Summary

Let’s summarize what we’ve learned so far.

• The tidyverse: We looked at the tidyverse. The tidyverse has a lot of packages that work together beautifully, such as the dplyr and the ggplot2 packages.

• The dplyr package: We also learned about the dplyr package, which is useful for data wrangling and helps to elegantly and efficiently summarize and manipulate data.

• Gathering and spreading: We learned that the gather() and spread() functions are invaluable for manipulating data and allowing a switch between wide and long formats as needed.

• The do() function: We saw that the do() function allows us to combine the grouping aspects of the dplyr package with running functions on data, such as data analysis.

• The qplot() and ggplot() functions: We learned that the qplot() and ggplot() functions are excellent for creating professional figures. These functions give a near-total control over the figures, and there are practically infinite ways to customize the plots with them.

• Data wrangling along with plotting: Finally, we saw that combining data wrangling and plotting is a powerful technique to quickly transform raw data into summarized figures.