How to group a Pandas DataFrame by multiple columns and perform aggregation based on a specific column?

Python
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#1

I have a dataset similar to the dataset shown below:

Name      Country             Sales

Alice       USA               1000
Bob         Canada            500
Charlie     UK                2000
Bob         Canada            700
Alice       USA               200
David       USA               1200
Charlie     UK                600
Alice       USA               2000

And I am trying to find the total sales made by each person based on which country they are from, in other words, I want to subset or group the data based on the country to which they belong and then group them on the basis of their names and then find the total sales for each person. Please provide me with different methods with example codes for doing this task. You can use the following dataframe code to get started:

data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'Bob', 'Alice', 'David', 'Charlie', 'Alice'],
    'Country': ['USA', 'Canada', 'UK', 'Canada', 'USA', 'USA', 'UK', 'USA'],
    'Sales': [1000, 500, 2000, 700, 200, 1200, 600, 2000]
}

df = pd.DataFrame(data)