Introduction 

If you are not a data scientist it might be the first time that you are hearing this word. Tidy verse makes data science fast, easier and more fun. Tidyverse is an opinionated collection of R packages which are designed for data science. Read on further to understand fully what Tidyverse and Tidyverse R package are.

  1. Definition of Tidyverse
  2. What packages does Tidyverse include?

1) Definition of Tidyverse

A collection of open-source R packages which are introduced by Hadley Wickham and his team. Tidyverse is an R package that is helpful in the presentation and transformation of data. The concept of Tidyverse is being expanded constantly i.e. it is open-source. Tidyverse is a one-stop spot for data analysis and data science.

It includes many other packages which can be installed. The packages which are present under Tidyverse umbrella help us in interacting and performing with the data. There are a whole lot of things which you can do with your data – for example, subsetting, transforming, and visualising. The Tidyverse is a clear system of packages for exploration, visualisation and transformation of data all of which share common design philosophy. 

2) What packages does Tidyverse include?

The packages in Tidyverse include:

  • Dplyr: This is the most useful package in R for data manipulation and the greatest advantage of this package is that you can use the pipe function “%>%” to combine different functions in R. This is known as the Tidyverse R package The complete list of functions dplyr offers are as follows:
  • Select (): Select columns from the given data sets
  • Filter (): filter out certain rows which meet your criteria
  • Group_by ()
  • Summarise  ()
  • Arrange ()
  • Join()
  • Mutate ()
  • Tidyr: This is a package complementing dplyr perfectly.it boosts the power of dplyr for pre-processing and data manipulation. The functions offered by Tidyr are as follows:
  • Gather ()
  • Spread ()
  • Separate ()
  • Unite ()
  • Stringr: This package provides a cohesive set of functions which is specially designed to make working with strings easy.
  • Forcat: this package provides numerous useful tools to solve common problems. R uses factors to operate categorical values, variables which have a known and fixed set of values which are possible.
  • Readrr: Readr provides a friendly and fast way to read rectangular data. It is designed flexibly to resolve the various types of data found in the wild. 
  • Purr: Purr improves R’s functional programming toolkit and provides a consistent and complete set of tools for working with vectors and functions. 
  • Tibble: Tibble is an up-to-date re-imagining of the data framework. This is a data frame that is lazy and surly. They complain more and do less causing more problems to be looked into earlier. This is similar to the concept of a leading indicator. 

The Tidyverse R package also comprises many other special packages which possess a more specialized usage. These packages include Wrangle, Import, Program, and Model.  

Conclusion 

Tidyverse packages possess several advantages such as consistency, coverage, education, parsimony, productivity and critical mass. Tidyverse is subject to some limitations as well which are largely beyond the designer’s control. Tidyverse has its main application in data science and is essentially designed to make work easy, fun and efficient. After reading this article we sincerely hope that you have understood what Tidyverse is and what it purports to do. 

If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional. 

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