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Jupyter for Data Science

You're reading from   Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781785880070
Length 242 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (11) Chapters Close

Preface 1. Jupyter and Data Science FREE CHAPTER 2. Working with Analytical Data on Jupyter 3. Data Visualization and Prediction 4. Data Mining and SQL Queries 5. R with Jupyter 6. Data Wrangling 7. Jupyter Dashboards 8. Statistical Modeling 9. Machine Learning Using Jupyter 10. Optimizing Jupyter Notebooks

Building standalone dashboards


Using Node.js, developers have come up with a way to host your dashboard/notebook without Jupyter on jupyter-dashboard-server.

Installation requires installing Node.js (as the server is written in Node.js). This is a larger installation set.

Once you have Node.js installed, one of the tools installed is npm-node product manager. You can use npm to install the dashboard server with the following command:

npm install -g jupyter-dashboards-server

Once installed you can run the server with the following command:

C:\Users\Dan>jupyter-dashboards-server --KERNEL_GATEWAY_URL=http://my.gateway.com

mygateway.com is a dummy. You would use your gateway server (if needed). At this point the server is running on the environment you mentioned and will output a few lines:

Using generated SESSION_SECRET_TOKENJupyter dashboard server listening on 127.0.0.1:3000

You can open a browser to the URL (http://127.0.0.1:3000/dashboards) and see what the server console looks like:

As for developing...

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