converting countries to continents when there is more than one country per row

Question

I have a column with country where each row has more than one country listed. I want to convert each country to continent. In the past I have used country converter, but when I try to use it in this case, I get an error because there is more than one country per row.

How can I fix this?

!pip install country_converter --upgrade

import pandas as pd
import country_converter as coco
import pycountry_convert as pc

df = pd.DataFrame()
df['country']=['United States, Canada, England', 'United Kingdom, Spain, South Korea', 'Spain', 'France, Sweden']

# CONVERT COUNTRY TO ISO COUNTRY
cc = coco.CountryConverter()

# Create a list of country names for the dataframe
country = []
for name in df['country']:
    country.append(name)
    
# Converting country names to ISO 3    
iso_alpha = cc.convert(names = country, to='ISO3')

# CONVERT ISO COUNTRY TO CONTENENT
def country_to_continent(country_name):
    country_alpha2 = pc.country_name_to_country_alpha2(country_name)
    country_continent_code = pc.country_alpha2_to_continent_code(country_alpha2)
    country_continent_name = pc.convert_continent_code_to_continent_name(country_continent_code)
    return country_continent_name

# converting to contenents
contenent=[]
for iso in iso_alpha:
    try:
        country_name = iso
        contenent.append(country_to_continent(country_name))
    except:
        contenent.append('other')

# add contenents to original dataframe
df['Contenent']=contenent

Answer 1

Assuming I understood you correctly, you want the result back in the DataFrame. Therefore, each row would have multiple continents matching to the corresponding country.

If so, you'll need to split each row, and then split the string so that each country can be processed separately, then join back row by row before putting back into DataFrame.

A few things to note:

• "England" isn't found to be a country, so will be labeled as "other". If you use an IDE, the execution window will display a warning. I didn't try to fix this.
• CountryConverter's convert will return a string if it got only one country, so have to check for the return type.
• I moved the "def" up to the top, so main code is on the bottom.

Here is the code that works for me:

import pandas as pd
import country_converter as coco
import pycountry_convert as pc

# CONVERT ISO COUNTRY TO CONTENENT
def country_to_continent(country_name):
    country_alpha2 = pc.country_name_to_country_alpha2(country_name)
    country_continent_code = pc.country_alpha2_to_continent_code(country_alpha2)
    country_continent_name = pc.convert_continent_code_to_continent_name(country_continent_code)
    return country_continent_name


# ------ MAIN -------
df = pd.DataFrame()
df['country']=['United States, Canada, England', 'United Kingdom, Spain, South Korea', 'Spain', 'France, Sweden']

# CONVERT COUNTRY TO ISO COUNTRY
cc = coco.CountryConverter()

# Create a list of country names for the dataframe
cont_list=[]
for arow in df['country']:
    country = []
    arowarr = arow.split(", ")
    for aname in arowarr:
        country.append(aname)

    #print(f'org:{arow} split:{country}')
    # Converting country names to ISO 3    
    iso_alpha = cc.convert(names = country, to='ISO3')
    #print(f'iso_alpha:{iso_alpha} type:{type(iso_alpha)}')

    # converting to contenents
    contenent=[]
    if (type(iso_alpha) == type("")):
        try:
            #print(f'   iso_alpha:{iso_alpha}')
            contenent.append(country_to_continent(iso_alpha))
        except:
            contenent.append('other')
    else:
        for iso in iso_alpha:
            try:
                #print(f'   iso:{iso}')
                contenent.append(country_to_continent(iso))
            except:
                contenent.append('other')

    # convert array back to string
    str_cont = ', '.join(contenent)
    #print(f'str_cont:{str_cont}')
    cont_list.append(str_cont)

# add contenents to original dataframe
df['Contenent']=cont_list
print(f"DF Contenent: \n{df['Contenent']}")

Answer 2

With help from @Ignatius Reilly, I was able to figure this out.

I am still learning python, so splitting the string first was easy for me to understand. Since all the countries were separated by commas it worked without complication.

country_split=[]
for x in df['country']:
    country_split.append(x.split(','))

Then I realized that I could change cc.convert from 'ISO3' to 'Continent' so that really simplified the code.

the output contained duplicate continents for example, [America, America]. So I used .map(pd.unique) to remove the duplicate values.

the final code is:

!pip install country_converter --upgrade

import pandas as pd
import country_converter as coco

df = pd.DataFrame()
df['country']=['United States, Canada', 'United Kingdom, Spain, South Korea', 'Spain', 'France, Sweden']

# Create a list of country names from the dataframe
country_split=[]
for x in df['country']:
    country_split.append(x.split(','))

# Converting country names to contenent 
cc = coco.CountryConverter()
iso_alpha_list = [cc.convert(names=name, to='Continent') for name in country_split]

df['continent_split']= iso_alpha_list
df['continent']=df['continent_split'].map(pd.unique)