Award-winning creative focused on data-driven art and visualizations, trying to push the boundaries of the web one visual story at a time ✨
Published
Edited
Mar 25, 2021
44 forks
Importers
Comments locked
21 stars
Introduction to SVG and D3.js1. Draw a flower petal on the screen2. Select existing petal(s) and bind movie data3. Create a petal for each movie4. Size each petal based on its movie's rating5. Turn petals into flowers for each movie7. Position film flowers by the genres they shareWorkshop Utility Functions
6. Add filter by options
updateBarsOld = (svg, data) => {
const rectWidth = 50
// ✨ OUR CODE HERE
}
updateBarsNew = (svg, data) => {
const rectWidth = 50
// ✨ OUR CODE HERE
}
{
const oldSVG = html`<svg height=100 style='overflow: visible' />`
const newSVG = html`<svg height=100 style='overflow: visible' />`
const code = html`<code />`
const button = html`<button>new data!</button>`
d3.select(button).on('click', d => {
// randomly generate an array of data
const data = _.times(_.random(3, 8), i => _.random(0, 100))
updateBarsOld(oldSVG, data)
updateBarsNew(newSVG, data)
// update div with new data array:
d3.select(code).text(JSON.stringify(data).replace(/\,/g, ', '))
})
return html`
<h4>old way:</h4>
${oldSVG}
<h4>new way:</h4>
${newSVG}
<p>
${button} ${code}
</p>
`
}
{
const rectWidth = 50
const svgHeight = 100
const svg = html`<svg height=${svgHeight} style='overflow: visible' />`
const code = html`<code />`
const button = html`<button>new data!</button>`
function updateBars() {
// select svg so that transition can be localized within selection
const t = d3.select('svg').transition().duration(1000)
// randomly generate an array of data
const data = _.times(_.random(3, 8), i => _.random(0, 100))
// ✨ YOUR CODE HERE
// update div with new data array:
d3.select(code).text(JSON.stringify(data).replace(/\,/g, ', '))
}
updateBars()
d3.select(button).on('click', updateBars)
return html`
${svg}
<p>
${button} ${code}
</p>
`
}
filtered = _.filter(movies, d => {
// either the genre is in the filtered genres
return (_.includes(filteredGenres, d.genres[0]) ||
// OR the movie's genre isn't one of the top genres, and "Other" is toggled
(_.includes(filteredGenres, 'Other') && !_.includes(topGenres, d.genres[0]))) &&
// AND movie's pg rating is in filtered pg
_.includes(filteredPG, d.rated)
})
filteredFlowers = calculateData(filtered)
{
// this line is a little bit of Observable magic to make sure that every time
// our filter cells update, we use the existing SVG element instead of trashing it and creating a new one
// if you're working in your index.html, you'd create your svg element and select it as we did before
const element = this || scrollSVG(html`<svg width=${width} height=${svgHeight}></svg>`)
const svg = d3.select(element).select('svg')
// create transition animation localized to svg selection
const t = svg.transition().duration(1000)
// ✨ YOUR CODE HERE
return element
}
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.