import { SummaryTable } from "@observablehq/summary-table"
SummaryTable(data)
filter = d3.timeParse("%Y-%m-%dT%H:%M:%S.%LZ")("2022-10-16T13:03:14.604Z")
data_filtered = data.filter((d) => d.date < filter)
SummaryTable(data_filtered)
viewof movingavgWindow = Inputs.range([1, 200], {
step: 1,
label: "Window size"
})
Plot.dot(data_filtered, {
x: "date",
y: "state",
title: "title",
fill: (d, i) => (d.state > movingAvg[i] + 5 ? 1 : 0) // adding 5 since we want to highlight points that are a least a bit *above* the moving average
}).plot({
y: { grid: false },
marks: [
Plot.ruleX(data_filtered, {
x: "data",
y: "state",
stroke: "#eee",
strokeWidth: 2
}),
Plot.line(
data_filtered,
Plot.windowY({
x: "date",
y: (d) => d.state + 5,
k: movingavgWindow,
stroke: "rebeccapurple",
shift: "trailing"
})
),
Plot.ruleY([0])
],
marginLeft: 30,
marginBottom: 100,
marginRight: 50,
width: width,
color: {
range: ["steelblue", "orange"]
}
})
Plot.plot({
y: {
grid: true,
type: "log"
},
marks: [Plot.line(data_filtered, { x: "date", y: "state" })]
})
viewof bins = Inputs.range([3, 20], {step: 1, label: "Bins"})
Plot.plot({
marks: [
Plot.ruleY([0]),
Plot.rectY(data, Plot.binX({ y: "sum" }, { x: "state", thresholds: bins }))
]
})
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