Sorting in R: A Comprehensive Guide

If things were unsorted, life would be a mess. Without sorting, we all would go several years looking for a specific telephone number in a directory or searching a particular record from vast amounts of databases. 

In this guide, we walk you through the process of sorting data in R. We cover all you need to know about R programming, how to sort in R, and specifically, how to sort a vector, row, column, and data array.

But before you plunge into R sorting,

What is R, and why is it relevant?

R is a programming language widely used by researchers and statisticians to deploy statistical computing and graphics. The language contains tools that allow you to clean, analyze, and graph data. 

The programming language R is free to use, hence its vast popularity among programmers. Although it’s free, it still relies on code to get the job done rather than the simplicity of buttons and drop-down menus. Regardless, R’s benefits outweigh its time and effort.

Is R still relevant?

The most fundamental relevance of R is open-source, which allows it to be used by everyone. Aside from what this suggests in accessibility, it also means R:

  • fixes bugs quickly, thanks to the community.
  • updates programming trends and training methods.
  • uses the newest statistical tools for BI
  • provides help and support through users

Anyone can write codes using R and have others take a look at them. Anyone can submit their codes and update the growing library. Programmers use R to offer codes as packages. While some packages can be broader, others contain simplified statistical analysis.

But the question remains…

What is R used for?

R is used for everything — from descriptive analysis, regression equations to hierarchical linear modeling. Rather than spend a fortune on SPSS, SAS, and STATA to get all these done, you can simply engage the all-rounder R.  

R’s features ensure you no longer need MPlus for structural equation models or Excel for merging data sets, cleaning them, and identifying rows and columns. Also, R  makes colored pencils obsolete in creating interactive plots and 3D graphics. 

Microsoft Word has long become antiquated since R could produce APA formatted tables with significance stars and horizontal lines. R can perform all sorts of statistics from Bayesian to frequentist. R can make an elephant wink, write reproducible words, and put the world in order (no pun intended).

Python vs. R: which is more preferred?

Folks in Data Science and Business Intelligence are familiar with the R vs. Python debate. Although both languages shape the future of humanity, they share weaknesses and strengths. Some of the reasons data analysts prefer R over Python include:

  • Approach: By nature, R is more suited to statistical analysis than Python. Although both languages boast online communities, Python leans more towards data analysis. Whereas an R useR would use the program to analyze customer behaviors, Python developers would deploy the program to build face recognition software.
  • Data Collection: R allows data analysts to import data from text files, CSV, and Excel and turn them into R data frames. UseRs can also convert Minitab’s files and SPSS formats into readable R formats for statistical analysis. On the other hand, Python supports all data formats but only when used for web development and building datasets.
  • Visualization: R is designed to achieve data visualization by supporting basic and advanced graphics. Users can create advanced visualization through ggplot2 and scatter plots. Python, however, lacks advanced visualization. Even with that, you can use the Matplotlib library to plot graphs and charts. 
  • Data Exploration: Data exploration in R is designed for statistical analysis as useRs can explore various tools for probability distributions and statistical tests. Python only analyzes data with Pandas for Deep Learning purposes.

How do I sort in R?

The best part of sorting is how it provides answers to everyday questions through a league table (also known as an R summary table). It is a table that groups elements by ascending and descending them.

The essence of sorting in R is not usually glaring. The benefits are subtle, but many of us would not have made it this far in life without sorted data. You can sort data in R through the following ways.

How do I sort a data frame in Base R?

Sorting data frames in base R is the same as sorting by using the order() function. By default, sorting is generated in ascending order which you can alter by adding a minus sign to suggest the descending order of the data frame.

How do I sort in R Dplyr?

Dplyr is only recently introduced as part of the R package. The package allows scientists to manipulate data arrays in R as well as the database table. Although the Dplyr syntax in R is more extended than in DataTable, the workings through pipe operators can help change in data frames:

  • the name of columns
  • values of columns
  • inclusion of columns and
  • order of columns

How can I sort in a DataTable?

DataTable is the most fundamental block in R. It’s simply a combination of rows and columns ready to take on data objects. DataTables are an integral part of SystemData and can be used independently or as part of a dataset. 

With DataTables, you can alter data frames and decide at the initial initiation stage if you want the parameter to display the data array in ascending or descending order.

How do I sort rows in R? 

Often, you may be interested in sorting rows only in R language. Your rows are on the horizontal lines, and you may want to either ascend them or descend. There are three ways to sort rows in R programming:

  • Sort rows by adding a minus sign to the variables. This descends the variables in the R summary table.
  • Sort rows in custom ways by using data.table function or a slice() function.
  • You can also use factor() to reorder variables in R to your desired arrangement.

How do I sort columns in R

You can sort columns in R programming by using order() on the names() of variables and use that order() to subset columns. Alternatively, you can use the select() option in Dplyr to reorder the columns of your data frames in R.

If you want to arrange columns alphabetically, you can use the select() and order() functions alongside the pipe operator. In some cases, you can do that with the order() function. However, if this doesn’t work, try the former function.

How do I sort vectors in R?

Learn how to sort a vector in R by using the sort function and passing the vector as an argument to the function. Once the argument is fulfilled, the sort function returns the vector in the default order, which is the ascending order.

However, if you want to alter the order to decreasing order, you should use the rev() function on the result returned by the sort function. That way, your vectors are reversed by the rev() function in descending order.

What is the difference between sort, rank, and order in R?

Sort in R is done in either ascending or descending orders. However, by default, sorting is in ascending order. 

Rank in R shows the values of data points present in the vectors, where the lowest rank value is 1. 

Order positions the indices of vectors in the sorted order, which is by default the ascending order.


Programming in R has versatile use in BI, especially for plotting charts, graphs, and tables. It’s more profound than Python in statistical analysis. You can sort alphabetically in R through rows, columns, vectors, and data frames. Each aspect can be customized to suit the desired statistical results.

To be grounded in R sorting, we suggest you forge your learning path. Join the SDS Club, a large community of Data Science enthusiasts, expert coaches, and thriving developers.

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