Lic. en Ciencias de la Computación, DC, FCEyN, UBA.
Profesor Asociado en el ITBA.
Public
Edited
Nov 20, 2022
1 fork
Wrangler(data)
data_procesada = aq
.from(data)
.select("season", "fb", "sl", "ct", "cb", "ch", "sf", "kn", "xx")
.fold(["fb", "sl", "ct", "cb", "ch", "sf", "kn", "xx"])
.orderby("season")
.objects()
data_final = data_procesada.map((d) => ({
season: new Date(d.season + "-01-01"),
key: d.key,
value: +d.value * 100
}))
data = d3.csv("https://download.data.world/s/ijpomkwfgk64gz6sb2umqsvdoilbki")
import { IndexChart } from "@d3/index-chart"
chart1 = Plot.line(
data_final,
Plot.normalizeY({ x: "season", y: "value", stroke: "key" })
).plot({ color: { legend: true }, y: { type: "linear", grid: false } })
chart2 = Plot.line(data_final, {
x: "season",
y: "value",
stroke: "key"
}).plot({
color: { legend: true }
})
data_final
chart = IndexChart(data3_final, {
x: (d) => d.season,
y: (d) => d.value,
z: (d) => d.key,
yType: d3.scaleLinear,
yLabel: "↑ % lanzamiento (×)",
width,
height: 400
})
w43Queryresult2 = FileAttachment("2022w43-QueryResult (2).csv").csv()
d3.extent(data_final.map((d) => d.value))
data_final
data3 = d3.csv("https://download.data.world/s/kunkw3hdrkrivf5rphvb4kftglvrw6")
Wrangler(mom_w44)
data3_final = aq
.from(data3)
.fold(["ip", "pitches"])
.objects()
.map((d) => ({
season: new Date(d.season + "-01-01"),
key: d.key,
value: +d.value * 100
}))
d3.schemeTableau10
// d3.scaleOrdinal([[domain, ]range])
//
// Constructs a new ordinal scale with the specified domain and range. If domain is not specified, it defaults to the empty array. If range is not specified, it defaults to the empty array; an ordinal scale always returns undefined until a non-empty range is defined.
d3.scaleOrdinal(["A", "B", "C"], ["red", "green", "blue"])
mom_w44 = d3.csv(
"https://download.data.world/s/mvwshoefvhfiau7blcw5matldtmrvx",
d3.autoType
)
// To use copied code replace "data" with your own variable
mom_w44_stats = aq
.from(mom_w44)
.select("party", "chamber", "raised")
.groupby("party", "chamber")
.rollup({
mean: (d) => op.mean(d["raised"]),
sum: (d) => op.sum(d["raised"]),
count: (d) => op.count()
})
.objects() // Uncomment to return an array of objects
Plot.plot({
facet: {
data: mom_w44_stats,
y: "chamber"
},
marks: [
Plot.barX(mom_w44_stats, {
x: "sum",
y: "party",
fill: "party",
sort: { y: "x", reverse: true }
}),
Plot.ruleX([0])
],
color: {
type: "categorical",
range: ["#4e79a7", "#f28e2c", "#e15759"],
legend: true,
columns: "80px"
},
marginLeft: 120
// marginRight: 200
// height: 200
// width: width
})
membersByPartyChamber = d3.group(
mom_w44,
(d) => d.party,
(d) => d.chamber
)
d3.rollup(
mom_w44,
(v) => d3.sum(v, (d) => d.raised),
(d) => d.party
)
// En este dataset sólo estan los datos de USA
tmp = d3.csv(
"https://download.data.world/s/ibjfmujmitmsc64h3zpqxmphe5un36",
d3.autoType
)
// lo vuelvo a leer, saco las primeras 2 columnas y alias al resto.
w45_wide = d3.csv(
"https://download.data.world/s/h5wv7bf7mupvfux3bhxxbadha443ej",
d3.autoType
)
w45 = aq
.from(w45_wide)
.fold(["alone", "children", "coworkers", "friends", "partner", "family"])
.rename({ year: "age" })
.objects()
w45_agrupado = [
...d3.rollup(
w45,
(v) => d3.sum(v, (d) => d.value),
(d) => d.key
)
].map((d) => ({ key: d[0], value: d[1] }))
Plot.plot({
marks: [
Plot.barX(w45_agrupado, {
x: "value",
y: "key",
sort: { y: "x", reverse: true },
fill: "darkolivegreen"
}),
Plot.ruleX([0])
],
marginLeft: 80
})
import { LineChart } from "@d3/multi-line-chart"
// la funcion LineChart espera que X sea una fecha
//
mLineChart = LineChart(w45, {
x: (d) => d.age,
y: (d) => d.value,
z: (d) => d.key,
yLabel: "↑ time (%)",
width,
height: 500,
color: "steelblue",
voronoi // if true, show Voronoi overlay
})
voronoi = false
w46 = d3.csv(
"https://download.data.world/s/ta2wqz4b56s66rckiezmffqfq4mool",
d3.autoType
)
d3.extent(w46, (d) => d.year)
w46_4c = aq
.from(w46)
.select("drug", "year", "wholesale_price", "retail_price")
.relocate("drug", { after: "year" })
.fold(["wholesale_price", "retail_price"])
.objects()
.map((d) => ({
year: new Date(d.year, 1, 1),
drug: d.drug,
key: d.key,
value: d.value
}))
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