Pipes

Rebecca Barter

Entering the tidyverse Piping: %>% Data manipulation: dplyr select: select columns filter: filter to rows that satisfy certain conditions mutate: add a new variable arrange: arrange the rows of the data frame in order a variable group_by: apply other dplyr functions separately within within a group defined by one or more variables summarise/summarize: define a variable that is a summary of other variables More dplyr functions Visualization: ggplot2 Adding geom layers More aesthetic mappings based on variables Other types of layers Histograms Boxplots Faceting Customizing ggplot2 Most people who learned R before the tidyverse have likely started to feel a nibble of pressure to get aboard the tidyverse train.