How to unpack a list column in pandas dataframe

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I have a pandas DataFrame of the form:

    age    begin        end       product_id
0   40  1578178800  1579388400        [3, 4]
1   30  1578178800  1579388400   [3, 4, 6, 2, 5, 1]
2   30  1578178800  1578265200         [6]
3   58  1578178800  1578265200         [6]
4   30  1578178800  1578265200         [6]

Since theproduct_id is the combination of the products the customers choose. For example: 1 - electronics, 2 - automobiles, 3- accessories, 4 - Robots, 5 - Training, 6 - Other

I would like to have the DataFrame in the form below without the list around it:

    age    begin        end                         product_id
0   40  1578178800  1579388400                 accessories, Robots
1   30  1578178800  1579388400   accessories, Robots, Other, automobiles, Training, electronics
2   30  1578178800  1578265200                       Other
3   58  1578178800  1578265200                       Other
4   30  1578178800  1578265200                       Other
pandas dataframe python-3.x python
1 Answers

Use list comprehension with map values by dictionary and convert to joined strings:

d = {1:'electronics',
     2: 'automobiles',
     3:'accessories', 
     4:'Robots',
     5:'Training',
     6: 'Other'}

df['product_id'] = df['product_id'].map(lambda x: ', '.join(d[y] for y in x))
print (df)
   age       begin         end  \
0   40  1578178800  1579388400   
1   30  1578178800  1579388400   
2   30  1578178800  1578265200   
3   58  1578178800  1578265200   
4   30  1578178800  1578265200   

                                          product_id  
0                                accessories, Robots  
1  accessories, Robots, Other, automobiles, Train...  
2                                              Other  
3                                              Other  
4                                              Other

Or:

df['product_id'] = [', '.join(d[y] for y in x) for x in df['product_id']]
user_29010020
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