Pandas: Grouping by one value + new column about this group

I have this dataframe:

    Player          Country
0   Peter           USA
1   Louis           France
2   Andrew          France
3   Peter           Spain
4   Michael         Spain
5   Alfred          USA
6   Peter           France
7   Michael         USA
8   Andrew          USA
9   Michael         Spain

I need to create a new dataframe grouping the column Player by the names and, besides, I have to create a new column where the result depends on the column Country. I need this column (called Availability) to say 'Yes' if in the countries appears a country different to Spain or USA. So the result in the new dataframe would be:

    Player          Availability
0   Peter           Yes
1   Louis           Yes
2   Andrew          Yes
3   Michael         No
4   Alfred          No

Any suggestion about how to do it? Thanks in advance.

Solution 1:

Use:

new_df = (~df['Country'].str.contains('USA|Spain', regex=True))\
    .groupby(df['Player'], sort=False).any().reset_index(name='Availability')\
    .assign(Availability=lambda df: df['Availability'].map({True : 'Yes',
                                                            False: 'No'}))
    
    Player Availability
0    Peter          Yes
1    Louis          Yes
2   Andrew          Yes
3  Michael           No
4   Alfred           No