This is a fast-paced, practical course aimed at experienced developers and system architects. As you progress, you'll find helpful tips and tricks, as well as useful self-assessment material, exercises, and activities to help you benchmark your progress and reinforce what you've learned. The activities have been devised to simulate real-world conditions in order to equip you with the necessary skills to accelerate software deployment while still maintaining security, portability, and affordability.
TARGET AUDIENCE:
This course is meant for professionals who work with data and use R as part of their workflow. It also targets students who want to extend and enhance their data analysis skills by adding complex, informative, and professional visualizations. This course will not cover the basics of R commands and objects, so students are expected to have some familiarity with the R language.
COURSE PREREQUISITES:
Hardware:
For successful completion of this course, students will require computer systems with the following:
• Processor: Intel Core i5 or equivalent
• Memory: 4 GB RAM
• Storage: 35 GB available space
Software:
• Operating System: Windows 7 SP1 64-bit, Windows 8.1 64-bit, or Windows 10 64-bit
• Browser: Google Chrome (latest version)
• R (latest version)
• RStudio (latest version)
COURSE CONTENT:
LESSON 1- BASIC PLOTTING IN GGPLOT2
• Introduction to ggplot2
• Geometric Objects
• The Grammar of Graphics
LESSON 2- THE GRAMMAR OF GRAPHICS AND VISUAL COMPONENTS
• More on the Grammar of Graphics
• Facets
• Changing Styles and Colors
• Geoms and Statistical Summaries
LESSON 3- ADVANCED GEOMS AND STATISTICS
• Advanced Plotting Techniques
• Time Series
• Maps
• Trends, Correlations, and Statistical Summaries
COURSE OBJECTIVE:
If you are interested in gaining a good grasp of ggplot2 in a systematic and practical way by working through real-world scenarios, then this course is for you.
This course will provide you with knowledge of the following:
• Illustrating continuous integration and continuous delivery concepts
• Setting up the R environment, R Studio, and explaining the structure of ggplot2
• Distinguishing between types of variables and best practices for visualizing them
• Changing the defaults of visualizations to reveal more information about the data
• Implementing the “Grammar of Graphics” in ggplot2, such as scales, coordinate systems, position adjustments, and faceting
• Creating complex visualizations and investigating the correlations between variables
• Designing and implementing a visualization from scratch
FOLLOW ON COURSES:
Not available. Please contact.