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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
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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

Making line plots


Line graphs are very used both at the academy and industry. Needless to say, economists are mad about line graphs, and for a good reason. They are an easy choice when it comes to demonstrating a progression (for example, time-progression) of some continuous variable, let's say macroeconomic indicators.

Non-interactive line plots can be drawn by ggplot2. If there is some need to update the graphic with considerable frequency, interactive ones are a better fit and they can be crafted by ggvis or plotly. Plots made with these packages rapidly respond to data changes.

For this recipe, we're going to draw line graphs about the evolution of foreign trade (as percentage of Gross Domestic Product) of Finland and West Germany between 1965 and 1990. Both countries had chosen different economic paths. Let's see check their economic paths once we make sure to meet the requirements.

Getting ready

Beforemoving on, we need to install the Zelig package in order to make data available. We also...

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