Reverse a series within DataFrame to new column

How would I reverse the order of a series within a DataFrame into a new column?

data = [["US Dollar", 7.00],
        ['Euro', 2.00],
        ['British Pound', 4.00],
        ['Indian Rupee', 2.00],
        ['Australian Dollar', 9.00],
        ['Canadian Dollar', 3.00],
        ['Singapore Dollar', 3.00],
        ['Swiss Franc', 5.00]
       ]

df = pd.DataFrame(data, columns=['Currency', 'Order'])

I tried using loc to do this but that is giving me the same order back.

df['Reverse Order'] = df['Order'].iloc[::-1]
df


#   Currency            Order   Reverse Order
# 0 US Dollar           7.0     7.0
# 1 Euro                2.0     2.0
# 2 British Pound       4.0     4.0
# 3 Indian Rupee        2.0     2.0
# 4 Australian Dollar   9.0     9.0
# 5 Canadian Dollar     3.0     3.0
# 6 Singapore Dollar    3.0     3.0
# 7 Swiss Franc         5.0     5.0

I’m trying to get the reverse order such that

#   Currency            Order   Reverse Order
# 0 US Dollar           7.0     5.0
# 1 Euro                2.0     3.0
# 2 British Pound       4.0     3.0
# 3 Indian Rupee        2.0     9.0
# 4 Australian Dollar   9.0     2.0
# 5 Canadian Dollar     3.0     4.0
# 6 Singapore Dollar    3.0     2.0
# 7 Swiss Franc         5.0     7.0

>Solution :

Convert the values to numpy array (because now the index align back to original dataframe):

df["Reverse Order"] = df.loc[::-1, "Order"].to_numpy()
print(df)

Prints:

            Currency  Order  Reverse Order
0          US Dollar    7.0            5.0
1               Euro    2.0            3.0
2      British Pound    4.0            3.0
3       Indian Rupee    2.0            9.0
4  Australian Dollar    9.0            2.0
5    Canadian Dollar    3.0            4.0
6   Singapore Dollar    3.0            2.0
7        Swiss Franc    5.0            7.0