import {Wrangler, op} from "@observablehq/data-wrangler"
data_raw = FileAttachment("temperature.csv").csv()
data_raw
Inputs.table(data)
final_data = aq.from(data)
.orderby(aq.desc("temperature"))
.derive({temperatureNum: d => +d.temperature})
.filter(d => d["temperatureNum"] < 50.6)
.filter(d => d["temperatureNum"] > 43.6)
.derive({temperatureCelsius: d => d.temperatureNum/ 1.8 - 32})
.rename({temperatureNum: "temperatureFahrenheit"})
.select('date','temperatureFahrenheit','temperatureCelsius')
.objects()
Wrangler(data_raw)
data = // To use copied code replace "data" with your own variable
aq.from(data_raw)
.orderby(aq.desc("temperature"))
.derive({temperatureNum: d => +d.temperature})
.filter(d => d["temperatureNum"] < 62.3)
.filter(d => d["temperatureNum"] > 60.6)
.derive({temperatureInCelcius: d => (d.temperatureNum-32)*5/9})
.select('date','temperatureNum','temperatureInCelcius')
.rename({temperatureNum: "temperatureInFahrenheit"})
.objects() // Uncomment to return an array of objects
data
Type Table, then Shift-Enter. Ctrl-space for more options.
Inputs.table(data)
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.
