Learning objectives Review the major types of vectors Demonstrate how to subset vectors Demonstrate vector recycling Define lists Demonstrate iterative operations using loops and map() functions Practice writing iterative operations using loops and map() functions Notes

Learning objectives Demonstrate how to use the pipe Demonstrate piping alternatives Define functions and their purpose Analyze a user-written function and explain how it works Demonstrate conditional execution Practice writing functions Notes

Learning objectives Introduce relational data Demonstrate how tables can be linked to one another Demonstrate methods in dplyr for linking and merging related tables Practice joining tables Define factors Demonstrate how to transform and reorder factors for visualizations Practice transforming factors

Learning objectives Define a tibble Demonstrate how vectors can be read and parsed Define various data file formats and functions for importation Define tidy data and its characteristics Practice tidying data Notes The purpose of this lecture is to learn how we import/arrange data that we want to work with in R. Typically, stats classes focus on doing actual stats so you don't get "real" data. Real data isn't necessarily the prettiest thing, so in this lecture, we'll teach you how to import and clean real data!

Learning objectives Define exploratory data analysis (EDA) and types of pattern exploration Demonstrate types of graphs useful for EDA and precautions when interpreting them Practice exploring data Approaches to EDA Look for variation and covariation Don't need to have pretty charts (for publishing purposes, you want to add titles, legends, themes etc.)

Learning objectives Identify computer programming as a form of problem solving Practice decomposing an analytical goal into a set of discrete, computational tasks Identify the verbs for a language of data manipulation Clarify confusing aspects of data transformation from R for Data Science Practice transforming data Diamonds Example(s)

Learning objectives Identify the importance of graphics in communicating information Define the layered grammar of graphics Demonstrate how to use layered grammar of graphics to build Minard's graph of Napoleon's invasion of Russia Practice generating layered graphics using ggplot2 April 8, 2020 Lecture Notes

Learning objectives Introduce myself Identify major course objectives Identify course logistics Introduce basic principles of data science workflow and programming Explain how to get started in R Monday, April 6, 2020

You can take notes using Markdown format. See this list Another item in the list Look at this code formatting ggplot(data = mtcars) + geom_point(mapping = aes(x = cyl))