covid = d3.csvParse(await FileAttachment("VDH-COVID-19-PublicUseDataset-Cases.csv").text(), function(d) {
return {
date: d3.timeParse("%x")(d["Report Date"]),
fips: d.FIPS,
locality: d.Locality,
district: d["VDH Health District"],
cases: +d["Total Cases"],
hospitalizations: +d.Hospitalizations,
deaths: +d.Deaths
};
});
covid.sort(function (a, b) {
return a.date - b.date;
});
covid.sort((a, b) => a.date - b.date)
printTable(covid.slice(0,7))
printTable(covid.slice(-7))
hr_districts = new Set(["Western Tidewater", "Chesapeake", "Virginia Beach", "Norfolk", "Portsmouth", "Hampton", "Peninsula"])
hr_covid = covid.filter(d => hr_districts.has(d.district))
printTable(hr_covid.slice(0,10))
printTable(hr_covid.slice(-10))
last_date = covid[covid.length-1].date
covid_totals = covid.filter(d => d.date >= last_date)
printTable(covid_totals.slice(0,10))
hr_totals = covid_totals.filter(d => hr_districts.has(d.district))
printTable(hr_totals)
viewof scatter = vl.markPoint()
.data(covid_totals)
.encode(
vl.x().fieldQ("cases"),
vl.y().fieldQ("deaths"),
vl.color().fieldN("locality"),
vl.tooltip(["locality","cases","deaths"])
)
.title(
{text:"Total Cases Vs. Deaths per locality"}
)
.render()
scatterplot2 = d3.rollups(covid, v => [d3.sum(v, d => d.cases),d3.sum(v, d => d.hospitalizations)], d => d.date)
md`*This code calculates the total cases and total hospitalizations in VA over time. It gets the total cases and total hopitalizations per each day.*`
scatterplot2_json = scatterplot2.map(obj => { let rObj= {}; rObj["date"] = obj[0]; rObj["totals"] = obj[1]; return rObj;})
viewof scatter2 = vl.markPoint({tooltip: {"content": "data"}})
.data(covid)
.encode(
vl.x().sum("cases"),
vl.y().sum("hospitalizations"),
vl.color().fieldT("date")
)
.title({text:"Total Cases vs. Hospitalizations in VA over time"})
.render()
fields =["cases", "hospitalizations", "deaths"]
viewof line = vl.markLine({tooltip: {"content": "data"}})
.data(covid)
.encode(
vl.x().fieldT("date"),
vl.y().sum(vl.repeat("column"))
)
.width(200).height(200)
.repeat({
column: ["cases", "hospitalizations", "deaths"]
})
.title({text:"Time series of Total Cases, Hospitalizations, and Deaths in VA over time"})
.render()
viewof layeredline = vl.markLine({tooltip: {"content": "data"}})
.data(hr_covid)
.encode(
vl.x().fieldT("date"),
vl.y().sum("cases"),
vl.color().fieldN("district")
)
.title({text:"Time series of Total Cases over time for Hampton Roads Health Districts "})
.render()
viewof facetedLineChart = vl.markLine({tooltip: {"content": "data"}})
.data(hr_covid)
.encode(
vl.column().fieldN("district"),
vl.x().fieldT("date"),
vl.y().sum("cases")
)
.width(100).height(100)
.title({text:"Time series of Total Cases over time for Hampton Roads Health Districts "})
.render()
viewof layeredBar = vl
.data(hr_totals)
.layer(
vl.markBar({tooltip: {"content": "data"}})
.encode(
vl.x().sum("cases"),
vl.y().fieldN("district").sort(vl.sum("cases").order("descending")),
vl.color().fieldN("district"),
)
)
.title({text:"Total Cases for Hampton Roads Health Districts"})
.render()
district_totals = d3.rollups(covid_totals, v => d3.sum(v, d => d.cases), d => d.district)
district_covid_totals = district_totals.map(
function(value){
return { "district": value[0], "total_cases": value[1]}
})
viewof boxplot2 = vl.markBoxplot({tooltip: {"content": "data"}})
.data(district_covid_totals)
.encode(
vl.x().fieldQ("total_cases")
)
.width("600").height("100")
.title({text:"Total Cases per Health District"})
.render()
d3 = require("d3@6")
import { vl } from "@vega/vega-lite-api"
import {printTable} from '@uwdata/data-utilities'
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