addTooltips(Plot.plot({
marginRight: 100,
insetBottom: 0,
insetLeft:0,
insetTop: 30,
color: {legend: false, scheme: "ylorrd", width: 400},
marks: [
Plot.barX([70], {fill: "gray", fillOpacity: .5}),
Plot.barX([-10], {fill: "skyblue", fillOpacity: 1}),
Plot.barY([-45], {fill: "orange", fillOpacity: .5}),
Plot.text(['🌋'], {x:0,y:-18, fontSize: 300,}),
Plot.text(['Duration of volcano eruptions since 1950'], {x:39,y:-25, fontSize: 45, fill: "maroon", lineWidth: 20, opacity: 0.8}),
Plot.text(['The Aira volcano in Japan\nstarted erupting in 1955 and\ncontinued erupting until 2016.'], {x:68,y:70, fontSize: 16, fill: "maroon", lineWidth: 20, opacity: 0.8, textAnchor: "end", filter: d=>yearsvolcano>60}),
Plot.text(['years'], {x:69,y:-4, fontSize: 25, fill: "maroon", textAnchor: "end", filter: d=>yearsvolcano>60}),
Plot.text(['Design: Deepsha Menghani | Twitter: Bigdatadipper | Data: Tidy Tuesday'], {x:69,y:-43, fontSize: 15, fill: "gray", textAnchor: "end", fontStyle: "oblique"}),
Plot.arrow(volcanoes_1950, {x1: 0, y1: 0, x2: "years", y2: "years", stroke: "years", bend: true, filter: d=>d.years!=0 & d.years<= yearsvolcano, title: d=>d.volcanoes}),
Plot.link(volcanoes_1950, {x1: "years", y1: "years", x2: "years", y2: 0, stroke: "years",
filter: d=>d.years!=0 & d.years<= yearsvolcano,
title: d=>d.volcanoes}),
Plot.text(volcanoes_1950, {x:"years",y:-4, text: "years", fill: "years", fontSize: d=>10+d.years*.3, filter: (d=>d.years>28 & d.years!=42 & d.years<= yearsvolcano)}),
Plot.text(volcanoes_1950, {x:"years",y:-4, text: "years", fill: "years", dx: -13, fontSize: d=>10+d.years*.3, filter: (d=>d.years===42& d.years<= yearsvolcano)}),
Plot.text(volcanoes_1950, {x:"years",y:-4, text: "years", fill: "red", fontSize: d=>10, dx:-4, filter: d=>d.years<=28& d.years<= yearsvolcano}),
Plot.axisY({ tickSize: 0, fontSize: 0 }),
Plot.axisX({ tickSize: 0, fontSize: 0 }),
], width: 1300, height: 700
}), {stroke: "maroon", "stroke-width": 6}
)
Plot.plot({
style: "overflow: visible;",
marginBottom: 50,
marginLeft: 75,
insetBottom: 10,
insetLeft: 10,
marks: [Plot.barY([23], {fill: "black", fillOpacity: 1}),
Plot.ruleX([6.5], {stroke: "gray", opacity: 0}),
Plot.ruleX([10], {stroke: "gray", opacity: 0}),
Plot.ruleY([0], {stroke: "gray", opacity: 0.2}),
Plot.text([`Spurious Correlations`], {x:6.5, y:21.5, frameAnchor: "middle", fontSize: 70, lineWidth: 25, textAnchor: "start", lineHeight: 1.2, clip: false, fill: "white", opacity: 1, fontStyle: "oblique"}),
Plot.text([`Drink less beer, Get attacked less by bears!!`], {x:6.5, y:18.9, frameAnchor: "middle", fontSize: 40, lineWidth: 25, textAnchor: "start", lineHeight: 1.2, clip: false, fill: "white", opacity: 1}),
Plot.text([`Months with higher % beer production saw a higher % of bear attacks.`], {x:7.7, y:10, frameAnchor: "middle", fontSize: 20, lineWidth: 10, textAnchor: "start", lineHeight: 1.2, clip: false, fill: "gray", opacity: 1, fontStyle: "oblique"}),
Plot.dot(beer_bear_correlation, {x: "perc_prod", y: "perc_attacks", r: 10, stroke: "#d2b48c", fill: "#d2b48c", title: d=>d.monthabb, opacity: 1}),
Plot.dot(beer_bear_correlation, {x: "perc_prod", y: d=>d.perc_attacks-0.1, r: 4, stroke: "lightblue", fill: "white", title: d=>d.monthabb}),
Plot.text(beer_bear_correlation, {x: d=>d.perc_prod+0.1, y: d=>d.perc_attacks+0.6, r: 3, fill: "gray", text: d=>d.monthabb}),
Plot.linearRegressionY(beer_bear_correlation, {x: "perc_prod", y: "perc_attacks", ci: 0.1, stroke: "white"}),
Plot.image(beer_bear_correlation, {x: 9.49, y: 4.9, width: 260,
src: "https://th.bing.com/th/id/OIP.YcBnzliiACwk4-5FX6qI5QHaHa?w=159&h=180&c=7&r=0&o=5&dpr=1.3&pid=1.7"
}),
Plot.image(beer_bear_correlation, {x: 9.6, y: 4, width: 100,
src: "https://th.bing.com/th/id/OIP._vZBqe6o4WNetvdqVfYAnwHaHP?w=171&h=180&c=7&r=0&o=5&dpr=1.3&pid=1.7"
}),
Plot.axisY({ tickSize: 0, fontSize: 18, label: "Percentage of Bear attacks", anchor: "left", labelAnchor: "center", ticks: 4}),
Plot.axisX({ tickSize: 0, fontSize: 18, label: "Percentage of Beer production", anchor: "bottom", labelAnchor: "center", ticks: 4}),
],
height: 700,
width: 900
})
Plot.plot({
insetTop: 10,
insetBottom: 10,
marks: [Plot.image(avocadoprices.slice(0,1), {x: "Date", y: 1.4, src: "url", title: "Date", width: 700, dx: 500, opacity: .1}),
Plot.barY([3], {fill: "green", fillOpacity: 0.04}),
Plot.barY([2.52], {fill: "pink", fillOpacity: 0.1}),
Plot.lineX(avocadoprices, Plot.windowY({x: "Date", y: "AveragePrice", k: k, stroke: "type", strokeWidth: 2,
filter: d=>d.region === regionselected,
//filter: d=>d.Date >= dateinput,
title: "AveragePrice"})),
Plot.text(['Maximum average price across regions over time'], { y: 2.46, fontSize: 15, dx: -300, fill: "orange"}),
Plot.text(['Avocado price over time'], { y: 2.7, fontSize: 60, dx: +470, fill: "gray", textAnchor: "end", opacity: 0.7}),
Plot.text(['-Organic'], { y: 2.1, fontSize: 20, dx: -460, fill: "forestgreen", textAnchor: "start"}),
Plot.text(['-Conventional'], { y: 0.6, fontSize: 20, dx: -460, fill: "maroon", textAnchor: "start"}),
Plot.ruleY([0]),
Plot.ruleY([2.52], {stroke: "orange"}),
Plot.axisY({ tickSize: 0, fontSize: 14 }),
Plot.axisX({ tickSize: 0, fontSize: 15 }),
Plot.text(['Design: Deepsha Menghani | Twitter: Bigdatadipper | Data: Tidy Tuesday'], {y:.05, dx: 460, fontSize: 12, fill: "gray", textAnchor: "end", fontStyle: "oblique"}),
],
color: {
type: "categorical", range: ["forestgreen", "maroon"], domain: ["organic", "conventional"], legend: false,
style: {
fontSize: "20px",
}
},
width: 1000, height: 500
})
addTooltips(Plot.plot({
marginTop: 25,
insetBottom: 10,
projection: "equirectangular",
marks: [Plot.sphere({fill: "black"}),
Plot.geo(land, {fill: "black", opacity: .8, stroke: "gray"}),
Plot.dot(renewable, {x: "longitude", y: "latitude", r: "renewable_perc", fill: "renewable_perc", opacity: .6, title: d=>d.name+" \n"+d.renewable_perc_char, filter: d=> d.Year === 2020}),
Plot.dot(renewable, {x: "longitude", y: "latitude", r: "renewable_perc", fill: "renewable_perc", opacity: .5, title: d=>d.name+" \n"+d.renewable_perc_char, filter: d=>d.renewable_perc>50 & d.Year === 2020}),
Plot.density(renewable, {x: "longitude", y: "latitude", bandwidth: 3, thresholds: 20, stroke: "white", fill: "renewable_perc", fillOpacity: 0.25, mixBlendMode: "multiply", weight: "renewable_perc", title: d=>d.name+" \n"+d.renewable_perc_char}),
Plot.text(['% of primary energy that comes from renewables (2020)'],{x:30, y: 88, dy: -60, fontSize: 25, fill: "black", opacity: 1, lineHeight: 1.2}),
Plot.text(['Data source: Ourworldindata.org, Design: Deepsha Menghani'],{x:40, y: -85, fontSize: 10, fill: "gray", opacity: 1, lineHeight: 1.2 }),
],
width: 1000,
r: { range: [5, 20]},
color: {type: "sequential", label: "", legend: true, scheme: "ylgnbu", style: {fontSize: 20}}
}), {fill: d => d.n, stroke: "gray", "stroke-width": 1}
)
Plot.plot({
inset: 40,
projection: "Equal-Earth",
width,
marks: [
Plot.geo(land, {fill: "gray", opacity: .3, stroke: "black"}),
Plot.geo(land, {opacity: .9, stroke: "black"}),
Plot.graticule(),
Plot.dot(renewable, {x: "longitude", y: "latitude", r: "renewable_perc", fill: "renewable_perc", opacity: 1, title: d=>d.name+" \n"+d.renewable_perc_char, filter: d=> d.Year === 2020}),
Plot.dot(renewable, {x: "longitude", y: "latitude", r: "renewable_perc", fill: "renewable_perc", opacity: 1, title: d=>d.name+" \n"+d.renewable_perc_char, filter: d=>d.renewable_perc>50 & d.Year === 2020}),
Plot.text(['Data source: Our World In Data, Design: Deepsha Menghani'],{x:70, y: -80, fontSize: 10, fill: "black", opacity: 1, lineHeight: 1.2 }),
//Plot.density(renewable, {x: "longitude", y: "latitude", bandwidth: 3, thresholds: 20, stroke: "renewable_perc", fill: "renewable_perc", fillOpacity: 0.25, mixBlendMode: "multiply", weight: "renewable_perc", title: d=>d.name+" \n"+d.renewable_perc_char}),
Plot.sphere()
],
r: { range: [5, 20]},
color: {legend:true, scheme: "ylgnbu", label: "What percentage of our primary energy comes from renewables? (2020)", style: {fontSize: 30}}
})
addTooltips(Plot.plot({
marginLeft: 100,
insetLeft: 200,
marginTop: 150,
marginBottom: 10,
marginRight: 200,
marks: [Plot.image(amtrak,{y: 0, x:0, dy:-100, dx: -180, width: 300, opacity: .003, src: "https://blog.amtrak.com/wp-content/uploads/2013/10/amtrak-011-e1437095759125.jpg"}),
Plot.text(['🚄'],{y: 2, x:0, textAnchor: "start", fontSize: 800, dy:0, dx: -550, }),
Plot.text(['⬜️'],{y: 2, x:0, textAnchor: "start", fontSize: 690, dy:-50, dx: -127, opacity: 1 }),
Plot.text(['Number of Amtrak stations in the United States'],{y: 0, x:0, fontSize: 30, dy:-150, dx: 350, lineWidth: 25, lineHeight: 1.3, fontStyle: "normal", fontFamily: "Menlo", fontWeight: "bold", opacity: 0.7}),
Plot.text(['Design: Deepsha Menghani Twitter: BigDataDipper Source: DataWorld'],{y: 3, x:0, fontSize: 12, dy:127, dx: 550, lineWidth: 15, lineHeight: 1.3, fontStyle: "oblique", fontFamily: "Menlo", opacity: 0.5}),
Plot.cell(
amtrak,
Plot.stackX({
y: (_, i) => i % 5,
fill: "n",
title: d=>d.state + "\n" + d.n + "\n" ,
opacity: 0.3,
dy: -50
})
),
Plot.text(
amtrak,
Plot.stackX({
y: (_, i) => i % 5,
text: "emoji5",
fontSize: d=>20 + d.n*.2,
title: d=>d.state + "\n" + d.n + "\n",
dy: -50
})
),
Plot.text(
amtrak,
Plot.stackX({
y: (_, i) => i % 5,
text: "stateabb",
fontSize: 20,
dy: -10,
title: d=>d.state + "\n" + d.n + "\n"
})
),
Plot.axisX({ tickSize: 0, fontSize: 0 }),
],
x: { axis: null },
y: { axis: null },
height: 700,
width: 1200,
}), {fill: d => d.n, stroke: "black", "stroke-width": 4}
)
addTooltips(Plot.plot({
marginTop: 25,
insetBottom: 10,
projection: "Equal-Earth",
marks: [Plot.sphere({fill: "white"}),
Plot.geo(countries, {fill: "gray", opacity: .3, stroke: "white"}),
Plot.geo(countries, {fill: (d)=> labor_2020.get(d.properties.name), opacity: 1, stroke: "white",
title: (d)=> d.properties.name + "\n" + Math.round(labor_2020.get(d.properties.name))+"%"
}),
Plot.text(['Ratio of female to male labor force participation rate (%)'],{x:80, y: 100, dy: -60, fontSize: 30, fill: "black", opacity: 1, lineHeight: 1.2}),
Plot.text(['Data source: data.worldbank.org, Design: Deepsha Menghani'],{x:70, y: -77, fontSize: 10, fill: "black", opacity: 1, lineHeight: 1.2 }),
],
width: 1000,
r: { range: [5, 20]},
color: {type: "sequential", legend: true, scheme: "blues", style: {fontSize: 20}}
}), {fill: d => d.n, stroke: "gray", "stroke-width": 1}
)
femaletomalelabor.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
labor = (await FileAttachment("femaletomalelabor.csv").csv()).map(d => ({name: rename.get(d.country) || d.country, Year2022: +d.Year2022}))
rename = new Map([
["Antigua and Barbuda", "Antigua and Barb."],
["Bolivia (Plurinational State of)", "Bolivia"],
["Bosnia and Herzegovina", "Bosnia and Herz."],
["Brunei Darussalam", "Brunei"],
["Central African Republic", "Central African Rep."],
["Cook Islands", "Cook Is."],
["Democratic People's Republic of Korea", "North Korea"],
["Democratic Republic of the Congo", "Dem. Rep. Congo"],
["Dominican Republic", "Dominican Rep."],
["Equatorial Guinea", "Eq. Guinea"],
["Iran (Islamic Republic of)", "Iran"],
["Lao People's Democratic Republic", "Laos"],
["Marshall Islands", "Marshall Is."],
["Micronesia (Federated States of)", "Micronesia"],
["Republic of Korea", "South Korea"],
["Republic of Moldova", "Moldova"],
["Russian Federation", "Russia"],
["Saint Kitts and Nevis", "St. Kitts and Nevis"],
["Saint Vincent and the Grenadines", "St. Vin. and Gren."],
["Sao Tome and Principe", "São Tomé and Principe"],
["Solomon Islands", "Solomon Is."],
["South Sudan", "S. Sudan"],
["Swaziland", "eSwatini"],
["Syrian Arab Republic", "Syria"],
["The former Yugoslav Republic of Macedonia", "Macedonia"],
["United States", "United States of America"],
// ["Tuvalu", ?],
["United Republic of Tanzania", "Tanzania"],
["Venezuela (Bolivarian Republic of)", "Venezuela"],
["Viet Nam", "Vietnam"]
])
world = FileAttachment("countries-50m.json").json()
countries = topojson.feature(world, world.objects.countries)
labor_2020 = new Map(labor.map(({name, Year2022}) => [name, Year2022]))
amtrack.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
import {addTooltips} from "@mkfreeman/plot-tooltip"
land50m = FileAttachment("land-50m@1.json").json()
land = topojson.feature(land50m, land50m.objects.land)
volcanoes_1950@1.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
mmr_world_2016.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
renewable_energyperc_country@1.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
avocado.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
avocado
beer_bear_correlation.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.