使用pandas的df.iloc选择单列触发ValueError的原因解析

咱们先从你给出的例子说起：你用日期索引创建了DataFrame后，df.loc['20130101':'20130102', 'A']能正常返回结果，但换成df.iloc[0:1, 'A']就直接抛出了ValueError，核心原因其实是**iloc和loc的设计逻辑完全不同**：

先明确两个索引器的核心定位 #

• loc是标签索引器：它完全靠行/列的标签名称定位数据，所以你传日期字符串（行标签）和列名'A'（列标签）完全符合它的规则。
• iloc是位置索引器：它只认行/列的整数位置（从0开始计数），不接受任何标签类参数——比如列名、日期字符串这类都不属于它的合法输入范围。

你的错误用法哪里出问题了？ #

你在iloc的第二个参数传了'A'，这是列的标签名称，不是它对应的整数位置，直接违反了iloc的使用规则，所以它抛出的错误信息已经说得很直白：

Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types

翻译过来就是：基于位置的索引只能用整数、整数切片、整数列表/数组或者布尔数组类型的参数。

正确的iloc用法 #

如果想用iloc实现和df.loc['20130101':'20130102', 'A']一样的效果，你需要把列名'A'换成它的整数位置（这里'A'是第0列）：

# 注意iloc是左闭右开切片，要取前两行得写0:2
df.iloc[0:2, 0]

如果不确定列的位置，也可以用df.columns.get_loc('A')动态获取列的位置索引：

col_pos = df.columns.get_loc('A')
df.iloc[0:2, col_pos]

回顾你的完整代码示例 #

创建DataFrame的代码

import pandas as pd
import numpy as np

dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))

正确的loc调用及输出

df.loc['20130101':'20130102', 'A']

输出：

2013-01-01    0.469112
2013-01-02    1.212112
Freq: D, Name: A, dtype: float64

错误的iloc调用触发的完整报错

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py in _has_valid_tuple(self, key)
    221             try:
---> 222                 self._validate_key(k, i)
    223             except ValueError:

/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py in _validate_key(self, key, axis)
   1970                 raise ValueError("Can only index by location with "
-> 1971                                  "a [{types}]".format(types=self._valid_types))
   1972 

ValueError: Can only index by location with a [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array]

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-73-c05fbef69c91> in <module>()
----> 1 df.iloc[0:1, 'A']

/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py in __getitem__(self, key)
   1470             except (KeyError, IndexError):
   1471                 pass
-> 1472             return self._getitem_tuple(key)
   1473         else:
   1474             # we by definition only have the 0th axis

/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py in _getitem_tuple(self, tup)
   2011     def _getitem_tuple(self, tup):
   2012 
-> 2013         self._has_valid_tuple(tup)
   2014         try:
   2015             return self._getitem_lowerdim(tup)

/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py in _has_valid_tuple(self, key)
    224                 raise ValueError("Location based indexing can only have "
    225                                  "[{types}] types"
--> 226                                  .format(types=self._valid_types))
    227 
    228     def _is_nested_tuple_indexer(self, tup):

ValueError: Location based indexing can only have [integer, integer slice (START point is INCLUDED, END point is EXCLUDED), listlike of integers, boolean array] types

内容的提问来源于stack exchange，提问作者goedi