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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
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

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Uploading a CSV

In many types of analytical work, data is available in CSV or Excel files and not in a database. You can use the Upload a CSV feature to upload CSVs as tables in Superset, without parent database integration.

We will get some real data to test this. Let's download the Ethereum transaction history from http://etherscan.io and create a new table:

curl https://etherscan.io/chart/tx?output=csv > /tmp/eth_txn.csv
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 35279 0 35279 0 0 98k 0 --:--:-- --:--:-- --:--:-- 98k

# create a sqlite database to store the csv
cd ~/.superset
# this will create a sqlite database, quit after it opens the console
sqlite3 upload_csv.db
Edit Database details form

Once you have created the upload_csv database integration, make sure you select it when you are uploading the .csv file, as shown in the following screenshot:

Load CSV form
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Apache Superset Quick Start Guide
Published in: Dec 2018Publisher: ISBN-13: 9781788992244
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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