I am working on a dataset which contains a column with common country names.

Task: To convert country name into standard ISO names

 I have written a basic function which converts country names into country codes using `pycountry` library.

    import pandas as pd
    import pycountry
    df = pd.DataFrame({"Country":["China","US","Iceland"])

    
    def do_fuzzy_search(country):
        try:
            result = pycountry.countries.search_fuzzy(country)
            return result[0].alpha_3
        except:
            return np.nan

    df["country_code"] = df["Country"].apply(lambda country: do_fuzzy_search(country))


But I am facing issues.Its taking too long. My dataset has 17003 rows,which is not even that large a number.

Firstly, suggestions on the code to improve its performance would be welcome.

Secondly, I would like to know if there is completely different way to do this faster.