有可能,但真的很复杂:
np.random.seed(234)
df= pd.DataFrame(np.random.randint(5,8,(1000,4)), columns=['a','b','c','d'])
wm = lambda x: (x * df.loc[x.index, "c"]).sum() / x.sum()
wm.__name__ = 'wa'
f = lambda x: x.sum() / df['b'] .sum()
f.__name__ = '%'
g = df.groupby('a').agg(
{'b':['sum', f, 'mean', wm],
'c':['sum','mean'],
'd':['sum']})
g.columns = g.columns.map('_'.join)
print (g)
d_sum c_sum c_mean b_sum b_% b_mean b_wa
a
5 2104 2062 5.976812 2067 0.344672 5.991304 5.969521
6 1859 1857 5.951923 1875 0.312656 6.009615 5.954667
7 2058 2084 6.075802 2055 0.342671 5.991254 6.085645
适用的解决方案:
def func(x