How to check for duplicate values in the same dataframe column and apply if condition by dropping the row based on frequency?

Dataframe :

name	Location	Rating	Frequency
Ali	Nasi Kandar	1 star	1
Ali	Baskin Robin	4 star	3
Ali	Nasi Ayam	3 star	1
Ali	Burgergrill	2 star	2
Lee	Fries	1 star	3
Abu	Mcdonald	3 star	3
Abu	KFC	3 star	1
Ahmad	Nandos	3 star	2
Ahmad	Burgerdhil	2 star	3
Ahmad	Kebab	1 star	10

Here is the sample data set. The logic would be:

1st condition: if the name has duplicate values, check the frequency and see which one is higher, drop the row with lower frequency

2nd condition: If no name duplicate (e.g:Lee), keep the row

3rd condition: Rating is the same (e.g: Abu), keep the first value

Desired Output:

name	Location	Rating	Frequency
Ali	Baskin Robin	4 star	3
Lee	Fries	1 star	3
Abu	KFC	3 star	1
Ahmad	Kebab	1 star	10

Any of you guys know how I do this in python pandas or pyspark?

I got into troubles checking for duplicates and also applying probably the "if condition" to this dataframe