CODEWITHSUNDEEP
pythonpandasdataframe
mtm1186
mtm1186

Reputation: 135

Mapping a dictionary with Continent: Country to a DataFrame with a Country Column

I have a dataframe with a column df['Country']. I have created a dictionary with all of the continents as keys and the values as a list of the corresponding countries.

continents = { "North America" : ["Canada","Mexico","United States"]}

I would like to map this to my dataframe where it creates a column with each value in df['Country'] corresponding continent.

I have tried the below but it returns a column of NA values

df['Continents'] = df['Country'].map(continents)

Do I need to create a function to map the continents or can I use the pandas .map() method?

Upvotes: 2

Views: 1428

Answers (1)

mozway
mozway

Reputation: 260640

You have the wrong format for your dictionary, you need the reverse (and no list).

You can use this to get the right format:

countries_map = {country: continent
                 for continent,countries in continents.items()
                 for country in countries}

output:

{'Canada': 'North America',
 'Mexico': 'North America',
 'United States': 'North America'}

Then proceed as:

df['Continents'] = df['Country'].map(countries_map)

Upvotes: 2

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