Advanced functionalities"

In joyn: Tool for Diagnosis of Tables Joins and Complementary Join Features

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(joyn)
library(data.table)

x <- data.table(id = c(1, 4, 2, 3, NA),
                t  = c(1L, 2L, 1L, 2L, NA),
                country = c(16, 12, 3, NA, 15))

y <- data.table(id  = c(1, 2, 5, 6, 3),
                gdp = c(11L, 15L, 20L, 13L, 10L),
                country = 16:20)

Advanced use

This vignette will let you explore some additional features available in joyn, through an example use case.

Suppose you want to join tables x and y, where the variable country is available in both. You could do one of five things:

1. Use variable country as one of the key variables

If you don't use the argument by, joyn will consider country and id as key variables by default given that they are common between x and y.

# The variables with the same name, `id` and `country`, are used as key
# variables.

joyn(x = x, 
     y = y)

Alternatively, you can specify to join by country

# Joining by country

joyn(x = x, 
     y = y, 
     by = "country")

2. Ignore the values of country from y and don't bring it into the resulting table

This the default if you did not include country as part of the key variables in argument by.

joyn(x = x, 
     y = y, 
     by = "id")

3. Update only NAs in table x

Another possibility is to make use of the update_NAs argument of joyn(). This allows you to update the NAs values in variable country in table x with the actual values of the matching observations in country from table y. In this case, actual values in country from table x will remain unchanged.

joyn(x = x,
     y = y, 
     by = "id", 
     update_NAs = TRUE)

4. Update actual values in table x

You can also update all the values - both NAs and actual - in variable country of table x with the actual values of the matching observations in country from y. This is done by setting update_values = TRUE.

Notice that the reportvar allows you keep track of how the update worked. In this case, value update means that only the values that are different between country from x and country from y are updated.

However, let's consider other possible cases:

• If, for the same matching observations, the values between the two country variables were the same, the reporting variable would report x & y instead (so you know that there is no update to make).

• if there are NAs in country from y, the actual values in x will be unchanged, and you would see a not updated status in the reporting variable. Nevertheless, notice there is another way for you to bring country from y to x. This is done through the argument keep_y_in_x (see 5. below ⬇️)

# Notice that only the value that are 

joyn(x = x, 
     y = y, 
     by = "id", 
     update_values = TRUE)

5. Keep original country variable from y into returning table

(Keep matching-names variable from y into x -not updating values in x)

Another available option is that of bringing the original variable country from y into the resulting table, without using it to update the values in x. In order to distinguish country from x and country from y, joyn will assign a suffix to the variable's name: so that you will get country.y and country.x. All of this can be done specifying keep_common_vars = TRUE.

joyn(x = x, 
     y = y, 
     by = "id", 
     keep_common_vars = TRUE)

Bring other variables from y into returning table

In joyn , you can also bring non common variables from y into the resulting table. In fact you can specify them in y_vars_to_keep, as shown in the example below:

# Keeping variable gdp 

joyn(x = x, 
     y = y, 
     by = "id", 
     y_vars_to_keep = "gdp")

Notice that if you set y_vars_to_keep = FALSE or y_vars_to_keep = NULL, then joyn won't bring any variable into the returning table.

joyn documentation built on April 4, 2025, 5:23 a.m.