create a column based on other column, apply , lambda in Python

'''
We need to calculate the sales tax and total amount owed for every order in this sheet.

    If location is Sun Valley, apply a sales tax of 8%
    If location is Mammoth, apply a sales tax of 7.75%.
    If location is Stowe, apply a sales tax of 6%
'''

df['Tax'] = df.apply(lambda row: 0.08 if row['Location'] == 'Sun Valley'
                     else (0.0775 if row['Location'] == 'Mammoth'
                           else (0.06 if row['Location'] == 'Stowe'
                                 else row['Tax'])), axis=1)

df.loc[:, ['Tax', 'Location']]

###########################################################
'''
I have a Subtotal column and a Tax column in the dataframe and I want based on these two columns to write values ​​to the third column Total.
'''
df['Total'] = df.apply(lambda row: row['Subtotal'] + (row['Tax'] * row['Subtotal']), axis=1)
df['Total'] = df['Subtotal'] + (df['Tax'] * df['Subtotal])

titanic['fare'] = titanic['fare'] * 10