freelance javascripter
{
var doc = nlp("Björk, the singer-songwriter, plays at seven...")
doc.normalize()
return doc.out('text')
}
{
// default params:
return {
// remove hyphens, newlines, and force one space between words
whitespace: true,
// keep only first-word, and 'entity' titlecasing
case: true,
// remove commas, semicolons - but keep sentence-ending punctuation
punctuation: true,
// visually romanize/anglicize 'Björk' into 'Bjork'.
unicode: true,
// turn "isn't" to "is not"
contractions: true,
//remove periods from acronyms, like 'F.B.I.'
acronyms:true,
//---these ones don't run unless you want them to---
//remove words inside brackets (like these)
parentheses: false,
// turn "Google's tax return" to "Google tax return"
possessives: false,
// turn "batmobiles" into "batmobile"
plurals: false,
// turn all verbs into Infinitive form - "I walked" → "I walk"
verbs: false,
//turn 'Vice Admiral John Smith' to 'John Smith'
honorifics: false,
}
}
nlp('so... you like DONUTS? have all the donuts in the WORLD!!!').normalize({nouns:true}).out()
nlp('the so-called group of seven').normalize({numbers:true}).out()
{
//get the wikipedia plaintext with wtf_wikipedia
let text = await wtf.fetch(article).then(doc=>doc.plaintext())
//get all the nouns from the text
let nouns = nlp(text).normalize({plurals:true, parentheses:true, possessives:true, honorifics:true}).nouns()
//sort them by frequency
return JSON.stringify(nouns.out('topk'), null, 2)
}
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.