The general idea of this question has been asked here
However the answer did not work in my specific case since I want to use a third input into the function, which is a large dataframe. I have also tried using sapply as per this post but that still does not work.
My goal is to avoid having to create the new columns by hand/use a for loop to append into the new columns. Is this possible in R? Is there another more 'R' way to structure my data and/or function? I looked at purrr::pmap but I don't know how to have it output multiple columns
Here is my minimal reproducible example:
library(tidyverse)
find_sample_gaps<-function(site, analyte, df){
Sample <- df%>%
filter(site_code == site)%>%filter(analyte_code == analyte)%>%
mutate(Year = as.numeric(format(Date, '%Y')))
x<-Sample%>%
group_by(Year)%>%
summarize(n_samples = length(Year))
gaps<-which(c(1,diff(x$Year))>1)
a<-sum(x$n_samples)
b<-length(unique(Sample$Date))
c<-'No gaps'
if(length(gaps)>0){
c<-paste('There are', as.character(gaps), 'gaps')
}
return(cbind(a,b,c))
}
# use function inside cbind to add columns to dataframe
result<-cbind(output1, find_sample_gaps(output1$site_code, output1$analyte_code, output2)) # throws error because output2 dataframe isn't the same size as result?
# another attempt also using cbind with sapply
result<-cbind(output1, t(sapply(c(output1$site_code, output1$analyte_code, output2), find_sample_gaps))) # also throws error, does not recognize the inputs into the function?
Here is my input data:
output1<-structure(list(site_code = c("a", "b", "c", "d", "e", "f", "g",
"h", "i", "j", "j", "j", "j", "j", "j", "j", "k", "k", "k", "k",
"k", "k", "k", "l", "l", "l", "l", "l", "l", "m", "n", "o", "p",
"q", "r", "s", "t", "u", "v", "w", "w", "w", "w", "w", "x", "x",
"x", "x", "x", "y", "y", "y", "z", "z", "z", "z", "z", "aa",
"aa", "aa", "aa", "aa", "aa", "aa", "bb", "bb", "bb", "bb", "bb",
"cc", "cc", "cc", "cc", "cc", "dd", "dd", "dd", "dd", "dd", "ee",
"ee", "ee", "ee", "ee", "ee", "ee", "ff", "ff", "ff", "ff", "ff",
"gg", "gg", "gg", "gg", "gg", "hh", "hh", "hh", "hh", "hh", "hh",
"ii", "ii", "ii", "ii", "ii", "ii", "jj", "jj", "jj", "jj", "jj",
"jj", "jj"), analyte_code = c("a", "a", "a", "a", "a", "a", "a",
"a", "a", "b", "c", "d", "e", "a", "f", "g", "b", "c", "d", "e",
"a", "f", "g", "c", "d", "e", "a", "f", "g", "a", "a", "a", "a",
"a", "a", "a", "a", "a", "a", "d", "e", "a", "f", "g", "d", "e",
"a", "f", "g", "a", "f", "g", "d", "e", "a", "f", "g", "b", "c",
"d", "e", "a", "f", "g", "d", "e", "a", "f", "g", "d", "e", "a",
"f", "g", "d", "e", "a", "f", "g", "b", "c", "d", "e", "a", "f",
"g", "d", "e", "a", "f", "g", "d", "e", "a", "f", "g", "c", "d",
"e", "a", "f", "g", "c", "d", "e", "a", "f", "g", "b", "c", "d",
"e", "a", "f", "g")), row.names = c(NA, -115L), class = c("tbl_df",
"tbl", "data.frame"))
output2<-structure(list(site_code = c("dd", "k", "k", "r", "aa", "ii",
"y", "l", "l", "l", "q", "cc", "w", "bb", "c", "ff", "m", "ii",
"p", "ff", "ff", "z", "ff", "l", "w", "hh", "ff", "ff", "ff",
"k", "j", "bb", "x", "hh", "jj", "z", "dd", "q", "aa", "k", "bb",
"r", "e", "j", "j", "ii", "y", "hh", "p", "p", "u", "gg", "ff",
"p", "cc", "u", "dd", "n", "bb", "bb", "aa", "ff", "x", "k",
"w", "x", "j", "bb", "cc", "ii", "hh", "jj", "b", "hh", "y",
"u", "cc", "hh", "aa", "b", "jj", "hh", "gg", "y", "r", "a",
"aa", "aa", "z", "ff", "ee", "g", "hh", "hh", "cc", "hh", "hh",
"h", "l", "k"), analyte_code = c("e", "b", "b", "c", "f", "d",
"a", "a", "a", "d", "f", "c", "g", "a", "a", "e", "a", "e", "a",
NA, "c", "a", "d", "c", "d", "b", "a", "f", "a", "g", "b", "c",
"f", "f", "c", "a", "f", "a", "e", "g", "c", "a", "a", "b", "e",
"a", "e", "c", "a", "a", "a", "a", "b", "a", "e", "a", "f", "a",
"a", "a", "c", "e", "a", "e", "a", "c", "e", "c", "a", "e", "c",
"a", "a", "g", "c", "a", "b", "b", "f", "b", "e", "d", "d", "c",
"c", "a", "a", "b", "f", "f", "b", "a", "e", "g", "c", "a", "a",
"a", "e", "d"), Date = structure(c(13326, 14287, 14403, 17669,
16330, 18603, 17428, 15502, 18708, 13780, 17757, 18582, 18087,
18582, 17433, 13326, 17674, 13668, 18059, 17966, 16701, 17142,
14915, 16861, 13999, 15502, 15412, 16856, 14551, 18708, 12128,
14314, 13326, 12563, 13780, 17224, 17611, 15703, 16239, 13780,
12970, 16096, 16544, 17134, 18603, 13780, 18388, 15684, 19157,
18684, 17449, 18857, 15075, 18746, 12683, 15618, 17142, 18634,
15601, 17065, 15926, 12970, 17611, 16692, 13943, 12871, 16958,
13263, 13451, 16179, 13094, 15044, 18131, 12212, 15966, 16410,
14775, 13283, 16239, 16391, 17050, 13283, 16085, 16330, 17362,
18393, 18087, 13724, 14396, 14396, 17331, 19106, 14215, 13388,
14088, 18241, 18143, 17187, 13486, 12482), class = "Date")), row.names = c(NA,
100L), class = "data.frame")
Does this give you what you are after? Note I changed the return of the function to be a list.
find_sample_gaps<-function(site, analyte, df){
Sample <- df%>%
filter(site_code == site)%>%filter(analyte_code == analyte)%>%
mutate(Year = as.numeric(format(Date, '%Y')))
x<-Sample%>%
group_by(Year)%>%
summarize(n_samples = length(Year))
gaps<-which(c(1,diff(x$Year))>1)
a<-sum(x$n_samples)
b<-length(unique(Sample$Date))
c<-'No gaps'
if(length(gaps)>0){
c<-paste('There are', as.character(gaps), 'gaps')
}
comb <- list(a = a, b = b, c = c)
return(comb)
}
output3 <- output1 %>%
mutate(a = find_sample_gaps(site, analyte, all_of(output2))$a,
b = find_sample_gaps(site, analyte, all_of(output2))$b,
c = find_sample_gaps(site, analyte, all_of(output2))$c)
output3
site_code analyte_code a b c
<chr> <chr> <int> <int> <chr>
1 a a 1 1 No gaps
2 b a 1 1 No gaps
3 c a 1 1 No gaps
4 d a 1 1 No gaps
5 e a 1 1 No gaps
6 f a 1 1 No gaps
7 g a 1 1 No gaps
8 h a 1 1 No gaps
9 i a 1 1 No gaps
10 j b 1 1 No gaps