Data wrangling help dplyr

tidyverse
5

If you want to get specific help, you would need to provide a proper REPRoducible EXample (reprex) illustrating your issue. I'm going to make one for you this time but please have in mind that this is not your first time here and at this point, you should be following good practices on the forum.

library(dplyr)

# Sample data on a copy/paste friendly format
bees <- data.frame(
  stringsAsFactors = FALSE,
               mth = c("Jan", "Jan", "Jan", "Jan", "Jan", "Jan"),
               m_y = c("Jan-18","Jan-18","Jan-18",
                       "Jan-18","Jan-18","Jan-18"),
             event = c(1, 1, 1, 1, 1, 1),
              trap = c("NE-1", "NE-2", "NW-1", "NW-1", "NW-2", "NW-2"),
              site = c("NE", "NE", "NW", "NW", "NW", "NW"),
              taxa = c("Agapostemon",
                       "Lasioglossum dialictus","Lasioglossum dialictus","Apis mellifera",
                       "Augochlorella","Lasioglossum dialictus"),
            counts = c(1, 2, 12, 2, 1, 6),
        normalized = c(0.111, 0.222, 1.33, 0.222, 0.111, 0.667),
             units = c("number/day","number/day",
                       "number/day","number/day","number/day","number/day")
)

bees %>%
    group_by(m_y, site) %>% 
    summarise(sum_normal = sum(normalized))
#> `summarise()` regrouping output by 'm_y' (override with `.groups` argument)
#> # A tibble: 2 x 3
#> # Groups:   m_y [1]
#>   m_y    site  sum_normal
#>   <chr>  <chr>      <dbl>
#> 1 Jan-18 NE         0.333
#> 2 Jan-18 NW         2.33
1 Like