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You're reading from  Apache Superset Quick Start Guide

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Published inDec 2018
Reading LevelIntermediate
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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.
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Partitioning

We can visualize how much nations in a particular geographical region import from other regions in a different way, using partition diagrams called TreeMaps. We will create a filter to select records for Asian (excluding Near East) nations. The first partitions will be proportional to the total import trade volume of each Asian nation. Then, each nation's partition will be further partitioned to show how much and in what proportions the nation imports from different geographical regions.

The nations controlling the largest area in the first partition will be the nations dominating the import market in Asia (excluding the Near East). The larger partitions inside each nation will represent the export market that supplies most of the merchandise goods to the corresponding Asian nation:

Setting parameters for the partition graph to display Asian nations imports...
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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