Python - best approach to mapping codes in data to description

Question

I am getting the results I want but want to understand if this would be considered the best, or even a correct way of mapping data codes to descriptors.

I have a dataset where many of the values are stored as numeric codes which represent some attribute - e.g.

Fruit_Type:
1 = Apple,
2 = Orange,
3 = Banana,
4 = Grape

In SAS, I would have used a Proc Format to map the numeric to the descriptor. In SQL I would typically use a case statement which would let me either keep the original field name or assign it a new name.

I am fairly new to Python and am curious what would be considered the best approach to this. What I have been using - which seems to work fine is to create the mapping as a dictionary and then create a new column using the .apply function. This works but is it the right way to do this?

import pandas as pd 
# Create sample dataframe  
data = {'Fruit_Type':[1, 2, 2, 3, 1, 2, 4], 
        'other_data':['blah', 'blah','blah', 'blah','blah', 'blah',
                      'blah']} 

df = pd.DataFrame(data) 

#create dictionary
Fruit_Type_dictionary = {1: 'Apple',
                        2: 'Orange',
                        3: 'Banana',
                        4: 'Grape'}

df['rpt_Fruit_Type']= df['Fruit_Type'].apply(lambda x: Fruit_Type_dictionary.get(x))

print(df) 

which yields:

       Fruit_Type other_data rpt_Fruit_Type
0           1       blah          Apple
1           2       blah         Orange
2           2       blah         Orange
3           3       blah         Banana
4           1       blah          Apple
5           2       blah         Orange
6           4       blah          Grape

which pretty much gives me my desired results.

Answer 1

I would use Series map method to improve readability:

df['rpt_Fruit_Type']= df['Fruit_Type'].map(Fruit_Type_dictionary)