penguinData
Type Table, then Shift-Enter. Ctrl-space for more options.
penguinData.map(d => ({species: d.species, massKilograms: d.body_mass_g / 100, billRation: d.culmen_length_mm / d.culmen_depth_mm})).filter((d) => d.billRatio > 3.5)// Add your code here to do the wrangling steps above!
// Find the minimum culmen length in penguinData:
d3.min(penguinData, d => d.culmen_length_mm)
// Alternatively:
d3.deviation(penguinData, d => d.culmen_depth_mm)// Standard deviation of culmen depth:
d3.count(penguinData, d => d.flipper_length_mm)// Count of flipper length values:
penguinData
Type Table, then Shift-Enter. Ctrl-space for more options.
groupSpecies = d3.group(penguinData, (d) => d.species)// Group penguinData by species (store Map as groupSpecies):
groupSpecies.get("Adelie")// Then get just the Adelies:
groupSpeciesIsland = d3.group(penguinData, d => d.species, d => d.island)
// Group penguinData by species and island (store as groupSpeciesIsland):
groupSpeciesIsland.get("Adelie").get("Dream")
d3.rollup(
penguinData,
(v) => d3.mean(v, (d) => d.body_mass_g),
(d) => d.species
)// Find the mean body mass by penguin species:
d3.rollup(penguinData, v => d3.mean(v, d => d.flipper_length_mm), d => d.species, d => d.sex)
// Find the mean flipper length by penguin species and sex:
arrayOfArrays = [
[1, 2],
[3, 4]
]
arrayOfArrays.map(([firstNumber, secondNumber]) => ({
firstNumber,
secondNumber
}))
d3
.flatRollup(
penguinData,
(v) => d3.mean(v, (d) => d.body_mass_g),
(d) => d.species
)
.map(([species, meanMass]) => ({ species, meanMass }))// Use flatRollup to find mean body mass by penguin species, then map to get an array of objects:
Plot.plot({
marks: [
Plot.barY(
penguinData,
Plot.groupX(
{ y: "deviation" },
{ y: "body_mass_g", x: "species", sort: { x: "y", reverse: true } }
)
)
]
})// Create a new bar chart with Observable Plot to visualize mean body mass by species:
import { showMe } from "@observablehq/show-me"
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.
