contents("h1, h2, h3", "My Table of Contents", true)
showtypes(dataObject)
viewof selection = Inputs.table(dataObject, { /* width: 800, */ required: false })
selection // now I can return the columns as an array
viewof dataObjectAndColumns = Inputs.table(dataObject, { width: 1000 })
viewof dummyDataView = Inputs.table(dummyData, { width: 500 })
dummyDataView
Type Table, then Shift-Enter. Ctrl-space for more options.
dummyDataView
Object.keys(dummyDataView[0])
show(exampleDataCars.slice(0, 20), undefined, "*")
show(exampleDataCars.slice(0, 20), ["Name", "Horsepower"], 200)
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"field": "Lower",
"type": "quantitative"
}
}
},
{
"mark": {
"type": "text",
"font": "DIN",
"fontWeight": "narrow",
"align": "left",
"baseline": "bottom",
"filled": true,
"size": 10,
"color": "#858377",
"stroke": "transparent",
"strokeWidth": 0.01,
"xOffset": {
"expr": "_shapeOffset * 2.4"
},
"dy": 25,
"text": [
"Fertility remains 0.5",
"children lower than in ",
"the median scenario"
]
},
"encoding": {
"y": {
"field": "Lower",
"type": "quantitative"
}
}
},
{
"mark": {
"type": "text",
"font": "DIN",
"fontWeight": "bolder",
"align": "left",
"baseline": "bottom",
"filled": true,
"size": 10,
"color": {
"expr": "_historicColour"
},
"stroke": "transparent",
"strokeWidth": 0.01,
"xOffset": {
"expr": "_shapeOffset * 2.4"
},
"text": [
"UN PROBABILISTIC",
"SCENARIO"
]
},
"encoding": {
"y": {
"field": "UN",
"type": "quantitative"
}
}
},
{
"mark": {
"type": "text",
"font": "DIN",
"fontWeight": "bolder",
"fontStyle": "italic",
"align": "left",
"baseline": "center",
"filled": true,
"size": 12,
"color": "#fe666b",
"stroke": "#transparent",
"strokeWidth": 0.01,
"xOffset": {
"expr": "_shapeOffset * 2.4"
},
"yOffset": 2,
"text": ["IIASA*"]
},
"encoding": {
"y": {
"field": "IIASA",
"type": "quantitative"
}
}
},
{
"mark": {
"type": "text",
"font": "DIN",
"fontWeight": "bolder",
"fontStyle": "italic",
"align": "left",
"baseline": "top",
"filled": true,
"size": 12,
"color": "#efb92d",
"stroke": "transparent",
"strokeWidth": 0.01,
"xOffset": {
"expr": "_shapeOffset * 2.4"
},
"yOffset": -3,
"text": ["IHME**"]
},
"encoding": {
"y": {
"field": "IHME",
"type": "quantitative"
}
}
}
]
}
]
})
exampleDataCars = vegaData["cars.json"]() // load and parse cars data
vegaData["cars.json"].url
import {
toc as contents, // src = import { toc as contents } from "@jonfroehlich/collapsible-toc"
indenttoc as indenttoc,
fmt as fmt,
hl as mdhl,
printVegaJSON as printVega,
vegalite as VegaLite,
vegaEmbed as Vega,
printTableTypes as showtypes, // src = import { printTableTypes } from "@jonfroehlich/data-utilities"
printTable as show, // src = import { printTable as showtable } from "@jonfroehlich/data-utilities"
note as note
} from "@pbiqueryous-repo/tools"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
