Print examples for an R function of interest in console

Usage

forgot_exmpls(pkg, function_name, write = FALSE)

Arguments

pkg: string with installed R package name
function_name: function name in R package
write: logical write to RStudio rmd file, FALSE by default

Examples

forgot_exmpls("dplyr", "count")
#> 
#> # count() is a convenient way to get a sense of the distribution of
#> # values in a dataset
#> starwars %>% count(species)
#> starwars %>% count(species, sort = TRUE)
#> starwars %>% count(sex, gender, sort = TRUE)
#> starwars %>% count(birth_decade = round(birth_year, -1))
#> 
#> # use the `wt` argument to perform a weighted count. This is useful
#> # when the data has already been aggregated once
#> df <- tribble(
#>   ~name,    ~gender,   ~runs,
#>   "Max",    "male",       10,
#>   "Sandra", "female",      1,
#>   "Susan",  "female",      4
#> )
#> # counts rows:
#> df %>% count(gender)
#> # counts runs:
#> df %>% count(gender, wt = runs)
#> 
#> # When factors are involved, `.drop = FALSE` can be used to retain factor
#> # levels that don't appear in the data
#> df2 <- tibble(
#>   id = 1:5,
#>   type = factor(c("a", "c", "a", NA, "a"), levels = c("a", "b", "c"))
#> )
#> df2 %>% count(type)
#> df2 %>% count(type, .drop = FALSE)
#> 
#> # Or, using `group_by()`:
#> df2 %>% group_by(type, .drop = FALSE) %>% count()
#> 
#> # tally() is a lower-level function that assumes you've done the grouping
#> starwars %>% tally()
#> starwars %>% group_by(species) %>% tally()
#> 
#> # both count() and tally() have add_ variants that work like
#> # mutate() instead of summarise
#> df %>% add_count(gender, wt = runs)
#> df %>% add_tally(wt = runs)
forgot_exmpls(dplyr, count, write = FALSE)
#> 
#> # count() is a convenient way to get a sense of the distribution of
#> # values in a dataset
#> starwars %>% count(species)
#> starwars %>% count(species, sort = TRUE)
#> starwars %>% count(sex, gender, sort = TRUE)
#> starwars %>% count(birth_decade = round(birth_year, -1))
#> 
#> # use the `wt` argument to perform a weighted count. This is useful
#> # when the data has already been aggregated once
#> df <- tribble(
#>   ~name,    ~gender,   ~runs,
#>   "Max",    "male",       10,
#>   "Sandra", "female",      1,
#>   "Susan",  "female",      4
#> )
#> # counts rows:
#> df %>% count(gender)
#> # counts runs:
#> df %>% count(gender, wt = runs)
#> 
#> # When factors are involved, `.drop = FALSE` can be used to retain factor
#> # levels that don't appear in the data
#> df2 <- tibble(
#>   id = 1:5,
#>   type = factor(c("a", "c", "a", NA, "a"), levels = c("a", "b", "c"))
#> )
#> df2 %>% count(type)
#> df2 %>% count(type, .drop = FALSE)
#> 
#> # Or, using `group_by()`:
#> df2 %>% group_by(type, .drop = FALSE) %>% count()
#> 
#> # tally() is a lower-level function that assumes you've done the grouping
#> starwars %>% tally()
#> starwars %>% group_by(species) %>% tally()
#> 
#> # both count() and tally() have add_ variants that work like
#> # mutate() instead of summarise
#> df %>% add_count(gender, wt = runs)
#> df %>% add_tally(wt = runs)
if (FALSE) { # \dontrun{
forgot_exmpls("dplyr", "count", write = TRUE)
} # }