Published
Edited
Mar 30, 2019
//API: make the inquiry and will return information in a given structure
//https://developer.twitter.com/en/docs/tweets/search/overview/standard.html
resolveAfter2Seconds = function(x) {
return new Promise(resolve => {
setTimeout(() => {
resolve(x)
//resolve if the API successfully returned tweets
//or it might be rejection
}, 2000)
})
}
f1 = async function(number) {
//async: executing at different times, have a delay, not syncrocize, don't execute anything else before we successfully executed it.
var x = await resolveAfter2Seconds(number);
//waiting 2 seconds
console.log(x)
return x
}
f1(5)
vegalite = require("@observablehq/vega-lite@0.1")
z = require('https://bundle.run/zebras@0.0.11')
// Load a file locally
viewof text = html`<input type=file * ">`
tweetsStrings = Files.text(text)
tweetsDF = Object.values(JSON.parse(tweetsStrings))
count = {
let countArray = []
let groupedLocations = z.groupBy(x => x.location, tweetsDF)
for (const key of Object.keys(groupedLocations)) {
countArray.push({location: key, count: groupedLocations[key].length})
}
return countArray
}
countSorted = z.sortByCol('count', 'des', count)
vegalite({
data: {values: countSorted.slice(0,40)},
mark: "bar",
encoding: {
x: {field: "location", type: "nominal", sort:'*'},
y: {field: "count", type: "quantitative"},
color: {"field": "location", "type": "nominal"}
}
})
notNull = z.filter(r => r.lat != null, tweetsDF)
vegalite({
data: {values: notNull},
mark: "point",
encoding: {
x: {field: "lon", type: "quantitative"},
y: {field: "lat", type: "quantitative"}
}
})
// Loop through all the locations, and see if they are similar to Boston, then create a new column
newTweets = {
let newLocations = []
let locations = z.getCol("location", tweetsDF)
for (let id in locations) {
if (locations[id].toLowerCase().includes('boston')){
newLocations.push('Boston, MA')
} else {
newLocations.push(locations[id])
}
}
return z.addCol("cleanLocations", newLocations, tweetsDF)
}
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