dataSim2 = ({
iterations: d3.range(78).map((d, i) => {
return {
label: "Year " + (2023 + i) + ""
};
}),
values: dataCombined2.map((d) => {
const result = {
name: d.gname,
history: [d.pvalue]
};
d3.range(78 - 1).forEach((_) => {
const perc = 1 + d.gvalue / 100;
const last = result.history[result.history.length - 1];
console.log(perc, last);
result.history.push(last * perc);
});
return result;
})
})
dataGDP = load(
"https://cadasa.github.io/API_NY.GDP.MKTP.CD_DS2_en_csv_v2_6011335.csv"
)
dataGDPLastYear2 = dataGDP
.map((d) => {
return {
name: d["Country Name"],
value: +d["2022"],
history: d3.range(1960, 2023).map((v) => +d[v]),
filtered: d3
.range(1960, 2023)
.map((v) => +d[v])
.filter((d) => d)
};
})
.filter((d) => d.history.length != d.filtered.lenth)
dataGDPLastYear = dataGDP
.map((d) => {
return {
name: d["Country Name"],
value: +d["2022"],
history: d3.range(1995, 2023).map((v) => +d[v]),
filtered: d3
.range(1995, 2023)
.map((v) => +d[v])
.filter((d) => d)
};
})
.filter((d) => d.history.length != d.filtered.lenth)
dataGrowth = load(
"https://cadasa.github.io/API_NY.GDP.MKTP.KD.ZG_DS2_en_csv_v2_5994650.csv"
)
dataGrowthAveraged = dataGrowth.map((d) => ({
name: d["Country Name"],
value: d3.mean([+d["2022"], +d["2021"], +d["2020"], +d["2019"], +d["2018"]])
}))
dataGrowthAveragedSorted2 = dataGrowthAveraged2
.slice()
.sort((a, b) => (a.value < b.value ? 1 : -1))
dataGrowthAveraged2 = dataGrowth.map((d) => ({
name: d["Country Name"],
value: d3.mean([+d["2022"], +d["2021"]])
}))
dataGrowthAveragedSorted2.filter((d) => d.name === "Viet Nam")
dataCombined = dataGrowthAveraged.map((d,i)=>({gname:d.name,gvalue:d.value,
pname:dataGDPLastYear[i].name,
pvalue:dataGDPLastYear[i].value,
history:dataGDPLastYear[i].history}))
dataCombined2 = dataGrowthAveraged.map((d, i) => ({
gname: d.name,
gvalue: d.value,
pname: dataGDPLastYear2[i].name,
pvalue: dataGDPLastYear2[i].value,
history: dataGDPLastYear2[i].history
}))
dataCombinedSorted = dataCombined
.slice()
.filter(d=>!filteredGroups.includes(d.gname))
.filter(d=>d.gname.indexOf('IBRD')==-1)
.sort((a,b)=>a.pvalue<b.pvalue?1:-1)
.filter(d=>d.pvalue)
.filter(d=>d.gvalue<10)
dataCombinedSortedPast = dataCombinedSorted.slice().sort((a,b)=>a.history[0]<b.history[0]?1:-1)
d3 = require('d3@v5')
import {load} from "@bumbeishvili/fetcher"
import {text} from "@jashkenas/inputs"
import {comments} from "@bumbeishvili/utils"
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.
