Select non-consecutive dates for every grouped element in R

In a previous question, I had asked to select n Number of random non-consecutive dates for every grouped element in R. However, I would like to select x Number of dates per site in order to maximize the combination of sites and days.

Here's what the data looks like:

dput(uniqueSiteDate)

structure(list(Site = c("HP37P1B", "HP37P2B", "HP37P4B", "HP4008U", 
"INME03R", "INME03U", "INOA03R", "IPTO04R", "IPTO04U", "IPTO06R", 
"IPTO06U", "OLCAP2B", "OLCAP3B", "OLCAP5B", "PANMP1B", "PANMP2B", 
"PANMP3B", "STIN02R", "STIN02U", "UPMAP1B", "UPMAP3B", "UPMAP4B", 
"UPMAP5B", "UPMAP6B", "VAR210R", "VAR310R", "VAR310U", "VAR410R", 
"VAR410U", "HP36P1B", "HP36P3B", "HP36P4B", "HP4008R", "INBS04R", 
"INBS04U", "SEL107R", "SEL107U", "SEL207R", "SEL207U", "OLV110R", 
"OLV110U", "OLV208R", "OLV208U", "THEN10U", "HP37P1B", "HP37P2B", 
"HP37P4B", "HP4008U", "INME03R", "INME03U", "INOA03R", "IPTO04R", 
"IPTO04U", "IPTO06R", "IPTO06U", "OLCAP2B", "OLCAP3B", "OLCAP5B", 
"PANMP1B", "PANMP2B", "PANMP3B", "STIN02R", "STIN02U", "UPMAP1B", 
"UPMAP3B", "UPMAP4B", "UPMAP5B", "UPMAP6B", "VAR210R", "VAR310R", 
"VAR310U", "VAR410R", "VAR410U", "OLV110R", "OLV110U", "OLV208R", 
"OLV208U", "THEN10U", "HP37P1B", "HP37P2B", "HP37P4B", "HP4008U", 
"INME03R", "INME03U", "INOA03R", "IPTO04R", "IPTO04U", "IPTO06R", 
"IPTO06U", "OLCAP2B", "OLCAP3B", "OLCAP5B", "PANMP1B", "PANMP2B", 
"PANMP3B", "STIN02R", "STIN02U", "UPMAP1B", "UPMAP3B", "UPMAP4B", 
"UPMAP5B", "UPMAP6B", "VAR210R", "VAR310R", "VAR310U", "VAR410R", 
"VAR410U", "OLV110R", "OLV110U", "OLV208R", "OLV208U", "THEN10U", 
"HP37P1B", "HP37P2B", "HP37P4B", "HP4008U", "INME03R", "INME03U", 
"INOA03R", "IPTO04R", "IPTO04U", "IPTO06R", "IPTO06U", "OLCAP2B", 
"OLCAP3B"), Date = structure(c(18333, 18333, 18333, 18333, 18335, 
18335, 18335, 18338, 18335, 18338, 18335, 18333, 18333, 18333, 
18334, 18334, 18334, 18331, 18331, 18331, 18330, 18330, 18330, 
18330, 18332, 18332, 18332, 18332, 18332, 18325, 18325, 18325, 
18325, 18327, 18327, 18327, 18327, 18327, 18328, 18340, 18340, 
18340, 18340, 18340, 18334, 18334, 18334, 18334, 18336, 18336, 
18336, 18339, 18336, 18340, 18336, 18335, 18334, 18334, 18335, 
18335, 18335, 18332, 18332, 18332, 18331, 18331, 18331, 18331, 
18333, 18333, 18333, 18333, 18333, 18341, 18341, 18341, 18341,
18341, 18335, 18335, 18335, 18335, 18383, 18383, 18383, 18384, 
18384, 18384, 18384, 18385, 18385, 18335, 18342, 18342, 18341, 
18383, 18383, 18345, 18349, 18349, 18349, 18349, 18340, 18339, 
18340, 18341, 18339, 18386, 18386, 18348, 18346, 18347, 18328, 
18328, 18328, 18328, 18390, 18389, 18391, 18392, 18392, 18392, 
18392, 18392, 18392), class = "Date")), row.names = c(NA, -125L
), groups = structure(list(Site = c("HP36P1B", "HP36P3B", "HP36P4B", 
"HP37P1B", "HP37P2B", "HP37P4B", "HP4008R", "HP4008U", "INBS04R", 
"INBS04U", "INME03R", "INME03U", "INOA03R", "IPTO04R", "IPTO04U", 
"IPTO06R", "IPTO06U", "OLCAP2B", "OLCAP3B", "OLCAP5B", "OLV110R", 
"OLV110U", "OLV208R", "OLV208U", "PANMP1B", "PANMP2B", "PANMP3B", 
"SEL107R", "SEL107U", "SEL207R", "SEL207U", "STIN02R", "STIN02U", 
"THEN10U", "UPMAP1B", "UPMAP3B", "UPMAP4B", "UPMAP5B", "UPMAP6B", 
"VAR210R", "VAR310R", "VAR310U", "VAR410R", "VAR410U"), .rows = structure(list(
    30L, 31L, 32L, c(1L, 45L, 79L, 113L), c(2L, 46L, 80L, 114L
    ), c(3L, 47L, 81L, 115L), 33L, c(4L, 48L, 82L, 116L), 34L, 
    35L, c(5L, 49L, 83L, 117L), c(6L, 50L, 84L, 118L), c(7L, 
    51L, 85L, 119L), c(8L, 52L, 86L, 120L), c(9L, 53L, 87L, 121L
    ), c(10L, 54L, 88L, 122L), c(11L, 55L, 89L, 123L), c(12L, 
    56L, 90L, 124L), c(13L, 57L, 91L, 125L), c(14L, 58L, 92L), 
    c(40L, 74L, 108L), c(41L, 75L, 109L), c(42L, 76L, 110L), 
    c(43L, 77L, 111L), c(15L, 59L, 93L), c(16L, 60L, 94L), c(17L, 
    61L, 95L), 36L, 37L, 38L, 39L, c(18L, 62L, 96L), c(19L, 63L, 
    97L), c(44L, 78L, 112L), c(20L, 64L, 98L), c(21L, 65L, 99L
    ), c(22L, 66L, 100L), c(23L, 67L, 101L), c(24L, 68L, 102L
    ), c(25L, 69L, 103L), c(26L, 70L, 104L), c(27L, 71L, 105L
    ), c(28L, 72L, 106L), c(29L, 73L, 107L)), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -44L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

Expected Output: For example - HP37P1B has 4 unique dates associated with it - 7th March, 12th March, 13th March and 14th March. The output dataframe should have 7th March, 12th March and 14th March after following the process of selection. Sometimes there are more than 3 dates per site, but sometimes there is just 1 date per site. But the idea is to choose n Number of non-consecutive dates given a Site. In other words, if a particular site has 4 dates, I need 3 non-consecutive ones. If a particular site has only 1 date, let's just leave that in. I suppose an answer might lie in choosing odd dates?

Solution

Check if it works?

It first selects a maximum number of possible rows (odd numbered rows will always be maximum than even numbered rows)
thereafter three per group

df %>% 
  ungroup() %>% 
  group_split(Site) %>% 
  map_df(., ~ .x %>% ungroup() %>%
           arrange(Date) %>%
           mutate(n = 1) %>%
           complete(Date = seq.Date(first(Date), last(Date), by = 'days')) %>%
           group_by(n = cumsum(is.na(n))) %>%
           filter(!is.na(Site)) %>%
           filter(row_number() %% 2 == 1) %>%
           ungroup() %>%
           sample_n(min(n(), 3))
         ) %>%
  select(-n)

# A tibble: 91 x 2
   Date       Site   
   <date>     <chr>  
 1 2020-03-04 HP36P1B
 2 2020-03-04 HP36P3B
 3 2020-03-04 HP36P4B
 4 2020-03-07 HP37P1B
 5 2020-03-14 HP37P1B
 6 2020-03-12 HP37P1B
 7 2020-03-14 HP37P2B
 8 2020-03-07 HP37P2B
 9 2020-03-12 HP37P2B
10 2020-03-12 HP37P4B
# ... with 81 more rows