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Sign up or log in Sign up using Google. An empty string is data in R, like an integer value of 0.
There’s currently no one-shot for trying to zr more than one column which can be done by using a lookup table approach within ifelse is. As the update join modifies the data object, a fresh copy is used for each benchmark run.
Nettle 6 CT Connecticut 8: This is such a common operation!
r – Update/Replace Values in Dataframe with Tidyverse Join – Stack Overflow
However, update joins are already available with the data. AL Alabama 2: This question marked as duplicate, though link does not go to tidy solution. Sign up using Facebook.
Created on by the reprex package v0. AK Alaska 3: DE Delaware 9: Post as a guest Name. You could just create a full look-up table and do a merge left join?
The basic functionality is built defined in coalescethough, which can be applied programmatically if you don’t want to specify lots of column names. FL Florida AZ Arizona 4: The OP has stated to prefer a “tidyverse” solution.
AR 604-5 Clearance of Personnel for Access to Classified Defense Information and Material
Tidyverse solution answer much preferred. Similar questions do not seem to have tidy solutions. If you’ve got a lot of columns, you can coalesce programmatically, or even put it in a function.