More information about pipes (%>%)

[btskinner]

@edquant/team_class, here are some more resources on using pipes (%>%). Some are more technical than others, but they all may be useful:

• Aggregating and analyzing data with dplyr (Data Carpentry)
• Pipes (R for Data Science)
• Data Wrangling with Dplyr and Magrittr (U of Toronto Coders)

If you happen across one not on this list, feel free to link it below.