R lets you slice your data sets in various ways, depending on the data type. To select just certain columns from a data frame, you can either refer to the columns by name or by their location (i.e ...

The R programming language is an important tool for development in the numeric analysis and machine learning spaces. With machines becoming more important as data generators, the popularity of the ...

Following is what you need for this book: Hands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data ...

Thanks to the large volumes of data Uber collects and the fantastic team that handles Uber Data Analysis using Machine Learning tools and frameworks. If you’re curious to learn more about how data ...

In today's data-driven world, statistical analysis plays a critical role in uncovering insights, validating hypotheses, and driving decision-making across industries. R, a powerful programming ...

If the data is unstacked (or “pivoted” or converted to “wide data”), we get a Salary column for each value of Gender: R and the tidyverse include tools for reshaping data. The spread function is ...

Book Abstract: R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for ...

As an example of competing risk analysis in R, we analyze data from 35 patients with acute leukaemia who underwent HSCT. We estimate the cumulative risk of relapse and TRM.