Top Ten Most Wanted R Packages

Which ones do you load daily?

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There are several popular R packages for data science that are widely used by the community. As you might expect, certain R packages are more popular and prevalent than others. They are usually more functional and versatile than the average package. This means users can efficiently and effectively perform their tasks. These packages tend to have an intuitive and consistent syntax. They are actively developed and maintained by the community and thus have a good reputation. Regular updates, bug fixes, and new features enhance the usability and reliability of the packages. Compatibility with the wider R ecosystem, such as interoperability with other packages or seamless integration with popular IDEs like RStudio, can make a package more attractive to users.

Some of the most popular packages include:

1. dplyr: A package for data manipulation and transformation, providing a grammar of data manipulation. Key parts include the heavy use of ‘pipes’ %>% to move data from one function to the next as well as straight forward verbs for functions like filter and arrange. I still have a hard time convincing new coders that this is more useful than say, manipulating data in Excel first. However, once a person is sold on the idea of coding as getting exactly what you want out of a program that person takes to…