Data wrangling with R and tidyverse has many advantages, such as making your code more readable, efficient, flexible and reproducible. By using the same verbs and syntax for different tasks, you ...

It helps in writing more concise and readable code. tibble: Provides a modern re-imagining of the data.frame, keeping what time has proven to be effective, and throwing out what it has not. Tibbles ...

# Data Frames Moving on from vectors, the next most important data structure in R is the data frame. Think of a data frame as similar to a matrix, but (ideally) **each column is a vector of a single ...

This online data science specialization is designed for anyone interested in learning how to program in R. You will learn the basics of R, including imputing data, performing basic analysis, graphing, ...

R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh ...

Book Abstract: Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making ...