所以,这是我的问题:
dfa = pd.DataFrame({"a": [["a", "b", "c"][int(k/10)] for k in range(30)],
"b": ["a" + repr([10, 20, 30, 40, 50, 60][int(k/5)]) for k in range(30)],
"c": np.arange(30),
"d": np.random.normal(size=30)}).set_index(["a","b","c"])
dfb = pd.DataFrame({"a": [["a", "b", "c"][int(k/2)] for k in range(6)],
"b": ["a" + repr([10, 20, 30, 40, 50, 60][k]) for k in range(6)],
"m": np.random.normal(size=6)**2}).set_index(["a","b"])
基本上我有两个带有多指数的数据帧,我希望将dfa.d
除以dfb.m
,加入("a", "b")
。我无法天真地dfa.d / dfb.m
或join
,因为它表示merging with more than one level overlap on a multi-index is not implemented
。
我发现最直接(lol)这样做的方法是:
dfc = dfa.reset_index().set_index(["a", "b"]).join(dfb)
dfc["r"] = dfc.d / dfc.m
dfd = dfc.reset_index().set_index(["a", "b", "c"])[["r"]]
任何捷径?
答案 0 :(得分:5)
此问题的an open bug,当前的里程碑显示0.15.1
。
在出现更好的事情之前,a workaround涉及以下步骤:
unstack
将不匹配的索引级别排除在列stack
列回到原来的位置。像这样:
In [109]: dfa.unstack('c').mul(dfb.squeeze(), axis=0).stack('c')
Out[109]:
d
a b c
a a10 0 1.535221
1 -2.151894
2 1.986061
3 -1.946031
4 -4.868800
a20 5 -2.278917
6 -1.535684
7 2.289102
8 -0.442284
9 -0.547209
b a30 10 -12.568426
11 7.180348
12 1.584510
13 3.419332
14 -3.011810
a40 15 -0.367091
16 4.264955
17 2.410733
18 0.030926
19 1.219653
c a50 20 0.110586
21 -0.430263
22 0.350308
23 1.101523
24 -1.371180
a60 25 -0.003683
26 0.069884
27 0.206635
28 0.356708
29 0.111380
注意两件事:
dfb
必须是Series
,否则会有哪些dfb
列用于乘法的额外复杂性。您可以将dfb.squeeze()
替换为dfb['m']
。.reorder_levels(dfa.index.names)