Pandas add new columns based on splitting another column

Question

I have a pandas dataframe like the following:

A              B
US,65,AMAZON   2016
US,65,EBAY     2016

My goal is to get to look like this:

Answer 1

For getting the new columns I would prefer doing it as following:

df['Country'] = df['A'].apply(lambda x: x[0])
df['Code'] = df['A'].apply(lambda x: x[1])
df['Com'] = df['A'].apply(lambda x: x[2])

As for the replacement of , with a . you can use the following:

df['A'] = df['A'].str.replace(',','.')