Creating a new columns based on conditions from other columns

I have a dataframe that is something like this:

    Max        Min     Id
1    10        5      AAA
2    15        10     AAB
3    10        7      AAC 
4    20        15     AAD
5    15        10     AAE

I want to add another column to the dataframe with the condition that max and min values are the same, so de rows AAB and AAE would have the same “classification” or “family” .

I would have something like this:

     Max       Min    Id     Family
1    10        5      AAA      J
2    15        10     AAB      K
3    10        7      AAC      L
4    20        15     AAD      M
5    15        10     AAE      K

What’s the best way to do this?

Answer

Records having the same Max and Min will have the same family number.

The use of apply could make it slow for larger dataframes

def func(row):
    return df.loc[(df['Max']==row['Max']) & (df['Min']==row['Min'])]['Max'].idxmin()

df['Family'] = df.apply(func, axis=1)

   Max  Min  Family
0   10    5       0
1   15   10       1
2   10    7       2
3   20   15       3
4   15   10       1

EDIT: A faster way to do the same

df['idx'] = df.groupby(['Max', 'Min']).ngroup()