我有以下DataFrame:

在我想要添加的地方,为列增加一个索引级别,如红色所示。
我创建的MultiIndex如下所示:
MI = pd.MultiIndex(levels=[['trade_input', 'mae_function'], list(df)],
labels=[[0, 0, 1, 1, 1, 1], range(len(list(df)))],
names=['first', 'second'])如何将MultiIndex添加到现有的DataFrame中?如何指定应将其应用于列?
在下面的数据和命令下面重新创建原始的DataFrame:
df = pd.DataFrame(data = dict, columns = ['entry_index', 'exit_index', 'direction', 'high', 'low', 'compar_tuples'])
dict = {'compar_tuples': {0: [(1, slice('1', '1', None))],
1: [(1, slice('1', '2', None)), (2, slice('2', '2', None))],
2: [(1, slice('1', '3', None)),
(2, slice('2', '3', None)),
(3, slice('3', '3', None))],
3: [(1, slice('1', '4', None)),
(2, slice('2', '4', None)),
(3, slice('3', '4', None)),
(4, slice('4', '4', None))],
4: [(1, slice('1', '5', None)),
(2, slice('2', '5', None)),
(3, slice('3', '5', None)),
(4, slice('4', '5', None)),
(5, slice('5', '5', None))],
5: [(1, slice('1', '6', None)),
(2, slice('2', '6', None)),
(3, slice('3', '6', None)),
(4, slice('4', '6', None)),
(5, slice('5', '6', None)),
(6, slice('6', '6', None))],
6: [(1, slice('1', '7', None)),
(2, slice('2', '7', None)),
(3, slice('3', '7', None)),
(4, slice('4', '7', None)),
(5, slice('5', '7', None)),
(6, slice('6', '7', None)),
(7, slice('7', '7', None))]},
'direction': {0: 1, 1: -1, 2: -1, 3: -1, 4: -1, 5: -1, 6: -1},
'entry_index': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0},
'exit_index': {0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 7},
'high': {0: 1209.75,
1: 1211.0,
2: 1211.25,
3: 1207.25,
4: 1206.25,
5: 1205.75,
6: 1205.5},
'low': {0: 1207.25,
1: 1207.5,
2: 1205.75,
3: 1206.0,
4: 1201.0,
5: 1202.75,
6: 1203.75}}发布于 2017-01-03 16:53:46
最简单的方法是将pd.concat与keys参数一起使用
ti_cols = df.columns[:2]
mae_cols = df.columns[2:]
pd.concat([df[ti_cols], df[mae_cols]], axis=1, keys=['trade_inputs', 'mae_function'])

但是,如果您在创建多个索引时遇到了麻烦,只需将其分配给columns属性即可。
df.columns = MI
df

发布于 2017-01-03 16:54:24
df.index = index为我工作过。
https://stackoverflow.com/questions/41448361
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