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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.

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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!

Email Required, but never shown. AK Alaska 3: By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. Similar questions do not seem to have tidy solutions. Sign up using Facebook.

Post Your Answer Discard By clicking “Post Your Answer”, you acknowledge that you have read our updated terms of serviceprivacy policy and cookie policyand that your continued use of the website is subject to these policies. For now, you can build it manually.

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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. Stack Overflow works best with JavaScript enabled. Does the coalesce approach only work with NA and not other kinds of missingness like empty strings?