AAPL-1980-2024-Monthly.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
// ... your visualization here
// ... your visualization here
// ... your code here
// ... your code here
// ... your code here
// Uncomment to activate
// `Close` is standardized for you.
// You should do the `Volume` yourself
data_standardized = aq.from(data)
.derive({CloseStandardized: d => ( d.Close - op.mean(d.Close) ) / op.stdev(d.Close) || 0})
.derive({VolumeStandardized: d => ( d.Volume - op.mean(d.Volume) ) / op.stdev(d.Volume) || 0})
.objects()
// ... your code here
// ... your code here
// ... your code here
viewof control_year = Inputs.range([1985, 2025], {label: "Start Year", step: 1})
aq.from(data_standardized)
.filter(aq.escape( d => d["Date"] > control_year))
.objects()
Inputs.table(data_standardized)
data_standardized[0]["Date"].constructor.name
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
// ... your code here
import {howTo} from "@clokman/howto"
import {Wrangler, op} from "@observablehq/data-wrangler"
import {toc} from "@nebrius/indented-toc"
import {imageToDo} from "@clokman/student-blocks"
imageToDo
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.
