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R for SEO
  • Using R for SEO, What to expect?
  • Getting started
  • What is R? What is SEO?
  • About this Book
  • Crawl and extract data
    • What's crawling and why is it useful?
    • Download and check XML sitemaps using R'
    • Crawling with rvest
    • Website Crawling and SEO extraction with Rcrawler
    • Perform automatic browser tests with RSelenium
  • Grabbing data from APIs
    • Grab Google Suggest Search Queries using R'
    • Grab Google Analytics Data x
    • Grab keywords search volume from DataForSeo API using R'
    • Grab Google Rankings from VALUE SERP API using R'
    • Classify SEO Keywords using GPT-3 & R'
    • 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 using gmail API
    • 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 Data visualisation 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
    • SEO & R People x
    • Execute R code online
    • useful SEO XPath's & CSS selectors X
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  1. Data Viz

Use Esquisse to create plots quickly

PreviousWhy Data visualisation is important? xNextExplore data with rPivotTable

Last updated 3 years ago

Was this helpful?

ggplots is great package but it can be a bit overwhelming to deal with. So many options and functions. Lucky for us, thanks to Fanny Meyer & Victor Perrier, there is a shortcut, the . It basically helps explore your data quickly and build a ggplot.

Let me take an example As always installing and loading

install.packages("esquisse")
library("esquisse")

After that, only one line of code to make the magic happens

esquisser()

you pick your dataset, the field you want to import and it's now possible to choose what metrics to display on each axis by drag & dropping them into each selector

Pick the plot style

you can also customise the plot titles and legends

you can pick the colors and plot style

Filter the values

Last and foremost, it gives you the code to generate this plot + some extra export option.

Esquisse is not capable of doing every available ggplots but for a simple graph, it's a great way to speed up the processs.

esquisse package
esquisse wiward