RStudio is your one-stop shop for programming in R, reading R scripts and data, looking at help manuals, interactively running through tutorials and notebooks, and even making presentations like this one!
RStudio is for joining various components in R. But this just scratches the surface of RStudio’s features… RStudio is a desktop (or server) application that eliminates the need for a CLI (as it comes packaged in RStudio itself) and includes a notebook panel for writing and running scripts. An IDE ( integrated development environment) is a program designed to facilitate programming in a particular language. In order to make writing R easier for statisticians, a group of statisticians based in Boston developed RStudio, an IDE for R programming. However, its basic use is command-line only. Especially within the context of RStudio, R (in conjuction with the ggplot2 package) can be used to make sophisticated displays of data, useful in both exploratory data analysis ( EDA) and presentation of research findings.īy itself, R is a powerful programming language. In addition to running statistical computations, R is very useful for graphing data as well. R makes data science incredibly quick to write and simple to understand.
For example, the ggplot2 package is a package for R that allows you to create high-quality graphs and visualizations.)īecause R was made specifically with statistics in mind, it is a premier language for statistical computing, data visualization, and machine learning. ( Note: A package (very similar to a library or module) is an addition to a base program that gives it more commands and functionality. Of course, if you have already installed Anaconda in py0 of the SAAS Crash Course curriculum, you have these packages installed already. To do such tasks in Python, packages such as pandas and scikit-learn must be installed first. For example, manipulating data and creating and evaluating linear models are readily available in R by default via the ame() and lm() commands respectively. Because of this, many statistical tasks are very easily provided by even the base R libraries. Rather, R was developed for the use of data scientists and statisticians specifically. In contrast to Python, R is not a general programming language. An ordered list of commands comprises a script, which can be run automatically by the R program as well.) (Note: A command is generally used to describe an interactive style of programming, where you enter commands line-by-line in a console. R is the name of both the language for computational tasks as well as the runtime environment that actually reads commands and scripts written in the R language to execute tasks. Print("Hello SAAS!") # Printing in Python # Hello SAAS! print("Hello SAAS!") # Printing in R # "Hello SAAS!" Its syntax (aka specific language structure) is a little different than Python’s, but a lot of it is identical! For example, in both languages, printing a string to the console is done via the same command: Just like Python, R is a programming language.
#Rstudio downloads code#
The first thing to notice about R is that it’s open-source - that is, R is free to use and anyone can see how it was made! The free and open nature of R led to the formation of the R community, a constantly-expanding network of individuals who contribute ideas and code to R and all of its packages, free-of-charge. This tutorial is the prerequisite for r1, SAAS’s crash course on R for data science and statistics.īefore we begin installing R, what is R anyway?
#Rstudio downloads how to#
In this mini-tutorial, you will learn how to install R (a statistical programming language) and RStudio (an integrated development environment (IDE) for R programming). Introduction to R Part 0: Installing R and RStudio By Arun Ramamurthy
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