freelance javascripter
// (use .tokenize() for a minimal initial analysis)
doc=nlp.tokenize(`time for our weekly silluette drawing`);
doc.json()[0].terms
{
let d = doc.clone()
d.compute('wordCount')
d.compute('tagRank')
d.compute('offset')
return d.json()[0].terms
}
{
let d=nlp('weekly silluette drawing')
//add the reverse for each term
d.docs[0].forEach(term=> {
// reverse it
term.backwards = term.normal.split("").reverse().join("")
})
return d.json()[0].terms
}
{
// create a plugin for our .compute() method
nlp.plugin({
compute:{
// our new compute method
backward:(d)=>{
d.docs.forEach(terms=>{
terms.forEach(t=>{
t.backward = t.normal.split("").reverse().join("") //reverse the string
})
})
}
}
})
// okay, now it has a new compute method
let doc = nlp('patio furniture')
doc.compute('backward')
return doc.json()[0].terms.map(t=>t.backward)
}
nlp.version
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
