In this tutorial, we will get knowledge about R merge CSV files. When working with CSV files in R, you usually have a need to merge those CSV files. We will provide you with two popular solutions: using rbind() and merge(). These are built-in functions so you don’t need to install external packages.
Merge csv files in R
Using rbind()
Rbind() stands for row binding. It will join multiple rows into a table.
Syntax:
rbind(x,y,..z)
Parameters:
- x: This is the first data frame or objects to be merged.
- y: This is the second data frame or objects to be merged.
- z: This is the last data frame or objects to be merged.
Assume you have three CSV files that contain the same data structure as follows:
Category, Views
R, 2555
JavaScript, 754Category, Views
Python, 355
SQL, 1823Category, Views
C++, 9999
Go, -1We will use the read.csv() function to read and store data in those files to merge them later.
# Read the first CSV file and store it in a data frame data1 <- read.csv(file='learnshareit1.csv',sep=',',header=T) # Read the second CSV file and store it in a data frame data2 <- read.csv(file='learnshareit2.csv',sep=',',header=T) # Read the last CSV file and store it in a data frame data3 <- read.csv(file='learnshareit3.csv',sep=',',header=T) # Merge all CSV files read learnshareit <- rbind(data1, data2, data3) # Display the result learnshareit
Output
> learnshareit
Category Views
1 R 2555
2 JavaScript 754
3 Python 355
4 SQL 1823
5 C++ 9999
6 Go -1As can be seen, after we merge CSV files in R, we receive a data frame with one header row, and the data rows are all the rows that are represented in each CSV file. This is just an example of merging three files; however, if you have more files, you can apply the same read method and then rbind() function with more arguments as much as you want.
Using merge()
To perform R merge CSV files, you can use merge() function in R (See the syntax here). To make it simple, we will reuse the first two CSV files we have declared in the previous solution and just apply the method on two data tables stored only:
# Merge two CSV files read learnshareit <- merge(data1, data2, all=TRUE) # Display the result learnshareit
Output
> learnshareit
Category Views
1 JavaScript 754
2 R 2555
3 Python 355
4 SQL 1823Can you realize the differences between the two results in each solution? This merge function can merge two CSV files instead of many files like the rbind() function. Therefore, if you want to merge more than two csv files, you should reuse more merge() functions as follows:
# Merge first and second csv files learnshareit1 <- merge(data1, data2, all=TRUE) # Merge the merged table and last csv files learnshareit <- merge(learnshareit1, data3, all=TRUE) # Display the result learnshareit
Output:
> learnshareit
Category Views
1 JavaScript 754
2 R 2555
3 Python 355
4 SQL 1823
5 C++ 9999
6 Go -1However, you should remember to pass an argument all = TRUE to this function if you want to merge the data rows in these files.
Summary
We have learned how to merge CSV files in R using two different approaches. Depending on how many files you want to merge, you can consider using any function. Generally, the first solution is proved more efficient when solving this problem. Let’s try it!
Maybe you are interested:
I’m Edward Anderson. My current job is as a programmer. I’m majoring in information technology and 5 years of programming expertise. Python, C, C++, Javascript, Java, HTML, CSS, and R are my strong suits. Let me know if you have any questions about these programming languages.
Name of the university: HCMUT
Major: CS
Programming Languages: Python, C, C++, Javascript, Java, HTML, CSS, R
