You are given the following table:

NAME_1 | 1 | T4 | T4 | T10 | T4 | T4 | T10 | T4 | 2 | T4 | 3 | T10
NAME_2 | NAME_3 | NAME_4 | NAME_5 | NAME_6 | NAME_7 | NAME_8 | NAME_9 | NAME_10 | NAME_11 | NAME_12 NAME_13 | NAME_14 | NAME_15
Money ($) | 350,000 | 66,633 | 66,633 | 44,184 | 66,633 | 66,633 | 44,184 | 66,633 | 207,000 | 66,633 | 131,974 | 44,184
Country | United States | United States | United States | United States | United States | United States | New Zealand | United States | Australia | United States | United States | Fiji
To par | E | +4 | +4 | +5 | +4 | +4 | +5 | +4 | +2 | +4 | +3 | +5
Score | 72-69-71-68=280 | 70-73-72-69=284 | 68-70-72-74=284 | 69-69-72-75=285 | 69-72-77-66=284 | 70-72-77-65=284 | 72-72-70-71=285 | 69-70-76-69=284 | 68-67-74-73=282 | 72-68-73-71=284 | 70-72-67-74=283 | 70-71-72-72=285

Your task is to reformat the table to ensure it is well-structured and can be readily parsed into a pandas DataFrame. 
You are permitted to transform the table in any manner, such as transposing, sorting/reordering, deleting, adding, etc.
You should also unify the formatting across each column.

Use the following format to response:
**Thought**: Carefully examine the table to determine whether it is well-structured. Think about what actions need to be taken if any.
**Plan**: List all the steps you plan to take to improve the table's organization. If the table is already well-structured, you can choose to leave it as is.
**Final Output**: Provide the revised, well-organized table in Markdown format. The word "format" should not appear in your response.
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