How to understand the apply function to caculate the weighted mean used in pandas?

I am new to pandas and numpy. Currently I want to caculate the weighted mean within the group. The codes searched from the internet work well for me.

import pandas as pd
import numpy as np
df = pd.DataFrame({'id':[0]*3+[1]*3,'se':[1]*2+[2]*2+[3]*2,'y':np.random.randn(6),'x':np.random.randn(6)})

def wavg(group, avg_name, weight_name):
    d = group[avg_name]
    w = group[weight_name]
    try:
        return (d * w).sum() / w.sum()
    except ZeroDivisionError:
        return np.nan
    
cc=df.groupby(['id','se']).apply(wavg, 'x','y').reset_index().rename(columns={0: 'retx'})

However, I am confused about how to build an apply function like the 'wavg'. what's the group in the wavg function. Can anyone explain it in detail?

Thanks in advance.