What Is Tidyverse?

Key takeaways

Tidyverse is a suite of R packages that include easy-to-use functions for manipulating data, making it a good choice for beginners.

• Tidyverse packages include ggplot2, dplyr, tidyr, and purr.

• You can use Tidyverse packages to enhance your ability to interact with data and to more easily manipulate, visualize, and organize it.

• You can pursue a career in which you use Tidyverse, such as data analytics, by earning a degree, learning R through online courses, tutorials, or boot camps, and gaining hands-on experience.

Learn about the core components of Tidyverse and how they can help you work more efficiently. If you want to learn more about how you can import, wrangle, visualize, and model data with Tidyverse R packages, enroll in the Tidyverse Skills for Data Science in R Specialization. In as little as two months, you have the opportunity to organize a data science project, build predictive machine learning models, and wrangle and manipulate messy data.

What is Tidyverse?

Tidyverse is a suite of R packages with the same grammar, design philosophy, and data structures. R is a programming language designed to help data professionals visualize, analyze, and manage data sets. Open-source R programming was originally created as a way to support statistics. 

However, beginner coders may find the R language confusing or challenging. To make this process easier, many professionals use the Tidyverse, an alternative to R's built-in functions that includes easy-to-use functions for manipulating data.

What is the Tidyverse package? Core components of Tidyverse

Tidyverse contains several key packages that address different aspects of data manipulation. These include:

ggplot2 for data visualization

Based on The Grammar of Graphics, ggplot2 is a package that helps map variables to specific aesthetics. Using code, you can add different layers to create visualizations within complex graphics. Once you provide the data, ggplot2 takes your stated parameters and outputs your desired graph.

dplyr for data manipulation

dplyr provides a consistent set of verbs that help you overcome common data manipulation challenges. These verbs include:

• Mutate

• Select

• Filter

• Summarize

• Arrange

tidyr data tidying

Tidyr data simplifies analysis and saves time by reducing the need to wrestle with different tools. It makes messy data easier to manipulate. With tidy, every variable gets a column to itself, every observation or object measured gets a row, and every value gets a cell.

purrr for consistent tools

Purrr enhances the usability of Tidyverse by providing a complete and consistent set of various tools for interacting with data. It reduces loops of code, making the entire data set much easier to read. It’s a great tool for beginners since it’s typically difficult to write loop-free code when you’re starting out.

What is Tidyverse used for?

The Tidyverse supports data analysts in their data manipulation activities. It helps streamline programming, graphing, data manipulation, data wrangling, and more. The Tidyverse introduces a simplified and consistent syntax to your code that makes it easier to read and write. In turn, this helps make data science, as a whole, more accessible.

The Tidyverse is also considered to be more than just R packages; it’s a thriving online community of programmers and data analysts. This community works together to support each other, answer questions, and continually find ways to improve the Tidyverse's functions for anyone who might need to use it.

Who uses Tidyverse?

Non-programmers tend to use Tidyverse, as programmers designed the entire R language for first-time or end-user programmers. Data analysts use data to increase profit, reduce turnover, solve problems, and improve business processes. They use their expertise to analyze data for hidden insights that help businesses make better, more informed decisions. Data analysts have skills in different programming languages and use tools, such as the Tidyverse, to get the most out of the large datasets collected by their teams.

Learn more: Essential R Programming Skills

Pros and cons of using Tidyverse

Tidyverse brings a range of advantages and disadvantages worth considering before choosing whether or not you want to use it for your work. Some of these pros and cons include:

Benefits

The Tidyverse allows users to implement consistency across multiple data levels, making the data much easier to read. The packages’ pipeline function also helps to increase readability. You have the ability to load and use the different aspects of the Tidyverse with a single command. Tidyverse has a friendly syntax that makes it easier for a user to work with the R language. For example, since the tools are consistent, once you master one, learning another makes it easier.

Drawbacks

Some drawbacks of the Tidyverse include its computational speed—it may bottleneck. To overcome these potential lags and match the performance of traditional R, you may benefit from having experience in lower-level tools. Plus, it relies on functional programming, so it might be difficult for new users or beginner coders to fully understand how to use Tidyverse correctly.

Should I learn base R or Tidyverse?

The language you choose to learn will likely depend on your needs and how you plan to use it, with many recommending that you have at least some knowledge of both. If your work involves a lot of data manipulation and visualization, the Tidyverse may be a better choice. If, however, software and package development play a large part in daily work, base R can be a better approach.

How to get started in Tidyverse

If you’re interested in working with Tidyverse, the first step is to learn the R language. Many people do so either through traditional education methods or by practicing small tasks independently. Online courses and tutorials are available to walk you through learning the R language's basics. Boot camps also allow learning code without committing to a four-year degree.

If you want to pursue a career that works with Tidyverse, you might want to consider a role as a data analyst. These professionals use Tidyverse and other programming languages to analyze data for insights. Most companies that hire data analysts want you to have a bachelor’s degree in a subject such as computer science, statistics, or mathematics. Depending on your intended industry, you might also need to earn a master’s degree. 

It’s important that you have the ability to demonstrate hands-on experience, which you might gain either from formal education, internships, or work done while in an adjacent role. Once you secure an entry-level role, you might expect to further develop your skills on the job until you’ve gained enough expertise to advance into higher roles.

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