You realize you are using the right document editor when such a simple job as Unite columns record does not take more time than it should. Editing documents is now a part of a lot of working operations in numerous professional areas, which is the reason accessibility and efficiency are crucial for editing resources. If you find yourself studying guides or searching for tips about how to Unite columns record, you may want to get a more easy-to-use solution to save time on theoretical learning. And here is where DocHub shines. No training is required. Simply open the editor, which will guide you through its principal functions and features.
A workflow becomes smoother with DocHub. Use this instrument to complete the files you need in short time and get your productivity to a higher level!
in the deep liar library you can take an existing character column and turn it into two or more new columns using the separate function so were just going to show how to do that in this video first were going to create some data some fake date data here to separate now you can see we made a data frame but it only has one column called dates and we can use separate to turn these dates into three different columns for the month day and year so to do that were gonna take the data well pipe it to separate this first argument here is just the name of the column you want to do separate on in this case we only made one column so thats what were gonna pass in the next argument is a vector of the new column names you want to create were gonna create three new columns month day and year and then the last argument here SEP is just the separator that you want to split the string on to make the new columns in this case the dates are separated using the slash character so thats what were pa