Pandas - 如何在列中展平分层索引 [英] Pandas - How to flatten a hierarchical index in columns
问题描述
我有一个数据框,在轴 1(列)中有一个分层索引(来自 groupby.agg
操作):
I have a data frame with a hierarchical index in axis 1 (columns) (from a groupby.agg
operation):
USAF WBAN year month day s_PC s_CL s_CD s_CNT tempf
sum sum sum sum amax amin
0 702730 26451 1993 1 1 1 0 12 13 30.92 24.98
1 702730 26451 1993 1 2 0 0 13 13 32.00 24.98
2 702730 26451 1993 1 3 1 10 2 13 23.00 6.98
3 702730 26451 1993 1 4 1 0 12 13 10.04 3.92
4 702730 26451 1993 1 5 3 0 10 13 19.94 10.94
我想把它弄平,使它看起来像这样(名称并不重要 - 我可以重命名):
I want to flatten it, so that it looks like this (names aren't critical - I could rename):
USAF WBAN year month day s_PC s_CL s_CD s_CNT tempf_amax tmpf_amin
0 702730 26451 1993 1 1 1 0 12 13 30.92 24.98
1 702730 26451 1993 1 2 0 0 13 13 32.00 24.98
2 702730 26451 1993 1 3 1 10 2 13 23.00 6.98
3 702730 26451 1993 1 4 1 0 12 13 10.04 3.92
4 702730 26451 1993 1 5 3 0 10 13 19.94 10.94
我该怎么做?(我试了很多,都无济于事.)
How do I do this? (I've tried a lot, to no avail.)
根据建议,这是字典形式的头部
Per a suggestion, here is the head in dict form
{('USAF', ''): {0: '702730',
1: '702730',
2: '702730',
3: '702730',
4: '702730'},
('WBAN', ''): {0: '26451', 1: '26451', 2: '26451', 3: '26451', 4: '26451'},
('day', ''): {0: 1, 1: 2, 2: 3, 3: 4, 4: 5},
('month', ''): {0: 1, 1: 1, 2: 1, 3: 1, 4: 1},
('s_CD', 'sum'): {0: 12.0, 1: 13.0, 2: 2.0, 3: 12.0, 4: 10.0},
('s_CL', 'sum'): {0: 0.0, 1: 0.0, 2: 10.0, 3: 0.0, 4: 0.0},
('s_CNT', 'sum'): {0: 13.0, 1: 13.0, 2: 13.0, 3: 13.0, 4: 13.0},
('s_PC', 'sum'): {0: 1.0, 1: 0.0, 2: 1.0, 3: 1.0, 4: 3.0},
('tempf', 'amax'): {0: 30.920000000000002,
1: 32.0,
2: 23.0,
3: 10.039999999999999,
4: 19.939999999999998},
('tempf', 'amin'): {0: 24.98,
1: 24.98,
2: 6.9799999999999969,
3: 3.9199999999999982,
4: 10.940000000000001},
('year', ''): {0: 1993, 1: 1993, 2: 1993, 3: 1993, 4: 1993}}
推荐答案
我认为最简单的方法是将列设置为顶级:
I think the easiest way to do this would be to set the columns to the top level:
df.columns = df.columns.get_level_values(0)
注意:如果 to 级别有名称,您也可以通过 this 访问它,而不是 0.
.
如果你想结合/加入
你的MultiIndex 合并为一个索引 (假设您的列中只有字符串条目) 您可以:
If you want to combine/join
your MultiIndex into one Index (assuming you have just string entries in your columns) you could:
df.columns = [' '.join(col).strip() for col in df.columns.values]
注意:我们必须strip
没有第二个索引时的空格.
In [11]: [' '.join(col).strip() for col in df.columns.values]
Out[11]:
['USAF',
'WBAN',
'day',
'month',
's_CD sum',
's_CL sum',
's_CNT sum',
's_PC sum',
'tempf amax',
'tempf amin',
'year']
这篇关于Pandas - 如何在列中展平分层索引的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!