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Data-Centric Statistical Inference Using R and Tidyverse

The Pipe Operator

Explore how to simplify data transformation in R by using the pipe operator %>% from the dplyr package. This lesson helps you write more readable and efficient code by chaining multiple data wrangling functions into a single sequential process, enhancing your data analysis workflow.

We'll cover the following...

Needed packages

Let’s load all the packages needed.

R
library(dplyr) 
library(ggplot2) 
library(nycflights13)

Before we start data wrangling, let’s first introduce a tool that gets loaded with the dplyr package—the pipe operator %>%. The pipe operator allows us to combine multiple operations in R into a single sequential chain of actions. Let’s start with a hypothetical example. Say we’d like to perform a hypothetical sequence of operations on a hypothetical data frame x using hypothetical functions f(), g(), and h():

  1. Take x ...