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Observable
The end-to-end solution for building and hosting better data apps, dashboards, and reports.
Published
Edited
Apr 14, 2022
18 forks
Importers
13 stars
6
Templates
Boilerplates
(17)
Integrations
(7)
Developer Workflows
(7)
Hiring TimelineBreakout Room Breaker Outer“Happy Birthday” SynchronizerSurvey Cross-Tabulation AnalysisAgenda Tracker (Clock Time)Survey Report BuilderAgenda Tracker (Start Button)Team-Order ShufflerIntegration Test FlakinessIntegration Test DurationStartup Operating ModelTargets vs. ActualsUser RetentionPlot ScatterplotPlot U.S. MapPlot World MapUser Retention with SegmentsSimple SVGInteractive SVGInteractive HTML CanvasSimple HTML CanvasSimple D3D3 scatterplotD3 U.S. mapD3 world mapProcessing (p5.js)WebGL ShaderBlog PostGitHub: Pull Request VisualizerAWS HTTP Status DashboardStripe API StarterGoogle Sheets StarterSQLite StarterGitHub API StarterReglThree.jsGitHub Stargazer HistoryFigma API StarterAWS S3 API StarterAWS EC2 API StarterGitHub API ExplorerGitHub Suggested ReviewersPlot: HistogramInput + ChartSearch + TableSQL + ChartThe MoMA Collection DataU.S. Geographic DataPlot Test DataNOAA Hourly Weather DataEIA Electricity DataBandcamp Sales Data
Google Merchandise Sales Data
DarkCideS: Bats in Caves Data
Also listed in…
Curated Datasets
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db
SELECT * FROM items
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db
SELECT * FROM events LIMIT 100
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db
SELECT type, COUNT(*)::INT AS count FROM events GROUP BY type ORDER BY count DESC
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SELECT MIN(date) AS min, MAX(date) AS max FROM events
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db
SELECT *
FROM events
JOIN items on events.item_id = items.id
WHERE type = 'purchase'
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purchases
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Plot.plot({
marks: [
Plot.rectY(
purchases,
Plot.binX(
{ y: "sum" },
{
x: "date",
y: "price_in_usd",
fill: "category",
thresholds: d3.utcDay,
}
)
)
],
color: { legend: true, columns: "100px" },
})
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db
SELECT * FROM users LIMIT 100
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db
SELECT date_trunc('day', date) as day, count(*)::INT as count
FROM users
WHERE date > TIMESTAMP '2020-07-01'
GROUP BY day
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Plot.rectY(dailyFirstTouch, { x: "day", y: "count", interval: d3.utcDay }).plot()
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items = FileAttachment("items.csv").csv({ typed: true })
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events = FileAttachment("events@1.csv").csv({ typed: true })
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users = FileAttachment("users.csv").csv({ typed: true })
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db = DuckDBClient.of([
FileAttachment("items.parquet"),
FileAttachment("events@1.parquet"),
FileAttachment("users@1.parquet"),
])
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db.describe()
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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.
Learn more