我如何在不对 pandas 进行排序的情况下取消堆叠?
问题描述
我有以下几天的时间序列数据.. 我想按日期"取消堆叠.但我使用 .unstack() 然后自动对时间进行排序..(日期/时间是多索引)
i have below time-series data couple of day.. and i wanna unstack by 'Date' it. but i used .unstack() then automatically sorted of time.. (Date/Time is multi index)
Date Time a b c d e
2015-12-06 22:00:00 21.26 0 2.62 242.195 0
2015-12-06 22:15:00 21.14 0 2.55 255.516 0
2015-12-06 22:30:00 21.2 0 2.49 241.261 0
2015-12-06 22:45:00 21.18 0 2.48 232.058 0
2015-12-06 23:00:00 21.12 0 2.38 239.661 0
2015-12-06 23:15:00 21 0 2.23 228.324 0
2015-12-06 23:30:00 21.13 0 2.29 0 0
2015-12-06 23:45:00 21.12 0 2.29 0 0
2015-12-06 0:00:00 21.02 0 2.17 0 0
2015-12-06 0:15:00 21.09 0 2.13 0 0
2015-12-06 0:30:00 20.96 0 2.21 0 0
2015-12-06 0:45:00 20.92 0 2.19 0 0
2015-12-06 1:00:00 20.99 0 2.13 0 0
2015-12-06 1:15:00 20.92 0 2.14 0 0
2015-12-06 1:30:00 20.97 0 2.13 0 0
2015-12-06 1:45:00 20.85 0 2.11 0 0
2015-12-06 2:00:00 20.76 0 1.72 0 0
我想要的结果如下所示.我该怎么做?
my wanted results is like below. how can i do it?
a a a a...
Date 2015-12-06 0:00 2015-12-13 0:00 2015-12-20 0:00 2015-12-23 0:00...
Time
22:00:00 21.02 21.26 20.75 22.61
22:15:15:00 21.09 21.36 20.74 22.65
..
0:00:00 20.92 21.2 20.79 22.37
0:15:00 20.99 21.33 20.77 22.44
0:30:00 20.92 21.24 20.76 22.28
..
解决方案
你需要unstack 按第一级然后reindex 由第二级的 unique 值，最后 MutiIndexsort_index> 在列中:
You need unstack by first level and then reindex by unique values of second level, last sort_index of second level of MutiIndex in columns:
df =df.unstack(0).reindex(pd.unique(df.index.get_level_values(1))).sort_index(axis=1,level=1)
print (df)
a b c c e valve
Date 2015-12-06 2015-12-06 2015-12-06 2015-12-06 2015-12-06
Time
22:00:00 21.26 0 2.62 242.195 0
22:15:00 21.14 0 2.55 255.516 0
22:30:00 21.20 0 2.49 241.261 0
22:45:00 21.18 0 2.48 232.058 0
23:00:00 21.12 0 2.38 239.661 0
23:15:00 21.00 0 2.23 228.324 0
23:30:00 21.13 0 2.29 0.000 0
23:45:00 21.12 0 2.29 0.000 0
0:00:00 21.02 0 2.17 0.000 0
0:15:00 21.09 0 2.13 0.000 0
0:30:00 20.96 0 2.21 0.000 0
0:45:00 20.92 0 2.19 0.000 0
1:00:00 20.99 0 2.13 0.000 0
1:15:00 20.92 0 2.14 0.000 0
1:30:00 20.97 0 2.13 0.000 0
1:45:00 20.85 0 2.11 0.000 0
2:00:00 20.76 0 1.72 0.000 0
idx = (pd.date_range('2015-01-01','2015-01-01 23:45:00', freq='15T') +
pd.to_timedelta('22:00:00')).time
df = df.unstack(0).reindex(idx)
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