library("dplyr")
library("tidylog", warn.conflicts = FALSE)

filtered <- filter(mtcars, cyl == 4)
#> filter: removed 21 rows (66%)

summary <- mtcars %>%
    select(mpg, cyl, hp) %>%
    filter(mpg > 15) %>%
    mutate(mpg_round = round(mpg)) %>%
    group_by(cyl, mpg_round) %>%
    tally() %>%
    filter(n >= 1)
#> select: dropped 8 variables (disp, drat, wt, qsec, vs, …) 
#> filter: removed 6 rows (19%) 
#> mutate: new variable 'mpg_round' with 15 unique values and 0% NA 
#> group_by: 17 groups [cyl, mpg_round] 
#> filter: no rows removed

devtools::install_github("elbersb/tidylog")

a <- filter(mtcars, mpg > 20)
#> filter: removed 18 rows (56%)
b <- filter(mtcars, mpg > 100)
#> filter: removed all rows (100%)
c <- filter(mtcars, mpg > 0)
#> filter: no rows removed
d <- filter_at(mtcars, vars(starts_with("d")), any_vars((. %% 2) == 0))
#> filter_at: removed 19 rows (59%)
e <- distinct(mtcars)
#> distinct: no rows removed

a <- mutate(mtcars, new_var = 1)
#> mutate: new variable 'new_var' with one unique value and 0% NA
b <- mutate(mtcars, new_var = runif(n()))
#> mutate: new variable 'new_var' with 32 unique values and 0% NA
c <- mutate(mtcars, new_var = NA)
#> mutate: new variable 'new_var' with one unique value and 100% NA
d <- mutate_at(mtcars, vars(mpg, gear, drat), round)
#> mutate_at: changed 28 values (88%) of 'mpg' (0 new NA) 
#> mutate_at: changed 31 values (97%) of 'drat' (0 new NA)
e <- mutate(mtcars, am_factor = as.factor(am))
#> mutate: new variable 'am_factor' with 2 unique values and 0% NA
f <- mutate(mtcars, am = as.factor(am))
#> mutate: converted 'am' from double to factor (0 new NA)
g <- mutate(mtcars, am = ifelse(am == 1, NA, am))
#> mutate: changed 13 values (41%) of 'am' (13 new NA)
h <- mutate(mtcars, am = recode(am, `0` = "zero", `1` = NA_character_))
#> mutate: converted 'am' from double to character (13 new NA)

i <- transmute(mtcars, mpg = mpg * 2, gear = gear + 1, new_var = vs + am)
#> transmute: dropped 9 variables (cyl, disp, hp, drat, wt, …) 
#> transmute: changed 32 values (100%) of 'mpg' (0 new NA) 
#> transmute: changed 32 values (100%) of 'gear' (0 new NA) 
#> transmute: new variable 'new_var' with 3 unique values and 0% NA

a <- select(mtcars, mpg, wt)
#> select: dropped 9 variables (cyl, disp, hp, drat, qsec, …)
b <- select(mtcars, matches("a"))
#> select: dropped 7 variables (mpg, cyl, disp, hp, wt, …)
c <- select_if(mtcars, is.character)
#> select_if: dropped all variables

a <- band_members %>% left_join(band_instruments, by = "name")
#> left_join: added 0 rows and added one column (plays)
b <- band_members %>% full_join(band_instruments, by = "name")
#> full_join: added one row and added one column (plays)
c <- band_members %>% anti_join(band_instruments, by = "name")
#> anti_join: removed 2 rows and added no new columns