找出最频率组合并添加标签

Question

I have a table with my customer data like this:

Customer    Price
AAA            100
AAA            100
AAA            200
BBB            100
BBB            220
BBB            200
BBB            200

What I want to do is to find out the customer with the condition number of price >= 200 is more than number of price < 200 and add labels for them. for example:

Customer    LABELS
AAA            FALSE
BBB            TRUE

any ideas for this issue?

Answer 1

df.Price.ge(200).groupby(df.Customer).mean().gt(.5)

Customer
AAA    False
BBB     True
Name: Price, dtype: bool

Or if you insist on your format

df.Price.ge(200).groupby(df.Customer).mean().gt(.5).reset_index(name='Labels')

  Customer  Labels
0      AAA   False
1      BBB    True

Answer 2

Straightforward answer:

df.groupby('Customer').apply(
    lambda g: (g['Price'] >= 200).sum() > (g['Price'] < 200).sum()
)

Summing a boolean vector will return the number of True values.