I'm a professor of mathematics at the University of North Carolina Asheville. I've also done a fair amount of consulting work over the years focusing on scientific and data visualization.
I'm happy to be part of the first Observable Ambassador's cohort.
// Automatic choice dependent on domain and width
chart1 = Plot.plot({
width: svg_width,
height: 200,
x: {
domain: [d3.utcParse("%Y")(2017), d3.utcParse("%Y")(2023)]
},
y: { domain: [-30, 30] },
marks: [Plot.ruleX([d3.utcParse("%Y")(2017)]), Plot.ruleY([0])]
})
// Specifying exactly where you'd like the ticks to be placed and a format
chart2 = Plot.plot({
height: 200,
x: {
domain: [d3.utcParse("%Y")(2017), d3.utcParse("%Y")(2023)],
ticks: d3.timeMonth.range(
d3.utcParse("%Y")("2017"),
d3.utcParse("%Y")("2024"),
6
),
tickFormat: d3.timeFormat("%b/%y")
},
y: { domain: [-30, 30] },
marks: [Plot.ruleX([d3.utcParse("%Y")(2017)]), Plot.ruleY([0])]
})
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.