join: Join table by common keys

In hope-data-science/tidydt: Tidy Verbs for 'data.table'

Description

Join operations.

Usage

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

Examples

# use the examples from `maditr` package
library(data.table)
library(tidydt)

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)
workers %>% left_join_dt(positions)
workers %>% right_join_dt(positions)
workers %>% full_join_dt(positions)

# filtering joins
workers %>% anti_join_dt(positions)
workers %>% semi_join_dt(positions)

# To suppress the message, supply 'by' argument
workers %>% left_join_dt(positions, by = "name")

# 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"))

hope-data-science/tidydt documentation built on Feb. 21, 2020, 10:25 a.m.