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Learning Jupyter

You're reading from   Learning Jupyter Select, Share, Interact and Integrate with Jupyter Notebook

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884870
Length 238 pages
Edition 1st Edition
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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. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter JavaScript Coding 6. Interactive Widgets 7. Sharing and Converting Jupyter Notebooks 8. Multiuser Jupyter Notebooks 9. Jupyter Scala 10. Jupyter and Big Data

Standard Julia capabilities


Similar to functions in other languages, Julia can perform most of the rudimentary statistics on your data using the describe function, as in the example script that follows:

using RDatasets
describe(dataset("datasets", "iris"))

This script accesses the Iris dataset and displays summary statistics on the dataset.

If we were to build a notebook to show describe in use against the iris dataset (loaded in the previous example), we would end up with a display like this:

You can see the standard statistics generated for each of the variables in the dataset. I thought it was interesting that the count and percentage of NA values in the dataset are provided. I have found that I usually have to double-check to exclude this data using other languages. Here, it is a quick, built-in reminder.

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