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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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Author (1)
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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Arcs

After taking a close look at airports in South-East Asia, let's take a view of global flight routes. We saw that there are many airports almost everywhere on the world map. There will be exponentially more flight routes. So, to get a view of flight routes that we can comprehend and summarize while looking at one chart, we filter for flight routes that start from the city of Tehran, in Iran:

Setting the parameters for flight routes across Asia

You can select Fixed Color and Stroke Width to change the aesthetics of the Arc map. We can see that Iran in 2017 has only one international flight route, to Saudi Arabia:

The flight routes in Asia (the other place names are not important)

We will now use the Map Style feature of the Arc chart to use satellite images. This time, we select one of the largest cities in the world, and one that is mentioned in the chronicles—...

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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