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Dplyr

group_split()

df %>%
  # split by indicator and set name
  dplyr::group_split(
    indicator, # by
    .keep = T  # if keep the grouped variable
  ) %>%
  # set names
  purrr::set_names(
    purrr::map_chr(
      ., 
      ~ .x$indicator[1]
      )
  )

mutate()

mutate_at()

affects variables selected with a character vector or vars() 

scale2 <- function(x, na.rm = FALSE) (x - mean(x, na.rm = na.rm)) / sd(x, na.rm)
starwars %>% mutate_at(c("height", "mass"), scale2)
starwars %>% mutate(across(c("height", "mass"), scale2))

mutate_if()

affects variables selected with a predicate function 

tbl %>% mutate_if(is.numeric, funs(replace_na(.,0)))

iris %>%
  as_tibble() %>%
  mutate(across(where(is.numeric), list(scale = scale2, log = log)))

rename()

rename_at()

dplyr::rename_at(vars(BC:Interior), function(x) paste0(x,"_24"))
dplyr::rename_at(vars(-class), ~ paste0(., "_2014"))

rename_with()

rename_with(
  iris,
  ~ paste0("prefix_", .x, recycle0 = TRUE),
  starts_with("nonexistent")
)

data %>% 
  rename_with(
    .cols = matches('tally'),
    .fn   = ~ str_remove(.x, 'tally_')
  )

# change all column names to title style except start with hsda
df %>% rename_with(str_to_title, !starts_with("hsda"))

# change all `ha` to `residential_ha` in column names
df %>% rename_with(~ 'residential_ha', matches('ha$'))

relocate()

relocate(df, date_end, .after = date_start)

Set options

Intersection \(A \cap B\)

intersect

intersect(A, B) finds all rows in both A and B.

inner_join(A, B) only keeps observations from xA that have a matching key in B. Same with base r: merge(A, B)

Union \(A \cup B\)

intersect

union(A, B) finds all rows in either A or B, excluding duplicates.

union_all(A, B) finds all rows in either A or B, including duplicates.

semi_join(A, B) returns all rows from x with a match in y. Same with base r: A[A$x %in% B$x, , drop = FALSE]

full_join(A, B) keeps all observations in A and B. Same with base r: merge(A, B, all = TRUE)

Set difference \(A-B\)

intersect

setdiff(A, B) finds all rows in A that aren't in B.

anti_join(A, B) returns all rows from A without a match in B. Same with base r: A[!A$x %in% B$x, , drop = FALSE]

Symmetric difference \(A \Delta B\)

intersect

symdiff(A, B) computes the symmetric difference, i.e. all rows in A that aren't in B and all rows in B that aren't in A.