Faster way of replacing strings in large pandas dataframe with regex
There is not much to say about your code then, Regex is slow.

A non-regex solution could be to use Python's endswidth, this works the same as r"road$"

mergedAllCrimes.crime_location_approx = mergedAllCrimes.crime_location_approx.apply(lambda x: 'road' if x.lower().endswith('road') else x)


I'm assuming all the conditional words are at the end of the string