While working on the Data Analysis process, it is quite common to operate “Reordering Columns in R” to meet certain requirements in any table. After reordering a few columns, it becomes easy to filter out some data from any large Table or Data Frame.
Reordering any column in a table boosts readability and lends extra support to any sizable project. It’s pretty straightforward to reorder columns using the R programming language. All you need is a grasp of the basics, and you’re good to go.
This article is going to describe different methods needed to Reorder Columns of any table in the R programming language. So, let’s start our discussion.
Summary or Key Highlights:
The Reorder Columns operation goes on the Data Structure Data Frame.
In R Programming Language Maximum tables are in the DataFrame format.
There are mostly three ways to change Column Positions in a Dataframe.
The columns can be rearranged in the alphabetical format as well.
From Data Processing to Data Visualization, rearranging columns of the table will be needed.
Some best tips should be practiced to understand the concept easily.
What Is A Data Frame In R Programming Language?
The Frame is the tabular format present in the R Programming Language that works as a spreadsheet in the programming language. Whatever table you are going to create in the R programming language will create the same Data Frame format.
In DataFrame, there are certain terms are highly used like Term, Column Names, Column Position, etc. However, they are not that much of important to know for understanding the current topic. The way more important thing is the process of defining FrameTable in the R programming language.
# Single Length Table or DF
df <- data.frame(A = c(1, 2, 3))
df <- data.frame(A = 1:3)
The above-mentioned two code snippet examples are used to declare single-column in the code. The same way we are going to use to find processes to reorder columns in R.
How To Reorder Columns In R Data Frame?
Now, it is time to work on the central plot of this topic. Here, we are going to mark the ways used to rearrange the columns of any table in the R Programming language. Moreover, these three ways are highly used to alter columns in R.
We will start with the Manual Mode Option. Later, we will discuss a few more paths to achieve our target. So, let us start our practical implementation journey.
By Name Of The Column
Here, the simple Name will be used to alter column positions in the following data frame. The first column has the position 1 & the 2nd column will have the position 2. Using this concept & one particular syntax. we can change the column position.
Syntax: FrameName[, c(Column Names)]
# Creating Of A Sample DataFrame (DF)
zap <- data.frame(A = c(101, 202, 303),
B = c(404, 505, 606),
C = c(707, 808, 909))
zap <- zap[, c("B", "C", "A")] # Reordering Table
print(zap)
Steps Of The Program:
We will declare a sample table using the above board discussion we made on it.
Now, we will print the original table in the Window to see changes later.
Using the above syntax, we are going to alter columns in the table. Here, the 2nd column is going to be the first one.
We will again print the table information for the verification process.
Output:
From the above example, we can see that the Table Structure in the first one is different from the second one. The B Column is now in the first position and the C Column is now in the 2nd position. This implies our code is successful.
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Using Base Function
Here, we are going to use a simple function that is the subset() function. Using the subset() functions, we will promptly change the column sequence in the table. We have to note down the syntax for the successful execution of the code.
Syntax: subset(FrameName, select = c(Column Name Sequence))
# Creating Of A Sample DataFrame (DF)
zap <- data.frame(A = c(100, 200, 300),
B = c(400, 500, 600),
C = c(700, 800, 900))
print(zap)
one <- subset(zap, select = c(C, A, B)) # Reordering Table
print(one)
Steps Of The Program:
The first step will be to declare one table using the proper process. And we will provide some variables’ names there.
Now, the table will be printed first before moving for any changes there.
Using the above syntax, we will make the changes. You can add any order to the sequence. It might be in ascending or descending order as per your choice.
Now, we will again print the table information.
Output:
From the above example, we can see that there is a clear difference between the first table & the last table. The last table follows the sequence that we have provided there. The first table follows the older version.
Using The DPLYR Package
Another great way to rearrange columns in the R programming language is the DPLYR Package. It is the package that is used for the Data Manipulation purpose. You can even add some criteria to it to get a more specific result with the proper syntax.
Syntax: select(FrameName, all_of(Desired Sequence))
library(dplyr) # Inserting Package
# Creating Sample DataFrame (DF)
zap <- data.frame(A = c(101, 202, 303),
B = c(404, 505, 606),
C = c(707, 808, 909))
do <- c("C", "A", "B") # The Desired Order
one <- select(zap, all_of(do)) # Reordering Table
print(zap)
Steps Of The Program:
At first, we will insert the DPYLR Package into the program for use in its inbuilt library function.
Now, one table will be created where we will provide some value.
Here, we will create another variable that will store the Desired Sequence of the new table.
It is time to use the above-mentioned syntax. Using that, we will make the changes.
Now, we will print the new table with its changes.
Output:
The above example clearly shows that the new table has the right sequence that has been provided in the Desired Sequence section. So, the execution of the code was successful as it gave the right outcome which was expected.
How To Rearrange Columns In R Alphabetically?
As we have ended the core concept of the very article, we want to discuss a few more important questions related to Column change in the R Language. Here, we are going to rearrange or alphabetically relocate the column location.
For that purpose, the following syntax will be used. With this simple syntax, the column numbers will get rearranged in ascending alphabetic order.
Syntax: order(names(FrameName))
# Creating Of A Sample DataFrame (DF)
zap <- data.frame(B = c(100, 200, 300),
C = c(400, 500, 600),
A = c(700, 800, 900))
zap <- zap[, order(names(zap))] # Reordering Table
print(zap)
Steps Of The Program:
Here, the table will be created with some values. Just the table name will not be in the alphabetic order as we going to achieve this with code.
Now, the above syntax will be used to change the format in that same table.
Now, the table will be printed on the program to verify the developed code.
Output:
The above example shows that the table columns are now placed in alphabetic order. Earlier, the columns are present in random order. Now, they all relocate their location with the help of the syntax that ends our job within a few minutes.
What Is The Process Of R Reorder Columns Based On List?
The Table in the R is based on the list format only. That means when you are going to write the table on the program, it will come as the list in the compiler. To reorder columns in the list of the table, the Desired Sequence process, we have to use again.
# Creating Of A Sample DataFrame (DF)
zap <- data.frame(C = c(101, 202, 303),
A = c(404, 505, 606),
B = c(707, 808, 909))
do <- c("A", "C", "B") # Desired Order
zap <- zap[, do] # Reordering Table
print(zap)
Steps Of The Program:
The Table will be created along with some values to work on it.
Then, the Desried Sequences will be drafted on the program using the Column Names.
Now, we will implement the changes in the Table using the Variable DO.
At last, the new changed table will be printed on the screen.
Output:
The above example is proof that the list structure of the table can also be altered using the Desired Sequence process. The new table has the C Column in the middle & before the B Column. This is the same thing that we want to get as a result.
Practical Examples and Applications Of Column Reordering In R:
As we are going down to our article page a few more important things we would to highlight. One of the important points is Practical Examples & files of application of Columns and Rows Rearrangement in R process.
You will not find the process to relocate Columns & Rows using the R Programming Language in any beginner-level problem. It is used to solve some advanced-level problems from different fields. The field of utilization is the following.
Data Processing: Column Reodering is highly done in the Data Processing theory. In this case, a RAW Dataset will be used. From that dataset, the required values are extracted. Based upon the need some columns are swapped using the concept.
Data Visualization: Data Visualization is the next step of the Data Processing. Without Data Visualization, important steps can’t be taken to that dataset. To clear the concept of Data Visualization, the Column Reshuffle should be at any time.
Data Transformation: Data Transformation is the policy where a single dataset is being altered to serve for any other goal. That means, that for transforming values from one section to another, the Colum Swapping should be done.
Multiplying matrices in Java is also a fundamental operation in linear algebra, and it finds applications in various fields like computer graphics, data analysis, and scientific computing.
Conclusion:
As we saw, it is very important to understand the working process of “Reordering Columns in R”.
With this idea, we can alter the format of any table created with the R Programming Language. It’s important to note that the concept of tables in R programming differs from MySQL tables. It’s also recommended to establish a strong understanding of the R Programming Language.
Without a solid foundation, the concepts discussed in the article may seem pointless and ultimately ineffective. Without a grasp of the basics, it’s difficult to apply the knowledge independently. So, it’s crucial to master the fundamentals of R Programming.
Takeaways:
Reordering can only be possible if there is a Table is created.
Reorder means swapping Column Locations in the table to get certain data at the required location.
The Process is like working on the Database Management System tables using SQL.
The Reoder of Column can only be done using R Programming language.
There are many ways present to Reoder Column in R programming language, few notables are DPLYR Package, using Name, Indices, etc.
In R programming language, table column values can be shuffled alphabetically.
The Reordering Method is used from Data Analysis to Data Transfering all major working fields.
