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R for SEO
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R for SEO - The Cookbook
What is this?
Using R for SEO, What to expect?
Getting started
Crawl and extract data
What's crawling and why is it useful?
Download and check XML sitemaps
Crawling with rvest
Website Crawling and SEO extraction with Rcrawler
Perform automatic browser tests with RSelenium
Grabbing data from APIs
Grab Google Analytics Data x
Grab 'DataForSeo' API data x
Grab Google Search Console Data x
Grab 'ahrefs' API data x
Grab Google Custom search API Data x
Send requests to the Google Indexing API using googleAuthR
other APIs x
Export and read Data
Send and read SEO data to Excel/CSV
Send your data by email x
Send and read SEO data to Google Sheet x
data wrangling & analysis
Join Crawl data with Google Analytics Data
Count words, n-grams, shingles x
Hunt down keyword cannibalization
Duplicate content analysis x
Compute ‘Internal Page Rank’
SEO traffic Forecast x
URLs categorization
Track SEO active pages percentage over time x
Data Viz
Why this is important? x
Use Esquisse to create plots quickly
Explore data with rPivotTable
Resources
Launch an R script using github actions
Types / Class & packages x
Datasets x
SEO Tools x
SEO & R People x
Execute R code online
useful SEO XPath's & CSS selectors X
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URLs categorization
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# default category
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INDEX$UrlCat <- "Not match"
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​
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# create category name
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category_name <- c("Category", "Dates", "Page Auteur", "Page d'accueil")
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​
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# create category regex, must be the same length
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category_regex <- c("category", "2019", "author","example\.com.\/quot;)
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​
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# categorize
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for(i in 1:length(category_name)){
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cat(".")
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INDEX$UrlCat <- ifelse(grepl(category_regex[i], INDEX$Url, ignore.case = T),
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category_name[i], INDEX$UrlCat)
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}
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​
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# debug
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View(INDEX)
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