viewof warmest = Inputs.toggle({label: "Warm"})
viewof topN = Inputs.range([1, 50], {label: "Top N", step: 1, value: 10})
Plot.plot({
width: width,
marginBottom: 40,
color: {
legend: true,
scheme: "BuRd"
},
y: {
axis: null
},
x: {
tickRotate: 45
},
marks: [
Plot.barY(yearlyTemp, {x: "jahr", y: 1, fill: "mean"})
]
})
SummaryTable(dailyCombined)
grid = {
const svg = d3.create("svg");
new WeatherGrid(svg)
.options({cellColor: "condition", tempScale: "month", dateFormat: "%Y/%m/%d"})
.icon(icon)
.month(monat-1)
.data(dailyCombined.filter(x=>x.Zeit.getFullYear()>2002))
.column({
date: "Datum",
condition: "Kategorie",
low: "Temperatur Min",
high: "Temperatur Max",
avg: "Temperatur"
})
.render();
return svg.node();
}
jahresWerte = dailyCombined.filter(x=>toYear(x.Zeit)===""+jahr)
tagesDaten = combinedByDay.get(d3.timeFormat("%d.%m.%Y")(tag))
temperatur = FileAttachment("data_OBS_DEU_PT1H_T2M.csv").csv({typed: true})
toYear = d3.timeFormat("%Y")
toYear(dailyTemp[0].tag)
import {combinedByDay, dailyCombined} from "@iimog/wetter-daten-aufbereitung"
import {WeatherGrid} from "@iimog/weather-grid"
import {WeatherChart} from "@analyzer2004/sunny-day-rainy-day-in-seattle"
import {WeatherWheel, icon} from "@analyzer2004/west-coast-weather-from-seattle-to-san-diego"
import {SummaryTable} from "@observablehq/summary-table"
import {T} from "@pbeshai/tidyjs"
import {toc} from "@mbostock/toc"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
