Tidyverse in R - tips & tricks

🔔 Subscribe for weekly R videos:    / @tomhenry-datasciencewithr6047   Here are 18 ways to speed up data cleaning, tidying, and exploration with the tidyverse packages in R. They'll help you to work with data more efficiently, simplify your R code, and surprise your friends!! 🎉 Enjoyed this video? Leave a comment below to share what you liked the most! 0:00 Intro 1:04 Create new columns in a count or group_by 2:11 Sample and randomly shuffle data with slice_sample() 3:05 Create a date column specifying year, month, and day 3:25 Parse numbers with parse_number() 4:07 Select columns with starts_with, ends_with, etc. 4:56 case_when to create or change a column when conditions are met 6:36 str_replace_all to find and replace multiple options at once 7:15 Transmute to create or change columns and keep only those columns 7:48 Use pipes everywhere including inside mutates 9:11 Filter groups without making a new column 10:04 Split a string into columns based on a regular expression 11:10 semi_join to pick only rows from the first table which are matched in the second table 12:20 anti_join to pick only rows from the first table which are NOT matched in the second table 12:48 fct_reorder to sort bar charts 14:06 coord_flip to display counts more beautifully 14:32 fct_lump to lump some factor levels into "Other" 15:26 Generate all combinations using crossing 16:00 Create functions that take column names with double curly braces 18:00 The end Code: https://gist.github.com/larsentom/727... #rstats #rstudio #datascience #tidyverse