Book Image

Applied Data Visualization with R and ggplot2

By : Chris DallaVilla
Book Image

Applied Data Visualization with R and ggplot2

By: Chris DallaVilla

Overview of this book

Applied Data Visualization with R and ggplot2 introduces you to the world of data visualization by taking you through the basic features of ggplot2. To start with, you'll learn how to set up the R environment, followed by getting insights into the grammar of graphics and geometric objects before you explore the plotting techniques. You'll discover what layers, scales, coordinates, and themes are, and study how you can use them to transform your data into aesthetical graphs. Once you've grasped the basics, you'll move on to studying simple plots such as histograms and advanced plots such as superimposing and density plots. You'll also get to grips with plotting trends, correlations, and statistical summaries. By the end of this course, you'll have created data visualizations that will impress your clients. The github link for this title is here https://github.com/TrainingByPackt/Applied-Data-Visualization-with-R-and-ggplot2-eLearning
Table of Contents (3 chapters)
Chapter 3
Advanced Geoms and Statistics
Content Locked
Section 5
Trends, Correlations, and Statistical Summaries
Statistical summaries are useful for summarizing a group of points. You may want to see different quantities (such as the minimum, maximum, mean, median, or quantiles) for a time series plot or a line chart that includes multiple y values for a given x value. We will use the financial data from Facebook and the statistical summary tool to better understand the trends. Let us understand the following concepts: - Time Series Plot with Mean, Median, and Quantiles - Trends, Correlations, and Scatter Plots - Scatter Plot and Fitting a Linear Regression Model