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Julia 1.0 Programming

You're reading from   Julia 1.0 Programming Dynamic and high-performance programming to build fast scientific applications

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Product type Paperback
Published in Sep 2018
Publisher
ISBN-13 9781788999090
Length 196 pages
Edition 2nd Edition
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Author (1):
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Ivo Balbaert Ivo Balbaert
Author Profile Icon Ivo Balbaert
Ivo Balbaert
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Table of Contents (12) Chapters Close

Preface 1. Installing the Julia Platform FREE CHAPTER 2. Variables, Types, and Operations 3. Functions 4. Control Flow 5. Collection Types 6. More on Types, Methods, and Modules 7. Metaprogramming in Julia 8. I/O, Networking, and Parallel Computing 9. Running External Programs 10. The Standard Library and Packages 11. Other Books You May Enjoy

Using Plots on data


Let's apply Plots to show a graph on the famous Iris flower data set, which can be found in the Rdatasets package (don't forget to first add this package). We also need the StatPlots package when visualizing DataFrames. It contains an @df macro, which makes this much easier. Here is the code to draw a scatter plot:

# code in Chapter 10\plots_iris.jl 
  using PyPlots, StatPlots, RDatasets 
  iris = dataset("datasets", "iris") 
  @df iris scatter(:SepalLength, :SepalWidth, group=:Species,m=(0.5,   
  [:+ :h :star7], 4), bg=RGB(1.0,1.0,1.0)) 

We plot the sepalwidth property against the sepallength of the flowers. In the preceding code, iris is the name of our DataFrame, which is passed as the first argument to the @df macro. We then call the scatter function to obtain the following plot:

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