capstone_project_starbucks_2.py

# Portfolio preprocessing

values = []

# Iterate the dataframe
for index, row in portfolio.iterrows():
    
    # Set the default value
    new_value = [0,0,0,0]
    
    # If the value match with the channels, change it to 1
    for item in row['channels']:
        if item == 'web':
            new_value[0] = 1
        elif item == 'email':
            new_value[1] = 1
        elif item == 'mobile':
            new_value[2] = 1
        elif item == 'social':
            new_value[3] = 1
            
    values.append(new_value)

# Merge the current portfolio dataframe with the new one
portfolio = pd.concat([portfolio, pd.DataFrame(values, columns=['web', 'email', 'mobile', 'social'])], axis=1)
portfolio.drop(columns=['channels'], inplace=True)