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An empty string is data in R, like an integer value of 0. As the update join modifies the data object, a fresh copy is used for each benchmark run. Similar questions do not seem to have tidy solutions.
You could just create a full look-up table and do a merge left join? Picking up Alistaire’s and Nettle’s suggestions and transforming into a working solution.
CA California 6: Tidyverse solution answer much preferred. AR Arkansas 5: AK Alaska 3: Sign up using Facebook.
Does the coalesce approach only work with NA and not other kinds of missingness like empty strings? Sign up using Email and Password. CO Colorado 7: Nettle 6 However, update joins are already available with the data.
The basic functionality is built defined in coalescethough, which can be applied programmatically if you don’t want to specify lots of column names. There’s currently no one-shot for trying to coalesce more than one column which can be done by using a lookup table approach within ifelse is.
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AR 604-5 Clearance of Personnel for Access to Classified Defense Information and Material
CT Connecticut 8: The OP has stated to prefer a “tidyverse” solution. AL Alabama 2: DE Delaware 9: Email Required, but never shown.