Using dplyr pipelines to manipulate data frames

Another popular package is dplyr, which invents a grammar of data manipulation. Instead of using the subset function ([]), dplyr defines a set of basic erb functions as the building blocks of data operations and imports a pipeline operator to chain these functions to perform complex multistep tasks.

Run the following code to install dplyr from CRAN if you don't have it yet:

install.packages("dplyr") 

First, we will reload the product tables again to reset all data to their original forms:

library(readr) 
product_info <- read_csv("data/product-info.csv") 
product_stats <- read_csv("data/product-stats.csv") 
product_tests <- read_csv("data/product-tests.csv") 
toy_tests <- read_csv("data/product-toy-tests.csv") 

Then, we will load the dplyr package:

library(dplyr) 
##  
## Attaching package: 'dplyr' 
## The following objects are masked from 'package:data.table': 
##  
##     between...