//viewof favorite = Inputs.select(iris, {["Sepal_Length", "Sepal_Width", "Petal_Length", "Petal_Width"]})
width = 400
height = 400
margin = ({top: 20, right: 20, bottom: 120, left: 40})
x = d3.scaleLinear() // Escala lineal
.domain([0, d3.max(iris.map(function(d) { return d[campo_x] } ) )])// requiere un dominio 0 -> max(cantidad)
.range([margin.left, width - margin.right]) // y un rango en la gráfica: márgenes laterales
y = d3.scaleLinear() // Escala lineal
.domain([0, d3.max(iris.map(function(d) { return d[campo_y] } ) )])// requiere un dominio 0 -> max(cantidad)
.range([height - margin.bottom, margin.top]) // y un rango en la gráfica: márgenes laterales
xAxis = function (g){
return g.attr("transform", `translate(0,${height - margin.bottom})`) // Esta línea llama al método transform y a translate y "desplaza" el eje dibujado desde 0 y movido sobre el eje Y en height - margin.bottom pixeles
.call(d3.axisBottom(x))
}
yAxis = function (g){ return g.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))}
import {select} from "@jashkenas/inputs"
iris.map(function(d) { return d[campo_y] } )
campo_y
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.