In Python, how to convert this dataframe structure

[['US'], ['CA'], ['GB'], ['FR'], ['AU']] 

So that the double nested brackets are removed:

['US', 'CA', 'GB', 'FR', 'AU'] 

Here's a bit of context. I have a df with customer and country data. I want to count the countries so can find the top5 countries, and them use that as a filter elsewhere.

this gives me the counts

countries = collections.Counter(responses_2021['country'].dropna())

that yields this

[('US', 144), ('CA', 37), ('GB', 15), ('FR', 15), ('AU', 12)]

and this gives me the top 5

countries_top5 = countries.most_common(5)

now I need to transform it into a more simple structure so I can do my filter (here i'm just typing it manually because that's the only way I could move forward lol)

options = ['US', 'CA', 'GB', 'FR', 'AU'] 
rslt_df = df[df['country'].isin(options)] 

SO to get from the this

[('US', 144), ('CA', 37), ('GB', 15), ('FR', 15), ('AU', 12)]

to this

['US', 'CA', 'GB', 'FR', 'AU'] 

I started by trying to remove the counts

countries_top5_names = np.delete(countries_top5, 1, 1)

but that yields

[['US'], ['CA'], ['GB'], ['FR'], ['AU']] 

so now I'm trying to flatten that, but I don't know how.

You can try this,

variable = [['US'], ['CA'], ['GB'], ['FR'], ['AU']] 
new_var = list(map(lambda x: x[0], variable))
print(new_var)