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R Data Visualization Recipes

You're reading from   R Data Visualization Recipes A cookbook with 65+ data visualization recipes for smarter decision-making

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Length 366 pages
Edition 1st Edition
Languages
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Author (1):
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Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
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Table of Contents (13) Chapters Close

Preface 1. Installation and Introduction FREE CHAPTER 2. Plotting Two Continuous Variables 3. Plotting a Discrete Predictor and a Continuous Response 4. Plotting One Variable 5. Making Other Bivariate Plots 6. Creating Maps 7. Faceting 8. Designing Three-Dimensional Plots 9. Using Theming Packages 10. Designing More Specialized Plots 11. Making Interactive Plots 12. Building Shiny Dashboards

Creating an histogram with custom colors and bins width


This recipe meant to introduce and explain several useful arguments available at geom_histogram(). To spice things up, a problem context based on the game of chances is adopted. It is an optimal scenario to explain how histogram features can work both to display Monte Carlo simulations and aid hypothesis decisions. Once this context is explained, extrapolating it to challenges of your own won't be difficult.

In order to keep the focus on what matters, let's elaborate a very simple paradigma, design a game, and simulate it over and over again. The game rules can be summarized as following:

  • Initial bet is fixed on $75
  • Player decides before hand the number of rounds he is going through
  • For each round, a fair coin is tossed (fifty-fifty chance for each outcome)
  • Tail means current balance (positive or negative) is increased by 20 percent
  • Head subtracts 17 bucks from the current balance

Our player wants to have visual aid from a histogram. He wants...

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