Public
Edited
Jun 2
insurance = FileAttachment("insurance.csv").csv()
vl.markCircle()
.data(insurance)
.encode(
vl.x().fieldQ("bmi").title("BMI"),
vl.y().fieldQ("charges").title("Insurance Charges"),
vl.color().fieldN("smoker").title("Smoker"))
.width(500)
.height(400)
.title("Relationship Between BMI and Insurance Charges")
.render()
vl.markPoint()
.data(insurance)
.encode(
vl.x().fieldQ("bmi").title("BMI"),
vl.y().fieldQ("charges").title("Insurance Charges"),
vl.color().fieldN("sex").title("Sex"),
vl.shape().fieldN("smoker").title("Smoker"))
.width(500)
.height(400)
.title("Insurance Charges vs BMI by Sex and Smoker Status")
.render()
viewof colorField = Inputs.select(["sex", "smoker", "region"], {label: "Color by"})
vl.markCircle()
.data(insurance)
.encode(
vl.x().fieldQ("bmi").title("BMI"),
vl.y().fieldQ("charges").title("Insurance Charges"),
vl.color().fieldN(colorField),
vl.tooltip(["age", "bmi", "charges"])
)
.width(500)
.height(400)
.title("Relationship Between BMI and Insurance Charges based on Different Factors")
.render()
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.
