nDimensional
@nDimensional
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Statistics, Visualizations and a lot of Programming in R
Cottbus, Germany
Joined April 2010
Die Filterblase ist wohl doch eher in den Köpfen der Leute, als in den Algorithmen von Facebook und Twitter, zeigt diese Datenanalyse:
spiegel.de
Filterblasen sind offenbar durchlässiger als gedacht. Im Interview erklärt der Datenjournalist Michael Kreil, warum sie Nutzer wohl doch nicht von anderen Meinungen abschotten - und eher bestehende...
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Electricity, fridges, radio, color TV, cars, computers, smartphones One century perspective on how technology entered American households: https://t.co/AwDdOck5VS
ourworldindata.org
An interactive visualization from Our World in Data.
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Suche D3 Entwickler für DataViz mit Autoaktualisierung + Dashboard mit Metrics Raum Berlin-Brandenburg
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Brilliant atmosphere simulation by @NASA: carbon (green), dust (red-orange), sulfates (white), and sea salt (blue)
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The most common causes of death in the US -- by age, gender and race https://t.co/MxOxJCeCDr via @flowingdata
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How the world's population has changed and where it's going https://t.co/XpsWh5VRDd
#dataviz
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Night lights change in the Middle East between 2012 and 2016 https://t.co/qOA4Z1iNBv via @NASAEarth
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There are huge differences between countries in how much governments reduce inequality through taxes and transfers https://t.co/GN2zo9G2bq
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Release ‘open’ data from their PDF prisons using tabulizer https://t.co/KJfhT2XXwB
#rstats #DataScience
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Nuance matters, but so does the wide-angle shot - how long we live & how much we spend on health https://t.co/YE8R08rSbg by @MaxCRoser
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Unabhängige Analysen von NOAA und NASA zeigen: 2016 war global wärmstes Jahr seit Beobachtungsbeginn. https://t.co/B2nh8gWj7s
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I often hear #coding was an essential #IT skill these days. This chart powerfully shows why! https://t.co/ZlPzTjZV8r
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Fascinating chart. How the French changed their mind about World War Two. https://t.co/91WQPFTeac
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"...it’s not enough to see the data, you need to make sense out of it. You need to understand the context."
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“Open-washing” - The difference between opening your data and simply making them available
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