Map keys to values in pandas Python

Question

I have this dictionary which I scraped from Wikipedia. The dictionary contains continents and their respective countries. For example:

theWorld = {'Asia': ['China', 'Malaysia'.. etc], 'Europe': ['Germany', 'Italy' ..etc]}

I am trying to make a dataframe using pandas to map a country to its continent. For example:

Country   Continent
China     Asia
Malaysia  Asia 
Germany   Europe
Ghana     Africa

and so on and so fort.

Dani Mesejo · Accepted Answer · 2020-11-17 21:04:40Z

1

You could use a list comprehension to create the rows of the DataFrame:

import pandas as pd

theWorld = {'Asia': ['China', 'Malaysia'], 'Europe': ['Germany', 'Italy']}

df = pd.DataFrame(data=[[v, k] for k, vs in theWorld.items() for v in vs], columns=['country', 'continent'])
print(df)

Output

    country continent
0     China      Asia
1  Malaysia      Asia
2   Germany    Europe
3     Italy    Europe

Additional resources:

DataFrame data structure, here
When to use a list comprehension, here

edited Nov 17, 2020 at 21:04

answered Nov 17, 2020 at 20:50

Dani Mesejo

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4 Comments

Ozeus Over a year ago

thank you, that solved my problem. Would you be so kind to tell me what kind of reference I should look into for the solution you provided.

Ozeus Over a year ago

I don't understand list comprehension yet but I converted to normal loop and I kind of understood what you did exactly so thank you again. data= [] for k, vs in theWorld.items(): for v in vs: data.append([v,k]) print(data)

Dani Mesejo Over a year ago

@Ozeus I linked some resources to list comprehensions, hope it helps

Ozeus Over a year ago

really helpful. Thank you.

Sash Sinha · Accepted Answer · 2021-12-15 11:37:50Z

You could do it in two steps, first invert the dictionary in a dict comprehension then create the dataframe using that country to continent mapping:

>>> import pandas as pd
>>> the_world = {
...         'Asia': ['China', 'Malaysia'],
...         'Europe': ['Germany'],
...         'Africa': ['Ghana']
...     }
>>> country_to_continent = {
...         country: continent
...         for continent, countries in the_world.items() 
...         for country in countries
...     }
>>> country_to_continent
{'China': 'Asia', 'Malaysia': 'Asia', 'Germany': 'Europe', 'Ghana': 'Africa'}
>>> df = pd.DataFrame(
...         data={
...             'Country': country_to_continent.keys(),
...             'Continent': country_to_continent.values()
...         })
>>> df
    Country Continent
0     China      Asia
1  Malaysia      Asia
2   Germany    Europe
3     Ghana    Africa

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