Head coach data science @neuefische, @pyladieshamburg organizer , vice chair on the @python Software Verband, managing member @PSF and part of the D&I PSF work group
function dnorm(x, mean = 0, sd = 1) {
return 1 / sd * dnorm_standard((x - mean) / sd)
}
growth_size = values.length
curve_max = dnorm(growth_mean, growth_mean, growth_sd) * bin_width * growth_size
export2020 =to_billion(d3.sum(data, d => d.TradeValuePrevious))
export2021 = to_billion(d3.sum(data, d => d.TradeValue))
positive_percentage = values.filter(function(v) { return v > 0; }).length / values.length
values = d3.map(data, d=>to_billion(d.TradeValueGrowthValue))
data_old = d3.csvParse(await FileAttachment("Destinations-Growth-2019---2020---Click-to-Select-a-Country@2.csv").text(), d3.autoType)
data= d3.csvParse(await FileAttachment("Exports-Destinations-Growth-2021---2020----Click-to-Select-a-Country.csv").text(), d3.autoType).sort((a, b) => d3.descending(a.TradeValueGrowthValue, b.TradeValueGrowthValue))
line = d3.line()
.curve(d3.curveMonotoneX)
.x(d => x(d[0]))
.y(d => y(d[1]))
formatBillions(2)
formatBillions = d => `${formatNumber(d)}B`;
colors_lea_seydoux = ["#CF5F47","#1A1A1A","#F4EEE2"]
colors = colors_lea_seydoux
normalcolor = "#AE3039"
barcolor = colors[2]
textcolor = colors[1]
background = colors[0]
import { slider } from "@jashkenas/inputs"
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