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In this dataviz project I had several objectives and motivations. On the one hand I showcase how to handle a big dataset and making use of it in a well designed scatter plot. Moreover as everything is becoming dynamic these days I explain how to move from static to dynamic visualisation in 3 steps, first adding an animation using the beautiful d3.transition and secondly add some interactivity in the form of a tooltip using the library d3.tip.

Last but not least I want to give an example of how to "read" data visualisation detecting relevant patterns and adequately interpret them. In this video, I explain all this in just 10 min 😎

Scatter 2.png


In this example we have around 30.000 data points. You might think this is a  big dataset or not , but what matters is how can we help detecting patterns when plotting lots of data points in a small visual space. In terms of style we can reduce size to a minimum and use high transparency. The small size leads to less overlap and the transparency creates on heatmap effect as when points overlay the color gets darker due the transparency. Thanks to these style choice we can for example easily detect the positive relationship between the music attributes valence and danceability. 

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