Hi David, welcome!
You can use the tidystringdist package, take a look at this similar thread.
This would be one way to do it
library(tidystringdist)
library(tidyverse)
# Sample data
df <- data.frame(stringsAsFactors = FALSE,
Name = as.factor(c(" CANON PVT. LTD ", " Antila,Thomas ", " Greg ",
" St.Luke's Hospital ", " Z_SANDSTONE COOLING LTD ",
" St.Luke's Hospital ", " CANON PVT. LTD. ",
" SANDSTONE COOLING LTD ", " Greg ", " ANTILA,THOMAS ")),
City = as.factor(c(" Georgia ", " Georgia ", " Georgia ", " Georgia ",
" Georgia ", " Georgia ", " Georgia ", " Georgia ",
" Georgia ", " Georgia "))
)
match <- df %>%
tidy_comb_all(Name) %>%
tidy_stringdist() %>%
filter(so…
If you need more specific help please provide a minimal REPR oducible EX ample (reprex)
If you've never heard of a reprex before, you might want to start by reading this FAQ:
A minimal reproducible example consists of the following items:
A minimal dataset, necessary to reproduce the issue
The minimal runnable code necessary to reproduce the issue, which can be run
on the given dataset, and including the necessary information on the used packages.
Let's quickly go over each one of these with examples: