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
Women in the German Bundestag by PartyDiversity in the German BundestagPlaying Dota 2 as Crystal MaidenCumulative Dota 2 Stats - Do I play a lot?Pizza Chart - the temptation was strong with this oneWho Shrinks more with Age and what does Sports have to do with it?Exotic Animals for Sale on the Black MarketAuthors of Books with the Word Statistics in the TitlePlaying Piano with the Vaccine in GermanyThe Babyklappe in GermanyStripy Walking Mobility during CovidBlocks Colors: Charts vs Number of ColorsMoon to Earth Distance - Radial AreaDoes Pineapple Belong on Pizza?Deforestation - Arc DiagramABBA Lyrics Sentiment over the YearsAnnual Global Sea LevelsColors Frequently used Together in Charts in 2020!Plastic Bags since 1950 - packed squaresGender Employment Gap in EuropeSun Distance to Earth Year TilesAnimated April Day in HamburgHamburg from Dusk till DawnCovid Deaths in Germany .. what has changed?Part-time work in Europe by Gender and Number of KidsWorld Population Aging - UN 2013Years of Colonialism in Africa and Asia - Du Bois Radial Chart30 Days of Perceived Frustration in 3D BarsAnnual Global Sea Levels vs Temperature
2018 World Literacy in Confidence Strips
y = d3.scaleBand()
.domain(groups)
.range([height, height/2.2])
x = d3.scaleLinear()
.domain([0,100])
.nice()
.range([margin.left, width - margin.right])
xAxis = g => g
.attr('transform', `translate(0,${height +30 - margin.top})`)
.call(d3.axisBottom(x))
popExtent = {
const bounds = data.map((d) => d.percentage).sort(d3.ascending);
return [bounds[0], bounds[bounds.length - 1]];
}
size = d3.scaleSqrt()
.domain(popExtent)
.nice()
.range([0.5, 5])
dataExtent = {
const bounds = data.map((d) => d.percentage).sort(d3.ascending);
return [bounds[0], bounds[bounds.length - 1]];
}
color = d3.scaleOrdinal()
.domain(countries) .range(colors)
.unknown('black')
radius = 1
padding = 0.5
height = 700
rmargin = width/6
margin = ({
left: 90,
right: rmargin,
top: 100,
bottom: 0
})
colors2 = ['#E8ECFB', '#DDD8EF', '#D1C1E1', '#C3A8D1', '#B58FC2',
'#A778B4', '#9B62A7', '#8C4E99', '#6F4C9B', '#6059A9',
'#5568B8', '#4E79C5', '#4D8AC6', '#4E96BC', '#549EB3',
'#59A5A9', '#60AB9E', '#69B190', '#77B77D', '#8CBC68',
'#A6BE54', '#BEBC48', '#D1B541', '#DDAA3C', '#E49C39',
'#E78C35', '#E67932', '#E4632D', '#DF4828', '#DA2222',
'#B8221E', '#95211B', '#721E17', '#521A13']
colors = ['#4477AA', '#EE6677', '#228833', '#CCBB44', '#66CCEE',
'#AA3377', '#BBBBBB', '#000000']
groups = Array.from(new Set(data.map(d => d.gender)))
countries = Array.from(new Set(data.map(d => d.CountryName)))
data = data_raw[0].sort((a, b) => d3.ascending(a.percentage, b.percentage))
data_ci = data_raw_ci[0]
data_raw=Promise.all([csvs['all']].map(file => d3.csv(file, d3.autoType)))
csvs["ci"]
data_raw_ci = Promise.all([csvs["ci"]].map((file) => d3.csv(file, d3.autoType)))
d3 = require("d3@5")
import {form} from "@mbostock/form-input"
html`<link href="https://fonts.googleapis.com/css?family=IBM+Plex+Mono&display=swap" rel="stylesheet">`
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.
