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You're reading from  Apache Superset Quick Start Guide

Product typeBook
Published inDec 2018
Reading LevelIntermediate
Publisher
ISBN-139781788992244
Edition1st Edition
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Shashank Shekhar
Shashank Shekhar
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Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar

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Chord diagrams

Using a directed network diagram, we were able to identify the nations that experienced a spike or dip in their imports from other nations in 2010. We also noticed the nations that imported the most in that visualization. How about we now ask the question: which country exported more than they imported in 2014? How much did they import or export? Let's say we already have a list of nations in which we are interested, and they happen to be China, Germany, India, Japan, the United Kingdom, and the United States.

We will use a chord diagram to do this. The filter conditions on the year 2014 and the list of trading nations in which we are interested can be specified in the Custom WHERE clause text field:

(exporter="United Kingdom" OR exporter="Japan" OR exporter="China" OR exporter="Germany" OR exporter="India"...
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Apache Superset Quick Start Guide
Published in: Dec 2018Publisher: ISBN-13: 9781788992244

Author (1)

author image
Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar