),
mes_atras=sample(1:4, N, replace=T), pay_day=sample(1:30, N, replace=T))
s<-dcast(df, rutcli ~ mes_atras, fun.aggregate = min, value.var = 'pay_day')
View(s)
But I get a warning:
Warning message: In .fun(.value[0], ...) : no non-missing arguments to
min; returning Inf
And the results are not the desired:
rutcli 1 2 3 4
101 1 1 Inf 1
102 Inf 2 14 8
103 3 6 2 25
How can I solve this?
Thanks

Answer 1

You're getting the warning because you're asking for the minimum value of an empty set. For example, there are no values of pay_day for which rutcli=102 and mes_atras=1, so Inf is returned instead.
You can see this more easily if you set fun.aggregate=length. For example:
library(reshape2)
N <- 20
set.seed(11) # To make the `sample` function reproducible
df <- data.frame(rutcli=sample(101:103, N, replace=T),
mes_atras=sample(1:4, N, replace=T),
pay_day=sample(1:30, N, replace=T))
dcast(df, rutcli ~ mes_atras, fun.aggregate = length, value.var = 'pay_day')
rutcli 1 2 3 4
1 101 4 4 2 0
2 102 1 3 1 0
3 103 2 2 0 1
The zeros represent combinations of rutcli and mes_atras for which there are no values of pay_day. If we run dcast on this data frame with the min function, we'll get Inf where the zeros appear:
dcast(df, rutcli ~ mes_atras, fun.aggregate = min, value.var = 'pay_day')
rutcli 1 2 3 4
1 101 1 5 7 Inf
2 102 18 13 14 Inf
3 103 10 13 Inf 7
Warning message:
In .fun(.value[0], ...) : no non-missing arguments to min; returning Inf
You can get NA instead of Infby using one of the split-apply-combine methods. #MatthewLundberg gives a base R method. Here's one with dplyr:
library(dplyr)
df %>%
group_by(rutcli, mes_atras) %>%
summarise(min_pay_day=min(pay_day)) %>%
dcast(rutcli ~ mes_atras, value.var="min_pay_day")
rutcli 1 2 3 4
1 101 1 5 7 NA
2 102 18 13 14 NA
3 103 10 13 NA 7

Answer 2

You can do this with aggregate and reshape from package stats:
reshape(
aggregate(pay_day ~ mes_atras + rutcli, data=df, FUN=min),
direction='wide', timevar='mes_atras', idvar='rutcli'
)
## rutcli pay_day.1 pay_day.2 pay_day.3 pay_day.4
## 1 101 1 20 15 2
## 5 102 18 30 NA 3
## 8 103 2 5 23 16
You can replace NA values with Inf if desired.
Here's my df:
structure(list(rutcli = c(103L, 103L, 103L, 103L, 103L, 103L,
102L, 102L, 103L, 102L, 101L, 101L, 101L, 101L, 101L, 103L, 102L,
101L, 101L, 103L), mes_atras = c(1L, 3L, 4L, 1L, 1L, 2L, 1L,
4L, 1L, 2L, 2L, 4L, 3L, 2L, 2L, 4L, 4L, 4L, 1L, 2L), pay_day = c(3L,
23L, 16L, 18L, 2L, 5L, 18L, 3L, 12L, 30L, 20L, 2L, 15L, 24L,
29L, 24L, 3L, 19L, 1L, 12L)), .Names = c("rutcli", "mes_atras",
"pay_day"), row.names = c(NA, -20L), class = "data.frame")

Answer 3

I did it with:
my.min <- function (v) {if (length(v) == 0) 0 else min(v)}
s<-dcast(df, rutcli ~ mes_atras, fun.aggregate = my.min, value.var = 'pay_day')
And because I know that I don't have any 0:
s[s == 0] <- NA