[英]Bug in pandas query() method?
I was experimenting several use cases for the pandas query() method, and tried one argument that threw an exception, but yet caused an unwanted modification to the data in my DataFrame. 我正在为pandas query()方法试验几个用例,并尝试了一个引发异常的参数,但却导致对我的DataFrame中的数据进行不必要的修改。
In [549]: syn_fmax_sort
Out[549]:
build_number name fmax
0 390 adpcm 143.45
1 390 aes 309.60
2 390 dfadd 241.02
3 390 dfdiv 10.80
....
211 413 dfmul 215.98
212 413 dfsin 11.94
213 413 gsm 194.70
214 413 jpeg 197.75
215 413 mips 202.39
216 413 mpeg2 291.29
217 413 sha 243.19
[218 rows x 3 columns]
So I wanted to use query()
to just take out a subset of this dataframe that contains all the build_number
of 392, so I tried: 所以我想使用
query()
来取出包含所有build_number
为392的数据帧的子集,所以我尝试了:
In [550]: syn_fmax_sort.query('build_number = 392')
That threw a ValueError: cannot label index with a null key
exception, but not only that, it returned back the full dataframe to me,and caused all the build_number
to be set to 392: 抛出一个
ValueError: cannot label index with a null key
异常ValueError: cannot label index with a null key
,但不仅如此,它build_number
完整的数据帧返回给我,并导致所有build_number
都设置为392:
In [551]: syn_fmax_sort
Out[551]:
build_number name fmax
0 392 adpcm 143.45
1 392 aes 309.60
2 392 dfadd 241.02
3 392 dfdiv 10.80
....
211 392 dfmul 215.98
212 392 dfsin 11.94
213 392 gsm 194.70
214 392 jpeg 197.75
215 392 mips 202.39
216 392 mpeg2 291.29
217 392 sha 243.19
[218 rows x 3 columns]
However, I have since figured out how to get value 392 only, if I used syn_fmax_sort.query('391 < build_number < 393')
, it works/ 但是,我已经弄清楚如何只获取值392,如果我使用了
syn_fmax_sort.query('391 < build_number < 393')
,它可以工作/
So my question is: Is the behavior that I observed above when I queried the dataframe wrongly due to a bug in the query()
method? 所以我的问题是:当我因
query()
方法中的错误而错误地查询数据帧时,我上面观察到的行为是什么?
It looks like you had a typo, you probably wanted to use ==
rather than =
, a simple example shows the same problem: 看起来你有一个拼写错误,你可能想使用
==
而不是=
,一个简单的例子显示了同样的问题:
In [286]:
df = pd.DataFrame({'a':np.arange(5)})
df
Out[286]:
a
0 0
1 1
2 2
3 3
4 4
In [287]:
df.query('a = 3')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-287-41cfa0572737> in <module>()
----> 1 df.query('a = 3')
C:\WinPython-64bit-3.4.2.4\python-3.4.2.amd64\lib\site-packages\pandas\core\frame.py in query(self, expr, **kwargs)
1923 # when res is multi-dimensional loc raises, but this is sometimes a
1924 # valid query
-> 1925 return self[res]
1926
1927 def eval(self, expr, **kwargs):
C:\WinPython-64bit-3.4.2.4\python-3.4.2.amd64\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
1778 return self._getitem_multilevel(key)
1779 else:
-> 1780 return self._getitem_column(key)
1781
1782 def _getitem_column(self, key):
C:\WinPython-64bit-3.4.2.4\python-3.4.2.amd64\lib\site-packages\pandas\core\frame.py in _getitem_column(self, key)
1785 # get column
1786 if self.columns.is_unique:
-> 1787 return self._get_item_cache(key)
1788
1789 # duplicate columns & possible reduce dimensionaility
C:\WinPython-64bit-3.4.2.4\python-3.4.2.amd64\lib\site-packages\pandas\core\generic.py in _get_item_cache(self, item)
1066 res = cache.get(item)
1067 if res is None:
-> 1068 values = self._data.get(item)
1069 res = self._box_item_values(item, values)
1070 cache[item] = res
C:\WinPython-64bit-3.4.2.4\python-3.4.2.amd64\lib\site-packages\pandas\core\internals.py in get(self, item, fastpath)
2856 loc = indexer.item()
2857 else:
-> 2858 raise ValueError("cannot label index with a null key")
2859
2860 return self.iget(loc, fastpath=fastpath)
ValueError: cannot label index with a null key
It looks like internally it's trying to build an index using your query and it then checks the length and as it's 0 it raises a ValueError
it probably should be KeyError
, I don't know how it's evaluated your query but perhaps it's unsupported at the moment the ability to assign values to columns. 看起来在内部它正在尝试使用您的查询构建索引,然后检查长度,因为它为0它会引发一个
ValueError
它可能应该是KeyError
,我不知道它是如何评估您的查询但也许它目前不受支持为列分配值的能力。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.