I love to build dataviz for insight discovery. I also love to put technology to the service of humanity
Evolución Coronavirus en ColombiaCoronavirus Colombia por ciudades (WIP)Coronavirus in AsiaCoronavirus LatinoaméricaCoronavirus in AfricaCoronavirus ColombiaCalifornia COVID-19 disparities bullet graphCalifornia COVID-19 disparities stacked barsUS Excess deaths Ridgeline plot vega-lite-apiMultimorbidity patterns for COVID-19 deaths in ColombiaExcess Deaths Associated with COVID-19 in the USCOVID-19 by US county19 Confirmed CasesTiempo de procesamiento Pruebas Coronavirus ColombiaMapa Evolución Coronavirus Colombia
Pruebas Coronavirus Colombia
pruebas_por_dia2 = vl
.markArea({ tooltip: true, point: true })
.transform(
vl.fold(["pruebas_por_dia_positivas", "pruebas_por_dia_negativas"])
)
.encode(
vl.x().fieldT("fecha"),
vl
.y()
.fieldQ("value")
.stack(true),
vl
.color()
.fieldN("key")
.scale({ range: ["#a6cee3", "#fb9a99", "gray"] })
)
.data(data)
.width(width * .7)
.title("Número de pruebas covid procesadas por día")
.render()
pruebas_por_dia = vl
.markLine({ tooltip: true })
.encode(
vl.x().fieldT("fecha"),
vl
.y()
.fieldQ(vl.repeat("layer"))
.stack(true),
vl
.color()
.datum(vl.repeat("layer"))
.scale({ range: ["firebrick", "steelblue", "gray"] })
)
.data(data)
.width(width * .7)
.title("Número de pruebas covid procesadas por día")
.repeat({
layer: [
"pruebas_por_dia_positivas",
"pruebas_por_dia_negativas",
"pruebas_por_dia"
]
})
.render()
data = {
const gen = loadSocrata("https://www.datos.gov.co/resource/8835-5baf.csv", {
progressive: false
});
const data = (await gen.next()).value;
return data.map(d3.autoType).map((d, i) => {
// if (i === 0) {return d;}
d.pruebas_por_dia =
i === 0 || !data[i - 1].acumuladas
? 0
: d.acumuladas - data[i - 1].acumuladas;
d.pruebas_por_dia_positivas =
i === 0 ||
!data[i - 1].positivas_acumuladas ||
!data[i].positivas_acumuladas
? 0
: d.positivas_acumuladas - data[i - 1].positivas_acumuladas;
d.pruebas_por_dia_negativas =
i === 0 ||
!data[i - 1].negativas_acumuladas ||
!data[i].positivas_acumuladas
? 0
: d.negativas_acumuladas - data[i - 1].negativas_acumuladas;
return d;
});
}
d3 = require("d3-dsv@2")
import {navio} from "@john-guerra/navio"
import { vl } from "@john-guerra/vega-lite-api"
import {loadSocrata} from "@john-guerra/socrata-load-multiples-pages"
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