pandas apply function with multiple inputs to create a new column

Question

I have a function I want to use to generate a new column

 def airport_to_country(a_code,country_dict):
     return country_dict[a_code]

Dataframe looks like this:

Rank  AirportCode
1   LAX
2   AUH
3   HBE
...
.

What I want to do I create another column so it would look like this

Rank  ACode  Country
1       LAX  North America
2       AUH  United Arab Emirates
3       HBE  Egypt
...
.

normally I would do this :

df['Country'] = df['Acode'].apply(airport_to_country))

But my function has 2 inputs, so I also need to give it the country_dict which is a Airport code to Country mapping

I was hoping this would work but its erroring as its looking for another input for the country

df['Country'] = df['Acode'].apply(airport_to_country(country_dict))

But my function is a lookup in a dict and not a simple multiplication of variables. So I couldn't get it work

chowpay · Accepted Answer · 2022-07-29 00:06:05Z

1

after some fiddling around I got it to work using that example:

df['country'] = df.apply(lambda x: airport_to_contry(x['a_code'],country_dict),axis = 1)

answered Jul 28, 2022 at 1:43

chowpay

1,7158 gold badges25 silver badges57 bronze badges

Sign up to request clarification or add additional context in comments.

4 Comments

df['a_code'].apply(airport_to_country, args=(country_dict,)) <-- The apply can be simplified to this.

Also, df['a_code'].apply(airport_to_country, country_dict=country_dict)

@ScottBoston just curious what does country_dict=country_dict do?

Passes externally define country_dict to the applied function as an argument for country_dict variable input.