In R you use the merge function to combine data frames. This powerful function tries to identify columns or rows that are common between the two different data frames. How to use merge to find the intersection of data The simplest form of merge finds the intersection between two. Example 1: Combine Data by Two ID Columns Using merge Function. In Example 1, I’ll illustrate how to apply the merge function to combine data frames based on multiple ID columns. For this, we have to specify the by argument of the merge function to be equal to. The merge function takes these two data frames as argument which unions these two dataframes with an option all=TRUE as shown below # union in R - union of data frames in R dfunion1merge(df1,df2,all=TRUE) dfunion1 so the resultant data frame will be. Thus we have applied union in R.
Recipe Objective
In formation of a database, all the data cannot be stored in one table to avoid duplicacy. To extract specific information out of the database, we merge two or more tables using a common field. The merging takes place w.r.t the concept of joins. There are 5 types of joins:
- Inner join: Returns only matching records
- Outer join: Returns all records including no matches in both directions
- Left Join: Returns all records in left dataframe and only matching records from the other
- Right Join : Returns all records in right dataframe and only matching records from the other
- Cross join: Returns all the possible combination of records in both the dataframes
To merge 2 dataframes in R, we use merge() function to do so. In this recipe, we will learn how to merge two dataframe in R using an example.
Step 1: Loading required library and creating 2 dataframes.
Taking an example of university database with 1 table to be of personal details and the other as courses enrolled Medibang paint shortcuts.
#Data manipulation library(tidyverse) # Dataframe 1: personal_details = data.frame(Student_ID = c(1:5), Name = c('Siddhi', 'Jessica', 'Nisarg', 'Vishal', 'Fredo'), Address = c('Mumbai', 'Mumbai', 'Pune', 'Madgaon', 'Nashik')) #Dataframe 2: courses = data.frame(Student_ID = c(2,3,5,8), Course = c('Chemistry', 'Physics', 'Computer Science', 'History')) print(personal_details) print(courses)
Merging the two dataframes
We use the common field 'Student_ID' for merging the data using merge() function.
Syntax: merge(x , y, by = , all.x = , all.y = , all = )
Malwarebytes sale. where:
- x = dataframe 1
- y = dataframe 2
- by = common field by which the merging takes place
- all, all.x, all.y = logical values which indicates the type of merge. The default value of all is FALSE(i.e. it returns only the matching rows)
1. Inner Join
![Join Join](/uploads/1/3/7/5/137531291/884581022.jpg)
inner = merge(x=personal_details,y=courses,by='Student_ID') inner
2. Outer Join: (condition: all = TRUE)
outer = merge(x=personal_details,y=courses,by='Student_ID', all = TRUE) outer
3. Left Join: (Condition: all.x = TRUE)
Join Two Data Frame R
left = merge(x=personal_details,y=courses,by='Student_ID', all.x = TRUE) left
4. Right Join: (Condition: all.y = TRUE)
Join Two Dataframes Together
right = merge(x=personal_details,y=courses,by='Student_ID', all.y = TRUE) right