data = aq.fromCSV(await FileAttachment("data@4.csv").text())
data.view(5)
data
.derive({ range: (d) => `${d["range"]} ` * 1 })
.derive({ year: (d) => `${d["year"]} ` * 1 })
.filter((d) => d.range > 0)
.filter((d) => d.year > 0)
.orderby(aq.desc("range"))
.view(5)
data
.derive({ range: (d) => `${d["range"]} ` * 1 })
.derive({ year: (d) => `${d["year"]} ` * 1 })
.filter((d) => d.range > 0)
.filter((d) => (d.year > 0) & (d.year < 2024))
.orderby(aq.desc("range"))
.view(5)
data
.derive({ range2: (d) => `${d["range"]} ` * 1 })
.derive({ year: (d) => `${d["year"]} ` * 1 })
.filter((d) => d.range2 > 0)
.filter((d) => (d.year > 0) & (d.year < 2024))
.orderby("range2")
.view(5)
data_final = data
.derive({ range: (d) => `${d["range"]} ` * 1 })
.filter((d) => d.range > 0)
.derive({ year: (d) => `${d["year"]} ` * 1 })
.filter((d) => (d.year > 0) & (d.year < 2024))
.orderby(aq.desc("range"))
.objects()
data
.filter((d) => d.range > 0)
.filter((d) => (d.year > 0) & (d.year < 2024))
.derive({ range2: (d) => `${d["range"]} ` * 1 })
.groupby("technology")
.rollup({
mean: (d) => op.mean(d.range2),
median: (d) => op.median(d.range2),
max: (d) => op.max(d.range2),
count: op.count()
})
.orderby(aq.desc("mean"))
.view()
data
.filter((d) => d.range > 0)
.filter((d) => (d.year > 0) & (d.year < 2024))
.derive({ range2: (d) => `${d["range"]} ` * 1 })
.groupby("year")
.rollup({
mean: (d) => op.mean(d.range2),
median: (d) => op.median(d.range2),
max: (d) => op.max(d.range2),
count: op.count()
})
.orderby(aq.desc("mean"))
.view(6)
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.
