Of the many skills associated with data science, the knowledge and application of various programming languages to the creation of projects and products is key. Data Scientists often benefit from exploring multiple programming languages in order to determine which ones work best for them. In choosing a programming language to learn, it is important to identify the language(s) that are most common within the field or industry that you are interested in. For example, while languages like Java are more common when pursuing a career in web and mobile application development, SQL is more common for those interested in cybersecurity and database design.
R has become a go-to language for Data Scientists who want to manage a project from start to finish. This is because programming with R makes it easier to create data pipelines, engage in complex statistical analyses, and organize messy datasets. In addition, the community and resources around R have made the language more user-friendly than some others. Whether you are new to data science or further developing your career, R is one of the best programming languages to learn.
What is R?
R is a programming language created for the analysis of data, making it well known for its uses within the realm of statistical analysis and other forms of numerical processing. One of the most popular uses of statistical analysis in data science is running a regression, and languages like R are commonly employed when this type of numerical processing is required. R is also used to create graphics and data visualizations, and many users work with the RStudio products to develop and share key insights from their data collections. Serving as an integrated development environment (IDE), RStudio gives Data Scientists the tools that they need to perform data analyses and to develop software.
While most data science tools are known for their capabilities when it comes to data analysis, visualization, and product development, R is unique in its community and resources. The creation and development of the R programming language has also led to the construction of a community of users who are committed to educating other users on how to use R. Through libraries and forums, as well as events and clubs like Tidy Tuesday, community members across the globe work together to learn R through collaborative data science projects, portfolios, and shareable stores of data. This makes R a great language for beginner Data Scientists who may require more practice and hands-on instruction to develop their skills in the language.
How to Use R for Data Science
Similar to other programming languages R is used within data science to take a collection of data from storage to analysis and visualization. Main uses of R for data science include statistical analysis, the organization and cleaning of data, and the development of data pipelines. It’s also useful for Data Scientists who work in software engineering and development.
Data Analysis and Cleaning
Because R is geared towards computation and numerical analysis, it is simple to get started using this programming language with mathematical equations and statistical formulas, and many R courses start with these skills. Especially for Data Scientists working on more scientific research or business and finance, R acts as an intuitive programming language for data analysis. You can easily return descriptive statistics for a dataset, such as the average of a dataset or the mean values. Another introductory skill when working with R is learning how to use the language for data organization and cleaning, like identifying missing values in a dataset.
Data Pipelines and Packages
Another similarity between using R and other programming languages is the creation of data pipelines and the availability of data science packages. Data pipelines act as a systematized process or series of actions that assist in the migration of data from one place to another. Through filtering and sorting through a dataset, R makes it easier to build data pipelines that simplify working with large and complex datasets. In addition to data pipelines, R is also known for its data packages. The Tidyverse contains the most popular data science packages and offers resources to teach Data Scientists how to work with R and this particular package.
Data Engineering and Research
The R programming language has also become a popular skill for Data Scientists who are interested in engineering and software development. For most students and professionals interested in data engineering, there is an expectation that you should have more advanced knowledge of multiple programming languages. R is among the most useful programming languages to learn, along with others like Python and Java. Much of the popularity of R is seen within more traditional research settings, and any Data Scientist that is invested in pursuing a career in the Science, Technology, Engineering, and Mathematics (STEM) will find the knowledge of R useful. Its capabilities with big data analysis and working complex datasets make it especially valuable for the research and development of products as well as solving societal problems in academic or governmental settings, like policy analysis or public health.
Need to learn more about programming in R?
Whether you are interested in learning R for statistical analysis, data organization, or any number of other uses, this programming language offers versatility at all stages of the data science life cycle. Noble Desktop has a Data Analytics with R Bootcamp. In this five-day immersive experience, you’ll learn coding skills and make contributions to your portfolio of data science projects.
R is a perfect complement to other programming languages, such as Python and SQL. Data science students and professionals who want to learn more about programming can take one of Noble Desktop’s many data science classes. The Data Science Certificate includes an overview of both Python and SQL to teach the fundamentals of pursuing a career as a Data Scientist. Whether you are interested in learning more about programming with R or about programming in general, there is a course or certificate program to suit your needs.