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datasets = ({
"Iris Flower": irisObject,
// "Iris Pick 3 random": irisObjectReduced,
// "Square-Line dataset": squareLineObject,
// "QCM Alcohol sensors": qcmObject,
// "Random uniform data 100x100": randomUniform100x100Object,
// "Random normal data 100x10": randomNormal100x10Object,
// "Single datapoint": singleRandom1x100Object,
// "Three datapoints": threeRandom3x100Object,
// "Single four-variate datapoint": singleRandom1x4Object,
// "Two four-variate datapoints": doubleRandom2x4Object,
// "Ten four-variate datapoints": tenRandom10x4Object,
// "Poker hands": pokerObject,
// "Three Clusters": customObject,
// "Three Clusters for ABCD": customObjectNew,
// "Three Clusters with 3": customObjectNew3,
// "Three Clusters with 6": customObjectNew6,
// "Three Clusters with 9": customObjectNew9,
// "Three Clusters with 15": customObjectNew15,
// "Three Clusters with 30": customObjectNew30,
// "Three Clusters with 90": customObjectNew90,
// "Three Clusters with 300": customObjectNew300,
// "(harder) Three Clusters with 3": customObjectNewBetter3,
// "(harder) Three Clusters with 6": customObjectNewBetter6,
// "(harder) Three Clusters with 9": customObjectNewBetter9,
// "(harder) Three Clusters with 15": customObjectNewBetter15,
// "(harder) Three Clusters with 30": customObjectNewBetter30,
// "(harder) Three Clusters with 90": customObjectNewBetter90,
// "(harder) Three Clusters with 150": customObjectNewBetter150,
// "(harder) Three Clusters with 300": customObjectNewBetter300,
// "Three Clusters with more data": customObjectMoreValues,
// "Five Clusters": customObject2,
// "Single 2D Billiard Dynamics": billiardObject,
// "Single 2D BD / single datapoint": billiardVerticalObject,
// "Multiple billiard trajectories": billiardMultipleObject,
// "Cement Classification": cementObject,
// "Distillation Column sensors": distillationObject,
// "Cheddar chemical components": cheddarObject,
// "Bio Reactor yields": bioreactorObject,
// "Raw powder": powderRawObject,
// "Film thickness": filmThicknessObject,
// "Flotation device": flotationCellObject,
// "Food consumption": foodConsumptionObject,
// "Food texture": foodTextureObject,
// "Kamyr digester pulp quality": kamyrObject,
// "Low-density polyethylene properties": ldpeObject,
// "Peas properties and taste": peasObject,
// "Sawdust Properties": sawdustObject,
// "Material Characterization": materialCharacterizationObject,
// "Wine properties and taste": wineDOEObject,
// "Chemical Solvent properties": solventsObject,
// "Room Temperature": roomTemperatureObject,
// "Systematic Method": systematicMethodObject,
// "Multiple Billiard trajectories 1": multipleBilliard1Object,
// "Multiple Billiard trajectories 3 Clusters 10": multipleBilliard2Object,
// "Multiple Billiard trajectories 3 Clusters 60": multipleBilliard3Object,
// "Multiple Billiard trajectories 3 Clusters 60 (smaller)": multipleBilliard3ObjectSmaller,
// MNIST: mnistObject,
"Wine Data 3 Classes": wineObject,
// "CERN Test object": cernTestObject,
// "Outlier Test 100 samples": outlier100Object,
// "Outlier Test 10 samples": outlier10Object,
// "Fixed outlier 100 samples": fixedOutlier100Object,
// "Fixed outlier 10 samples": fixedOutlier10Object,
// "Billiard 3 Clusters, 30 Trajectories, 50 iterations": newBilliard3Clusters50iters,
"Test Object": testObject
})
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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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