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Learning Jupyter 5

You're reading from   Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789137408
Length 282 pages
Edition 2nd 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 (14) Chapters Close

Preface 1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter Java Coding 6. Jupyter JavaScript Coding 7. Jupyter Scala 8. Jupyter and Big Data 9. Interactive Widgets 10. Sharing and Converting Jupyter Notebooks 11. Multiuser Jupyter Notebooks 12. What's Next? 13. Other Books You May Enjoy

Node.js stats-analysis package


The stats-analysis package has many of the common statistics that you may want to perform on your data. You will have to install this package using npm, as explained previously.

If we had a small set of people's temperatures to work with, we could get some of the statistics on the data readily by using this script:

const stats = require("stats-analysis"); 
 
var arr = [98, 98.6, 98.4, 98.8, 200, 120, 98.5]; 
 
//standard deviation 
var my_stddev = stats.stdev(arr).toFixed(2); 
 
//mean 
var my_mean = stats.mean(arr).toFixed(2); 
 
//median 
var my_median = stats.median(arr); 
 
//median absolute deviation 
var my_mad = stats.MAD(arr); 
 
// Get the index locations of the outliers in the data set 
var my_outliers = stats.indexOfOutliers(arr); 
 
// Remove the outliers 
var my_without_outliers = stats.filterOutliers(arr); 
 
//display our stats 
console.log("Raw data is ", arr); 
console.log("Standard Deviation is ", my_stddev); 
console.log("Mean is ", my_mean...
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