RStudio is an open source user interface for R, and it also provides access to some packages not available in the basic R environment. To learn more about R, visit the R Project for Statistical Computing. For additional information about working with different data formats in R, see R Data Import/Export. XLSX), files from a variety of statistical packages (including SAS, SPSS, and Stata), and more.
The R environment provides an integrated suite of software facilities for data manipulation, calculation and graphical display. R can import and export data in a variety of formats, both open source and proprietary, including plain text and comma-separated values (CSV), Excel spreadsheets (.XLS and. The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.R is a programming language and environment for statistical computing and graphics. We help you develop a skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. Rather than covering every R skill you might need, you’ll build a strong foundation to prepare you for the more in-depth courses later in the series, where we cover concepts like probability, inference, regression, and machine learning. You’ll learn how to apply general programming features like “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data.
We’ll cover R's functions and data types, then tackle how to operate on vectors and when to use advanced functions like sorting. You will learn the R skills needed to answer essential questions about differences in crime across the different states.
You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. The first in our Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming.
0 kommentar(er)
