Python 无法对memmap数组的数据帧执行Groupby，因为它'；这太不像话了

我有panada dataframe

预测

，它由三列组成。我使用三个

memmap数组创建了这个数据帧

    predictions = pd.dataframe{'cell': list_1, 'tree': list_2, 'predict': list_3, 'label': list_4}

现在，我想对这个数据帧的两列进行分组，并对第三列进行平均，如下所示：

    df = predictions.groupby(['tree', 'cell'])['list3'].mean()

但是它给了我一个错误，说memmap数组是不可损坏的！并且它不能执行
groupby
。
我真的需要做
groupby
，否则我必须为
循环做两次
，因为我的字典有
1000000行。我想知道有人知道解决办法吗？谢谢

已编辑
单元格
和
树
列是
memmap数组
中的项目列表<代码>预测
和标签
只是普通列表。
memmap数组
项的列表如下所示：
细胞

预测数据帧如下所示：

      cell  label  predict  tree
0    [415]      0        1  [19]
1    [143]      1        1  [22]
2     [96]      0        1  [19]
3    [432]      1        1  [12]
4    [104]      0        1  [21]
5     [76]      0        1  [19]
6    [312]      1        1  [22]
7    [143]      1        1  [22]
8    [312]      1        1  [22]
9     [64]      0        1  [18]
10   [296]      1        1  [22]

我发现以下错误：

predictions_target = predictions.groupby(['tree', 'cell'])    ['predict'].mean()
File "/usr/venv/local/lib/python2.7/site-packages/pandas    /core/groupby.py", line 1015, in mean
return self._python_agg_general(f)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 826, in _python_agg_general
return self._python_apply_general(f)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 698, in _python_apply_general
self.axis)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1577, in apply
splitter = self._get_splitter(data, axis=axis)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1563, in _get_splitter
comp_ids, _, ngroups = self.group_info
File "pandas/src/properties.pyx", line 34, in pandas.lib.cache_readonly.__get__ (pandas/lib.c:44222)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1670, in group_info
comp_ids, obs_group_ids = self._get_compressed_labels()
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1677, in _get_compressed_labels
all_labels = [ping.labels for ping in self.groupings]
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 2308, in labels
self._musr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 2319, in _make_labels
labels, uniques = algos.factorize(self.grouper, sort=self.sort)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/algorithms.py", line 313, in factorize
labels = table.get_labels(vals, uniques, 0, na_sentinel, True)
File "pandas/src/hashtable_class_helper.pxi", line 843, in     pandas.hashtable.PyObjectHashTable.get_labels (pandas/hashtable.c:14831)
TypeError: unhashable type: 'memmap'

可能需要
predictions.list1=predictions.list1.apply（tuple）
和
predictions.list2=predictions.list2.apply（tuple）
如果值是
memmap数组的列表
s，最好添加一些小数据样本-4-5行，谢谢。这几乎是但不是一个简单的工作示例…我已经编辑了问题并添加了更多信息！
predictions_target = predictions.groupby(['tree', 'cell'])    ['predict'].mean()
File "/usr/venv/local/lib/python2.7/site-packages/pandas    /core/groupby.py", line 1015, in mean
return self._python_agg_general(f)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 826, in _python_agg_general
return self._python_apply_general(f)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 698, in _python_apply_general
self.axis)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1577, in apply
splitter = self._get_splitter(data, axis=axis)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1563, in _get_splitter
comp_ids, _, ngroups = self.group_info
File "pandas/src/properties.pyx", line 34, in pandas.lib.cache_readonly.__get__ (pandas/lib.c:44222)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1670, in group_info
comp_ids, obs_group_ids = self._get_compressed_labels()
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 1677, in _get_compressed_labels
all_labels = [ping.labels for ping in self.groupings]
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 2308, in labels
self._musr/venv/local/lib/python2.7/site-packages/pandas/core/groupby.py", line 2319, in _make_labels
labels, uniques = algos.factorize(self.grouper, sort=self.sort)
File "/usr/venv/local/lib/python2.7/site-packages/pandas/core/algorithms.py", line 313, in factorize
labels = table.get_labels(vals, uniques, 0, na_sentinel, True)
File "pandas/src/hashtable_class_helper.pxi", line 843, in     pandas.hashtable.PyObjectHashTable.get_labels (pandas/hashtable.c:14831)
TypeError: unhashable type: 'memmap'