2d:null 2e:["$","title",null,{"children":"Tweets about Hurricane Irma 2017 | Hoeyun Kwon | Observable"}] 33:[] 31:{"id":"d6cf0cf287468ebd","slug":"tweets-about-hurricane-irma","title":"Tweets about Hurricane Irma 2017","thumbnail":"830c47ca367ef5bde3711c526981b61ddef82a1160fdc421ade43778af0cdfdb","access_level":"public","create_time":"$D2020-05-15T06:52:08.883Z","update_time":"$D2020-05-15T21:45:03.244Z","view_time":null,"first_public_time":"$D2020-05-15T06:52:37.104Z","has_unpublished_edits":null,"fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"1ebfad7f2fd274fb","login":"kwonhy71","name":"Hoeyun Kwon","avatar_url":"https://avatars-next.observableusercontent.com/7af01d2752a31db6c1269ffc579ea9c66ba8a8f34eec28fd114eac6a0d0f4c80","tier":"starter_2024"},"version":1981,"publish_version":1981,"role":null,"authored":false,"authors":[{"type":"individual","id":"35e5c7704442a56a","login":"kwonhy71","name":"Hoeyun Kwon","avatar_url":"https://avatars-next.observableusercontent.com/7af01d2752a31db6c1269ffc579ea9c66ba8a8f34eec28fd114eac6a0d0f4c80","tier":null}],"members":[{"type":"individual","id":"35e5c7704442a56a","login":"kwonhy71","name":"Hoeyun Kwon","avatar_url":"https://avatars-next.observableusercontent.com/7af01d2752a31db6c1269ffc579ea9c66ba8a8f34eec28fd114eac6a0d0f4c80","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Tweets about Hurricane Irma 2017","cells":[{"id":0,"value":"md`# Tweets about Hurricane Irma 2017`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1967,"value":"md`#### Statistics - the number of tweets aggregated by month, weekday, and hour of day`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":400,"value":"viewof year = select({\n title: \"Year\",\n options: [2017],\n value: 2017\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1485,"value":"// Using d3.nest is way quicker than aggregating with vega lite\nembed({\n \"title\": `When tweets were uploaded (${year})`, // doesn't appear to support centering across hconcat\n \"hconcat\": [\n {\"mark\": \"bar\", \"data\": {\"values\": by_month}, \"encoding\": encoding, \"title\": \"By month\"},\n {\"mark\": \"bar\", \"data\": {\"values\": by_dow}, \"encoding\": encoding, \"title\": \"By Weekday\"},\n {\"mark\": \"bar\", \"data\": {\"values\": by_hour}, \"encoding\": encoding, \"title\": \"By hour of day\"},\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1611,"value":"by_month = d3.nest()\n .key(d => d3.timeFormat('%b')(d.datetime))\n .rollup(v => v.length)\n .entries(incidents)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1624,"value":"by_dow = d3.nest()\n .key(d => d3.timeFormat('%a')(d.datetime))\n .rollup(v => v.length)\n .entries(incidents)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1630,"value":"by_hour = d3.nest()\n .key(d => d3.timeFormat('%H')(d.datetime))\n .rollup(v => v.length)\n .entries(incidents)\n .sort((a,b) => d3.ascending(parseInt(a.key), parseInt(b.key)))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1777,"value":"map_styles = ({\n 'stamen': {\n url: 'https://stamen-tiles-{s}.a.ssl.fastly.net/watercolor/{z}/{x}/{y}.png', \n attribution: 'Map tiles by Stamen Design, CC BY 3.0 — Map data © OpenStreetMap'\n },\n 'openStreetMap': {\n url: 'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',\n attribution: '© OpenStreetMap'\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1569,"value":"// Using d3.nest is way quicker than aggregating with vega lite\nencoding = ({\n \"x\": {\n \"field\": \"key\",\n \"type\": \"ordinal\",\n \"title\": \"\",\n \"sort\": {\"field\": \"key\"}\n },\n \"y\": {\n \"field\": \"value\",\n \"type\": \"quantitative\",\n \"title\": \"\"\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1146,"value":"// TODO: find better way to trigger heat_layer\nmutable trigger_heat_layer = 0","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"incidents = {\n const parseDate = d3.timeParse(\"%Y-%m-%dT%H:%M:%S\")\n \n // gist barely accepted each of these due to file size, so separated into separate gists\n const filepaths = {\n '2017': 'https://raw.githubusercontent.com/kwonhy71/data/master/all_tweets.csv',\n }\n \n return d3.csv(filepaths[year],\n {cache: \"force-cache\"}, row => {\n return {id: row.ID_UNIQUE,\n datetime: parseDate(row.DDS_DATE_CREATION),\n long: +row.LOC_LONG,\n lat: +row.LOC_LAT,\n desc_key: row.ACTI_NOM_KEY,\n }\n }).then(data => data.filter(d => d.lat !== 0 && d.long !== 0))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":733,"value":"// A non-standard description for each incident is used but is often repeated, so we created a map and translated into English to reduce filesize and improve readability for English readers.\nall_incident_categories = d3.csv('https://raw.githubusercontent.com/kwonhy71/data/master/keys.csv')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":321,"value":"formatTime = d3.timeFormat(\"%B %d, %Y\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"L = require('leaflet@1.3.4')\n//L = require('leaflet@1.2.0')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":110,"value":"markerClusterCSS = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":63,"value":"leafletCSS = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2,"value":"d3 = require('d3@5')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"import { select, checkbox } from '@jashkenas/inputs'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":703,"value":"embed = require(\"vega-embed@3\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1976,"value":"md`Codes credit: https://observablehq.com/@john-clarke/montreal-311-incidents-in-2016-2018`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 32:"$31:body"