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For those that don’t work in education or aren’t aware, there is a measurement for a child’s reading level called a Lexile ® Level.  There are ways in which this level can be retrieved using different reading assessments.  The measurement can be used to match a child’s reading level to books that are the same level.  So the company maintains a database of books that they have assigned levels.  There are other assessments that measure how well a child is reading, but I’m not aware of any systems that assign books as comprehensively.  The library at the school I work at lacked Lexile Levels for their books.  This is unfortunate because of the fact that teachers are not able provide students with books for their respective Lexile Level.  Fortunately though the library had a list of ISBNs for the books.

On the Lexile website there is a way to search for books using ISBN numbers to retrieve their Lexile ® Level if the book is available in their database.  Entering every ISBN number available is a task fit for something not human.

rvest to the rescue.

Below is the script to retrieve the Lexile Levels of books if a list of ISBNs is available.  This was an incredible time save provided by some R code and hopefully someone else out there could use it.
 

	library(rvest) library(httr)
	library(htmltools)
	library(dplyr)
	##Prep for things used later
	url<-“https://www.lexile.com/fab/results/?keyword=“
	url2<-“https://lexile.com/book/details/“
	##CSV file with ISBN numbers
	dat1<-read.csv(“~isbns.csv“,header=FALSE)
	##dat1<-data.frame(dat1[203:634,])
	dat<-as.character(dat1[,1])%>%trimws()
	##dat<-dat[41:51]
	blank<-as.character(“NA“)
	blank1<-as.character(“NA“)
	##blank2<-as.character("NA")
	##blank3<-as.character("NA")
	all<-data.frame(“A“,“B“,“C“)
	colnames(all)<-c(“name“,“lexiledat“,“num“)
	all<-data.frame(all[–1,])
	for(i in dat) {
	sites<-paste(url,i,sep=““)
	x <- GET(sites, add_headers(‘user-agent‘ = ‘r‘))
	webpath<-x$url%>%includeHTML%>%read_html()
	##Book Name
	name<-webpath%>%html_nodes(xpath=“///div[2]/div/div[2]/h4/a“)%>%html_text()%>%trimws()
	##Lexile Range
	lexile<-webpath%>%html_nodes(xpath=“///div[2]/div/div[3]/div[1]“)%>%html_text()%>%trimws()%>%as.character()
	##CSS change sometimes
	lexiledat<-ifelse(is.na(lexile[2])==TRUE,lexile,lexile[2])
	test1<-data.frame(lexiledat,NA)
	##Breaks every now and then when adding Author/Pages
	##Author Name
	##author<-webpath%>%html_nodes(xpath=’///div[2]/div/div[2]/span’)%>%html_text()%>%as.character()%>%trimws()
	##author<-sub("by: ","",author)
	##Pages
	##pages<-webpath%>%html_nodes(xpath=’///div[2]/div/div[2]/div/div[1]’)%>%html_text()%>%as.character()%>%trimws()
	##pages<-sub("Pages: ","",pages)
	##Some books not found, this excludes them and replaces with NA values
	df<-if(is.na(test1)) data.frame(blank,blank1) else data.frame(name,lexiledat,stringsAsFactors = FALSE)
	colnames(df)<-c(“name“,“lexiledat“)
	df$num <- i
	all<-bind_rows(all,df)
	}
	master<-rbind(all1,all)

   
Link to code

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