Count observations by group

Join operations, wrapped directly from maditr.

left_join_dt(x, y, by = NULL, suffix = c(".x", ".y"))

right_join_dt(x, y, by = NULL, suffix = c(".x", ".y"))

inner_join_dt(x, y, by = NULL, suffix = c(".x", ".y"))

full_join_dt(x, y, by = NULL, suffix = c(".x", ".y"))

anti_join_dt(x, y, by = NULL)

semi_join_dt(x, y, by = NULL)

Arguments

x	data.frame
y	data.frame
by	a character vector of variables to join by. If NULL, the default, *_join() will do a natural join, using all variables with common names across the two tables. A message lists the variables so that you can check they're right (to suppress the message, simply explicitly list the variables that you want to join). To join by different variables on x and y use a named vector. For example, by = c("a" = "b") will match x.a to y.b.
suffix	If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.

Value

data.table

See also

left_join,dt_left_join

Examples

# use the examples from `maditr` package
workers = fread("
    name company
    Nick Acme
    John Ajax
    Daniela Ajax
")

positions = fread("
    name position
    John designer
    Daniela engineer
    Cathie manager
")

workers %>% inner_join_dt(positions)
#> dt_inner_join: joining, by = "name"
#>       name company position
#> 1:    John    Ajax designer
#> 2: Daniela    Ajax engineer
workers %>% left_join_dt(positions)
#> dt_left_join: joining, by = "name"
#>       name company position
#> 1:    Nick    Acme     <NA>
#> 2:    John    Ajax designer
#> 3: Daniela    Ajax engineer
workers %>% right_join_dt(positions)
#> dt_right_join: joining, by = "name"
#>       name company position
#> 1:    John    Ajax designer
#> 2: Daniela    Ajax engineer
#> 3:  Cathie    <NA>  manager
workers %>% full_join_dt(positions)
#> dt_full_join: joining, by = "name"
#>       name company position
#> 1:    Nick    Acme     <NA>
#> 2:    John    Ajax designer
#> 3: Daniela    Ajax engineer
#> 4:  Cathie    <NA>  manager

# filtering joins
workers %>% anti_join_dt(positions)
#> dt_anti_join: joining, by = "name"
#>    name company
#> 1: Nick    Acme
workers %>% semi_join_dt(positions)
#> dt_semi_join: joining, by = "name"
#>       name company
#> 1:    John    Ajax
#> 2: Daniela    Ajax

# To suppress the message, supply 'by' argument
workers %>% left_join_dt(positions, by = "name")
#>       name company position
#> 1:    Nick    Acme     <NA>
#> 2:    John    Ajax designer
#> 3: Daniela    Ajax engineer

# Use a named 'by' if the join variables have different names
positions2 = setNames(positions, c("worker", "position")) # rename first column in 'positions'
workers %>% inner_join_dt(positions2, by = c("name" = "worker"))
#>       name company position
#> 1:    John    Ajax designer
#> 2: Daniela    Ajax engineer