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Sandraviz
Olá! My name is Sandra and I work with Dataviz in beautiful Lisbon 🙋🏼‍♀️ I'm a visual analyst and researcher with a passion for data storytelling and statistics to uncover patterns in human behaviour and societies 💞
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Edited
Jan 23
Fork of SPOTIFY | YEARS ARQUERO.JS
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D3.JS COURSE | 30 DAYS
30 Days of D3 DatavizINTRO TO D3.JSINTRO TO OBSERVABLEINTRO TO HTML, SVG & CSSINTRO TO JAVASCRIPTd3.select.append( )VENN DIAGRAMd3.select.data( )d3.csv( )SPOTIFY | ARTIST | SIMPLE CHARTHISTOGRAMAIRBNB BERLIN | DATADATA SOURCESd3.scale( )SIMEPLE SCALINGSCALED CIRCLES70s CAR BUBBLE CHARTTHE POWER OF SCALEd3.axis( )BARCODE PLOTSCATTER PLOT WITH AXESSPOTIFY | ARTISTS | D3.JS | Step 11. ASSIGNMENTTHREATENED SPECIES | BIRDS 2020d3.transition( )SIMPLE TRANSITIONHTML BUTTONSVISUAL ENCODING BUTTON | HTMLTHREATENED SPECIES - BIRDS 2020 ANIMATEDANIMATED COLORSPOTIFY | ARTISTS | D3.JS | Step 2ANIMATED SCATTER PLOTd3.tip( )SPOTIFY | ARTISTS | D3.js | Step 3d3.hexbinFROM SCATTER TO HEXBINSPOTIFY | GENRESSPOTIFY | YEARS ARQUERO.JS
THE UNWELCOMED ARQUERO.JS
INTRO TO ARQUERO.JSGLOBAL TEMPERATURE TRENDS, 1880-2022 ARQUERO.JSGLOBAL TEMPERATURE MONTHLY, 1880-2022 D3.JSUSA GAS PRICE 2000-22SPOTIFY | ARTISTS ARQUERO.JSd3.line( )d3.area( )INTERACTIVE TIMEFRAMEGLOBAL TEMPERATURES ANOMALIESANIMATED LINE CHARTCSS PATH ANIMATIONANIMATED LINECOVID | MOBILITY DATA ON CITIESGLOBAL TEMPERATURES DAILY 1979 - 2024 | D3.JSCONSUMPTION EMISSION2. ASSIGNMENT
Also listed in…
Arquero.js
Visualización dinamica 2023
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data = aq.loadCSV(
"https://raw.githubusercontent.com/mohamadwaked/classico/master/p0017_dataset.csv"
)
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data.view(5)
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data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.view(5)
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data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.select(0, 1, 2, 3, 4, 6, 7, 9, 13, 15)
.view(5)
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data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.select(0, 1, 2, 3, 4, 6, 7, 9, 13, 15)
.orderby(aq.desc("missing"))
.view(25)
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data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.select(0, 1, 2, 3, 4, 6, 7, 9, 13, 15)
.orderby("missing")
.view(10)
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data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.filter((d) => d.missing > 0)
.select(0, 1, 2, 3, 4, 6, 7, 9, 13, 15)
.orderby("missing")
.view(5)
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refugee_filtered = data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.filter((d) => d.missing > 0)
.select(0, 1, 2, 3, 4, 6, 7, 9, 13, 15)
.orderby("missing")
.objects()
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region = data
.rename({
total_death_missing: "missing",
cause_of_death: "cause",
collapsed_cause: "cause_new",
collapsed_region: "region_new"
})
.filter((d) => d.missing > 0)
.groupby("region_new")
.rollup({
mean_missing: (d) => op.mean(d.missing),
sum_missing: (d) => op.sum(d.missing),
count: op.count()
})
.filter((d) => d.count > 0)
.orderby(aq.desc("mean_missing"))
.objects()
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