How to use full join In R Language

In this method of joining data,  the user calls the right_join function and  this will result in jointed data  of all the rows from the joined tables,

full_join() function:

This function includes all rows.

Syntax:

full_join(x, y, by = NULL, on = NULL)

Parameters:

  • x: A data.table
  • y: A data.table
  • by: A character vector of variables to join by.
  • on: Indicate which columns in x should be joined with which columns in y.

Example:

In this example, we will be using the full_join() function from the dplyr package to join two different data as shown in the image above in the R programming language.

R




# load library
library("dplyr")  
  
# create dataframe
gfg1<-data.frame(ID=c(1:5))
gfg2<-data.frame(ID=c(4:8))
  
# perform full join
full_join(gfg1,gfg2, by = "ID")    


Output:

  ID
1  1
2  2
3  3
4  4
5  5
6  6
7  7
8  8

Joining Data in R with Dplyr Package

In this article, we will be looking at the different methods of joining data with the dplyr in the R programming language.

We need to load the dplyr package. Type the below commands –

Install - install.packages("dplyr")          
Load - library("dplyr") 

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Method 1: Using  inner join

In this method of joining data,  the user call the inner_join function, which will result to jointed data with the records that have matching values in both tables in the R programming language....

Method 2: Using  left join

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Method 3: Using  right join

In this method of joining data,  the user call the left_join function and this will result to jointed data consisting of matching all the rows in the first data frame with the corresponding values on the second.s in the R programming language....

Method 4: Using full join

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Method 5: Using Semi join

In this method of joining data, the user call the right_join function and this will result to jointed data consisting of matching all the rows in the second data frame with the corresponding values on the first in the R programming language....

Method 6:  Using anti join

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