以嵌套列表的形式访问 pandas DataFrame答案

【问题标题】：Accessing pandas DataFrame as a nested list以嵌套列表的形式访问 pandas DataFrame
【发布时间】：2017-05-22 03:40:49
【问题描述】：

我已使用.set_index() 函数将第一列设置为数据框中行的索引：

>>> import pandas as pd
>>> df = pd.DataFrame([['x', 1,2,3,4,5], ['y', 6,7,8,9,10], ['z', 11,12,13,14,15]])
>>> df.columns = ['index', 'a', 'b', 'c', 'd', 'e']
>>> df = df.set_index(['index'])
>>> df
        a   b   c   d   e
index                    
x       1   2   3   4   5
y       6   7   8   9  10
z      11  12  13  14  15

应该如何操作数据框，以便可以像嵌套列表一样访问我？例如以下是可能的：

>>> df['x']
[1, 2, 3, 4, 5]

>>> df['x']['a']
1

>>> df['x']['a', 'b']
(1, 2)

>>> df['x']['a', 'd', 'c']
(1, 4, 3)

我在设置索引后尝试访问df['x']，但它引发错误，这是访问x 行的正确方法吗？

>>> import pandas as pd
>>> df = pd.DataFrame([['x', 1,2,3,4,5], ['y', 6,7,8,9,10], ['z', 11,12,13,14,15]])
>>> df.columns = ['index', 'a', 'b', 'c', 'd', 'e']
>>> df = df.set_index(['index'])
>>> df
        a   b   c   d   e
index                    
x       1   2   3   4   5
y       6   7   8   9  10
z      11  12  13  14  15
>>> df['x']
Traceback (most recent call last):
  File "/usr/local/lib/python3.5/site-packages/pandas/core/indexes/base.py", line 2393, in get_loc
    return self._engine.get_loc(key)
  File "pandas/_libs/index.pyx", line 132, in pandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)
  File "pandas/_libs/index.pyx", line 154, in pandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)
  File "pandas/_libs/hashtable_class_helper.pxi", line 1207, in pandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)
  File "pandas/_libs/hashtable_class_helper.pxi", line 1215, in pandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)
KeyError: 'x'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.5/site-packages/pandas/core/frame.py", line 2062, in __getitem__
    return self._getitem_column(key)
  File "/usr/local/lib/python3.5/site-packages/pandas/core/frame.py", line 2069, in _getitem_column
    return self._get_item_cache(key)
  File "/usr/local/lib/python3.5/site-packages/pandas/core/generic.py", line 1534, in _get_item_cache
    values = self._data.get(item)
  File "/usr/local/lib/python3.5/site-packages/pandas/core/internals.py", line 3590, in get
    loc = self.items.get_loc(item)
  File "/usr/local/lib/python3.5/site-packages/pandas/core/indexes/base.py", line 2395, in get_loc
    return self._engine.get_loc(self._maybe_cast_indexer(key))
  File "pandas/_libs/index.pyx", line 132, in pandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5239)
  File "pandas/_libs/index.pyx", line 154, in pandas._libs.index.IndexEngine.get_loc (pandas/_libs/index.c:5085)
  File "pandas/_libs/hashtable_class_helper.pxi", line 1207, in pandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20405)
  File "pandas/_libs/hashtable_class_helper.pxi", line 1215, in pandas._libs.hashtable.PyObjectHashTable.get_item (pandas/_libs/hashtable.c:20359)
KeyError: 'x'

【问题讨论】：

标签： python pandas matrix indexing nested-lists

【解决方案1】：

您可以使用loc。

从你的例子中：

df['x'] 应该是df.loc['x']
df['x']['a'] 应该是df.loc['x', 'a']，
df['x']['a', 'd', 'c'] 应该是df.loc['x', ['a', 'd', 'c']]

【讨论】：

【解决方案2】：

访问行应该使用loc:

df.loc['x']

获取行列应该是

df.loc['x', ['a', 'c']]

或者你可以得到转置

df.T.x

【讨论】：