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CA California 6: If you’ve got 640-5 lot of columns, you can coalesce programmatically, or even put it in a function. The OP has stated to prefer a “tidyverse” solution. An empty string is data in R, like an integer value of 0.
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Nettle 6 FL Florida Created on by the reprex package 6004-5. Tidyverse solution answer much preferred. Picking up Alistaire’s and Nettle’s suggestions and transforming into a working solution. CT Connecticut 8: CO Colorado 7: If the lookup table is more than two columns, it’s an update join, which doesn’t exist in dplyr for now.
AZ Arizona 4: You could just create a full look-up table and do a merge left join? AR Arkansas 5: However, update joins are already available with the data. Post as a guest Name. Sign up using Email and Password. DE Delaware 9: This question marked as duplicate, though link does not go to tidy solution.
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As the update join modifies the data object, a fresh copy is used for each benchmark run. AL Alabama 2: This is such a common operation!
The basic functionality is built defined in coalescethough, which can be applied programmatically if you don’t want to specify lots of column names.