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validate_address_usps(street = "140 N. Rolling Rd", city = "Springfield", state = "PA", username = username) Address2 City State Zip5 Zip4 1 140 N ROLLING RD SPRINGFIELD PA 19064 1413 2 NA NA NA NA NA 3 NA NA NA NA NA 4 NA NA NA NA NA 5 NA NA NA NA NA 6 140 N ROLLING RD SPRINGFIELD PA 19064 1413 7 140 N ROLLING RD SPRINGFIELD PA 19064 1413 8 140 N ROLLING RD SPRINGFIELD PA 19064 1413 9 NA NA NA NA NA 10 NA NA NA NA NA 11 140 N ROLLING RD SPRINGFIELD PA 19064 1413
This is an amazing package, but the output is odd. Here is just one address I tested, and it worked but this is how it returns the answer. I could only get it to work with one address. When mapping the output to a dataframe it just returned all NAs.
The text was updated successfully, but these errors were encountered:
validate_address_usps(street = "140 N. Rolling Rd", city = "Springfield", state = "PA", username = username) Address2 City State Zip5 Zip4 1 140 N ROLLING RD SPRINGFIELD PA 19064 1413 2 NA NA NA NA NA 3 NA NA NA NA NA 4 NA NA NA NA NA 5 NA NA NA NA NA 6 140 N ROLLING RD SPRINGFIELD PA 19064 1413 7 140 N ROLLING RD SPRINGFIELD PA 19064 1413 8 140 N ROLLING RD SPRINGFIELD PA 19064 1413 9 NA NA NA NA NA 10 NA NA NA NA NA 11 140 N ROLLING RD SPRINGFIELD PA 19064 1413
This is an amazing package, but the output is odd. Here is just one address I tested, and it worked but this is how it returns the answer. I could only get it to work with one address. When mapping the output to a dataframe it just returned all NAs.
The text was updated successfully, but these errors were encountered: