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ic-dataviz
Published
Edited
Sep 12, 2021
1 star
7
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dataSample = FileAttachment("diamonds@2.csv").csv()
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data = FileAttachment("diamonds@2.csv").csv({typed: true})
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d3 = require("d3@6")
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data3 = d3.json(url)
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data4 = d3.csv(url2)
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firstFive = data.slice(0,5)
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lastFive = data.slice(data.length-5, data.length)
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data2 = firstFive.map(function(d,i){ //Here 'd' represents each row entry of firstFive dataset
return{
"": d[""],
carat: d.carat,
cut: d.cut,
color: d.color,
clarity: d.clarity,
depth: d.depth,
table: d.table,
price: d.price,
x: d.x,
y: d.y,
z: d.z
}
})
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copyData = JSON.parse(JSON.stringify(firstFive))
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printTable(firstFive)
// Or, can directly do: printTable(data.slice(0, 5))
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import {printTable} from '@uwdata/data-utilities'
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md`>Number of rows = ${data.length}<br>
Number of columns = ${Object.keys(data[0]).length}`
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printTable(data.slice(0,6), [{field: 'cut', title: 'cut'}, {field: 'color', title: 'color'}, {field: 'clarity', title: 'clarity'}])
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printTable(data.filter(d => d.cut === 'Ideal').slice(0,5)) //It means it takes (d) as an argument and returns (d.cut === 'Ideal')
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// printTable(data.filter(function(d) {return d.cut === 'Ideal'}).slice(0,5))
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{
for (const i in copyData){
copyData[i].price_per_carat = parseFloat(copyData[i].price/copyData[i].carat).toFixed(2);
}
}
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printTable(copyData)
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printTable(data.slice(0,6).sort((a,b) => (a.carat-b.carat))) //OR, printTable(data.slice(0, 6).sort(function(a,b) {return a.carat-b.carat}))
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order = ["Ideal", "Good", "Very Good", "Premium"]
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printTable(
data.slice(0,6).sort((a,b) => {
return (
order.indexOf(a.cut) - order.indexOf(b.cut)
);
})
)
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keys = Object.keys(data[0])
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test = fromColumns(
{
day: ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'],
state: ['reading', 'playing', 'writing', 'interview', 'chilling']
}
)
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import {fromColumns} from '@uwdata/data-utilities'
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import { vl } from "@vega/vega-lite-api"
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vegalite = require("vega-embed@6")
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import {tb} from "@mariodelgadosr/target-blank"
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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.
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