I'm trying to clean a customer dataset that looks like the customers
df below. This dataset has many City names spelled incorrectly. I also have another df (Australian_Postcodes ) with the correct spelling of city names in the place_name column. I'm wondering how I update the incorrectly spelled city names in my customers
df based on the correctly spelled names in the Australian_Postcodes
df.
Many thanks for your help.
customers <- data.frame(
Name = c("customer1", "customer2", "customer3", "customer4", "customer5", "customer6", "customer7",
"customer8", "customer9"),
Address = c("address1", "address2", "address3", "address4", "address5","address6","address7",
"address8","address9"),
City = c("Port Norlunga", "Essendn", "Seaford Heigh", "Salisbury","Briar Hill","Elizabeth sa", "WARRADALE SA 5046",
"Parlawie","M|Vale"),
State = c("SA", "VIC", "SA", "SA","VIC","SA","SA","SA","SA"),
Postcode = c(NA,"3040", "5169", "5108",NA, "5000","5043", "5046",NA)
)
Australian_Postcodes <- data.frame(
place_name = c("Port Noarlunga","Essendon","Seaford Heights", "Salisbury","Briar Hill","Elizabeth", "Warradale",
"Paralowie", "Morphett Vale"),
post_code = c("5167","3040", "5169", "5108","3088", "5108","5043","5108","5162"),
State = c("SA", "VIC", "SA", "SA","VIC","SA","SA","SA","SA")
)
Created on 2021-03-08 by the reprex package (v0.3.0)