我0.12.0在Ubuntu上使用的是Pandas版本13.04。我正在尝试创建一个5D面板对象，以包含按条件分割的一些EEG数据。

我如何选择结构数据：

让我首先说明我对的使用pandas.core.panelnd.creat_nd_panel_factory。

Subject = panelnd.create_nd_panel_factory(
    klass_name='Subject',
    axis_orders=['setsize', 'location', 'vfield', 'channels', 'samples'],
    axis_slices={'labels': 'location',
            'items': 'vfield',
            'major_axis': 'major_axis',
            'minor_axis': 'minor_axis'},
    slicer=pd.Panel4D,
    axis_aliases={'ss': 'setsize',
            'loc': 'location',
            'vf': 'vfield',
            'major': 'major_axis',
            'minor': 'minor_axis'}
    # stat_axis=2  # dafuq is this?
    )

本质上，组织如下：

• setsize：实验条件，可以是1或2
• location的实验条件下，可以是"same"，"diff"或None
• vfield：实验条件，可以是"lvf"或“ rvf”

最后两个轴对应于DataFrame的major_axis和minor_axis。为了清楚起见，它们已重命名：

• channels：列，EEG通道（其中有129个）
• samples：行，单个样本。 samples可以作为时间轴。

我正在尝试做的是：

每个实验条件（subjectx setsizex locationx
vfield）都存储在它自己的制表符分隔的文件中，我正在阅读该文件并pandas.read_table获取一个DataFrame对象。我想Subject为每个主题创建一个5维面板（即），其中将包含DataFrame该主题的所有实验条件（即）。

首先，我为每个主题/构建一个嵌套字典Subject：

# ... do some boring stuff to get the text files, etc...
for _, factors in df.iterrows():
    # `factors` is a 4-tuple containing
    #  (subject number, setsize, location, vfield, 
    #  and path to the tab-delimited file).
    sn, ss, loc, vf, path = factors
    eeg = pd.read_table(path, sep='\t', names=range(1, 129) + ['ref'], header=None)

    # build nested dict
    subjects.setdefault(sn, {}).setdefault(ss, {}).setdefault(loc, {})[vf] = eeg

# and now attempt to build `Subject`
for sn, d in subjects.iteritems():
    subjects[sn] = Subject(d)

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---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-2-831fa603ca8f> in <module>()
----> 1 import_data()

/home/louist/Dropbox/Research/VSTM/scripts/vstmlib.py in import_data()
     64 
     65     import ipdb; ipdb.set_trace()
---> 66     for sn, d in subjects.iteritems():
     67         subjects[sn] = Subject(d)
     68

/usr/local/lib/python2.7/dist-packages/pandas/core/panelnd.pyc in __init__(self, *args, **kwargs)
     65         if 'dtype' not in kwargs:
     66             kwargs['dtype'] = None
---> 67         self._init_data(*args, **kwargs)
     68     klass.__init__ = __init__
     69

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _init_data(self, data, copy, dtype, **kwargs)
    250             mgr = data
    251         elif isinstance(data, dict):
--> 252             mgr = self._init_dict(data, passed_axes, dtype=dtype)
    253             copy = False
    254             dtype = None

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _init_dict(self, data, axes, dtype)
    293         raxes = [self._extract_axis(self, data, axis=i)
    294                  if a is None else a for i, a in enumerate(axes)]
--> 295         raxes_sm = self._extract_axes_for_slice(self, raxes)
    296 
    297         # shallow copy

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _extract_axes_for_slice(self, axes)
   1477         """ return the slice dictionary for these axes """
   1478         return dict([(self._AXIS_SLICEMAP[i], a) for i, a
-> 1479                      in zip(self._AXIS_ORDERS[self._AXIS_LEN - len(axes):], axes)])
   1480 
   1481     @staticmethod

KeyError: 'location'

我知道这panelnd是一项实验功能，但我可以肯定我做错了什么。有人能指出我正确的方向吗？如果 是 错误，是否可以解决？

和往常一样，非常感谢！

<class 'pandas.core.panelnd.Subject'>
Dimensions: 3 (setsize) x 1 (location) x 1 (vfield) x 10 (channels) x 2 (samples)
Setsize axis: level0_0 to level0_2
Location axis: level1_0 to level1_0
Vfield axis: level2_0 to level2_0
Channels axis: level3_0 to level3_9
Samples axis: level4_1 to level4_2

import pandas as pd
import numpy as np
from pandas.core import panelnd

Subject = panelnd.create_nd_panel_factory(
    klass_name='Subject',
    axis_orders=['setsize', 'location', 'vfield', 'channels', 'samples'],
    axis_slices={'location' : 'labels',
                 'vfield' : 'items',
                 'channels' : 'major_axis',
                 'samples': 'minor_axis'},
    slicer=pd.Panel4D,
    axis_aliases={'ss': 'setsize',
                  'loc': 'labels',
                  'vf': 'items',
                  'major': 'major_axis',
                  'minor': 'minor_axis'})


subjects = dict()
for i in range(3):
    eeg = pd.DataFrame(np.random.randn(10,2),columns=['level4_1','level4_2'],index=[ "level3_%s" % x for x in range(10)])

    loc, vf = ('level1_0','level2_0')
    subjects["level0_%s" % i] = pd.Panel4D({ loc : { vf : eeg }})

print Subject(subjects)