Public
Edited
May 1, 2023
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wrappedTechs= ({
"AWS":["AWS CloudFront","AWS Route 53","AWS S3"],
"APIs":["Dropbox API","Google Photos API","web sound API"],
"Git & Github":["Git","Github"],
"Advanced JS":["Javascript Generators"],
"Java":["Java Spring"],
"Node": ["Nodemon", "Npm"],
"*":["Rake","Release-it","xml2json","writing"],
"Ruby on Rails": ["Ruby"],
"SEO":["Seo sitemaps"],
"Web Debugging":["SourceMaps","Chrome Lighthouse"],
"CI/CD":["TravisCI", "Github Actions"],
"Web Testing":["Taiko"],
"Typescript":["Ts-node"],
"PWA":["Web Manifest"]
})
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dataCells2 = Object.keys(dataWithCounts)
.flatMap(key => Object.keys(dataWithCounts[key])
.map(year => ({tech: key, year: year, value: dataWithCounts[key][year]})))
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import {Swatches} from "@d3/color-legend"
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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.
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