R for Data Analysis is a course that will introduce you to data manipulation in R programming. You will learn about manipulating data and grouping it to prepare the data. You will also learn how to take data you prepared and present it on visualizations.
The course begins by introducing you to data manipulation. You will learn what data manipulation is and about packages or library you need to add to your program for data manipulation. You will be introduced to the difference between feature and observation manipulation. You will learn about grouping and how that can organize your data output.
Next, you will be introduced to the two different types data visualization. You will learn about the grammar of graphics, about different graphing techniques and charting libraries you will need for visualizations. The course also teaches about setting the colours and organizing your data in the visualizations.
This course will be of great interest to professionals working in the areas of data science and data analysis and who want to learn more about using R for statistical computing.
Prerequisites: The learner will need the have completed the previous course in Introduction to R for Data Science. The learner will need some knowledge of programming languages.
On completing this course, you will be able to: - List libraries/packages you will need to include in your program for data manipulation. - Discuss the process of features and observation manipulation. - Describe how the forward pipe operator helps cleans up and organize your code. - Explain what data visualization is and the difference between its two types. - List libraries you will need to include in your r program to create visualizations. - Describe how to display your data on a visualization.
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