Subsetting under multiple conditions

I want to return the number of Transmitter codes that have been seen in both Season Winter1 AND Winter2. The answer should be 6 (6 different codes that were seen in Winter1 and Winter2). But the following command returns 0:

length(unique(Dispersion[(Dispersion$Season == "Winter1") & (Dispersion$Season == "Winter2"),]$Transmitter))

What command is appropriate for my problem?

structure(list(Transmitter = c("A69-1602-59814", "A69-1602-59814", 
"A69-1602-59815", "A69-1602-59815", "A69-1602-59819", "A69-1602-59820", 
"A69-1602-59821", "A69-1602-59822", "A69-1602-59823", "A69-1602-59824", 
"A69-1602-59825", "A69-1602-59826", "A69-1602-59826", "A69-1602-59827", 
"A69-1602-59828", "A69-1602-59828", "A69-1602-59830", "A69-1602-59831", 
"A69-1602-59831", "A69-1602-59832", "A69-1602-59833", "A69-1602-59834", 
"A69-1602-59835", "A69-1602-59835", "A69-1602-59836"), Batch.location = c("Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer"), Location.Dispersion = c("Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
"Lemmer", "Lemmer", "Lemmer"), Season = c("Winter1", "Winter2", 
"Winter1", "Winter2", "Winter1", "Winter1", "Winter1", "Winter1", 
"Winter1", "Winter1", "Winter1", "Winter1", "Winter2", "Winter1", 
"Winter1", "Winter2", "Winter1", "Winter1", "Winter2", "Winter1", 
"Winter1", "Winter1", "Winter1", "Winter2", "Winter1"), Freq = c(1961L, 
2075L, 310L, 1L, 2880L, 305L, 366L, 834L, 19L, 2580L, 564L, 997L, 
3475L, 6447L, 988L, 2991L, 355L, 3147L, 6155L, 903L, 484L, 321L, 
76L, 1921L, 3329L)), row.names = c(NA, -25L), groups = structure(list(
    Transmitter = c("A69-1602-59814", "A69-1602-59815", "A69-1602-59819", 
    "A69-1602-59820", "A69-1602-59821", "A69-1602-59822", "A69-1602-59823", 
    "A69-1602-59824", "A69-1602-59825", "A69-1602-59826", "A69-1602-59827", 
    "A69-1602-59828", "A69-1602-59830", "A69-1602-59831", "A69-1602-59832", 
    "A69-1602-59833", "A69-1602-59834", "A69-1602-59835", "A69-1602-59836"
    ), Batch.location = c("Lemmer", "Lemmer", "Lemmer", "Lemmer", 
    "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
    "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
    "Lemmer", "Lemmer", "Lemmer"), Location.Dispersion = c("Lemmer", 
    "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
    "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", 
    "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer", "Lemmer"
    ), .rows = structure(list(1:2, 3:4, 5L, 6L, 7L, 8L, 9L, 10L, 
        11L, 12:13, 14L, 15:16, 17L, 18:19, 20L, 21L, 22L, 23:24, 
        25L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -19L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

>Solution :

You need to group by Transmitter (missing from your attempt) and ensure that both values are in each group of Season.

dplyr

library(dplyr)
out <- dat %>%
  group_by(Transmitter) %>%
  filter(all(c("Winter1", "Winter2") %in% Season)) %>%
  ungroup()
out
# # A tibble: 12 x 5
#    Transmitter    Batch.location Location.Dispersion Season   Freq
#    <chr>          <chr>          <chr>               <chr>   <int>
#  1 A69-1602-59814 Lemmer         Lemmer              Winter1  1961
#  2 A69-1602-59814 Lemmer         Lemmer              Winter2  2075
#  3 A69-1602-59815 Lemmer         Lemmer              Winter1   310
#  4 A69-1602-59815 Lemmer         Lemmer              Winter2     1
#  5 A69-1602-59826 Lemmer         Lemmer              Winter1   997
#  6 A69-1602-59826 Lemmer         Lemmer              Winter2  3475
#  7 A69-1602-59828 Lemmer         Lemmer              Winter1   988
#  8 A69-1602-59828 Lemmer         Lemmer              Winter2  2991
#  9 A69-1602-59831 Lemmer         Lemmer              Winter1  3147
# 10 A69-1602-59831 Lemmer         Lemmer              Winter2  6155
# 11 A69-1602-59835 Lemmer         Lemmer              Winter1    76
# 12 A69-1602-59835 Lemmer         Lemmer              Winter2  1921

And from here you can use n_distinct or something else to count the unique Transmitter values you need.

summarize(out, n = n_distinct(Transmitter))
# # A tibble: 1 x 1
#       n
#   <int>
# 1     6

or just

length(unique(out$Transmitter))
# [1] 6

base R, option 1

ind <- ave(dat$Season, dat$Transmitter,
           FUN = function(z) all(c("Winter1", "Winter2") %in% z)) == "TRUE"
ind
#  [1]  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE FALSE
# [21] FALSE FALSE  TRUE  TRUE FALSE
dat[ind,]
# ...

length(unique(dat[ind, "Transmitter"]))
# [1] 6

The == "TRUE" use of a character "TRUE" is because ave forces the return value to be the same class as its first argument, which is dat$Season. Internally it calculates logical but is coerced to string afterwards. (Just run the ave(..) without ==... to see this in action.)

base R, option 2

sum(aggregate(Season ~ Transmitter, data = dat,
              FUN = function(z) all(c("Winter1", "Winter2") %in% z))$Season)
# [1] 6