BUG: loc should not fallback for integer indexing for multi-index

[jreback]

https://groups.google.com/forum/m/#!topic/pydata/W0e3l0UvNwI

[jtratner]

Related from that discussion: iloc fails if you give it something out of range. loc should probably fail too if there are indices not included.

[jreback]

oh it does, but right now iirc it delegates multi index handling to the ix routines (which do fallback)
should be straightforward to fix

[jtratner]

No it doesn't (that was part of what was confusing on ML):

In [3]: df = DataFrame({"A": [1, 2, 3]})

In [4]: df
Out[4]:
   A
0  1
1  2
2  3

In [6]: df.loc[['a', 'b']]
Out[6]:
    A
a NaN
b NaN

In [7]: df.loc['a']
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-7-5dbae926782f> in <module>()
----> 1 df.loc['a']

../pandas/pandas/core/indexing.pyc in __getitem__(self, key)
    958             return self._getitem_tuple(key)
    959         else:
--> 960             return self._getitem_axis(key, axis=0)
    961
    962     def _getitem_axis(self, key, axis=0):

../pandas/pandas/core/indexing.pyc in _getitem_axis(self, key, axis)
   1067             return self._getitem_iterable(key, axis=axis)
   1068         else:
-> 1069             self._has_valid_type(key,axis)
   1070             return self._get_label(key, axis=axis)
   1071

../pandas/pandas/core/indexing.pyc in _has_valid_type(self, key, axis)
   1047                 raise
   1048             except:
-> 1049                 error()
   1050
   1051         return True

../pandas/pandas/core/indexing.pyc in error()
   1034                 if isnull(key):
   1035                     raise ValueError("cannot use label indexing with a null key")
-> 1036                 raise KeyError("the label [%s] is not in the [%s]" % (key,self.obj._get_axis_name(axis)))
   1037
   1038             try:

KeyError: 'the label [a] is not in the [index]'

[jreback]

your example is as expected

a single loc raises while a list does not

[jtratner]

Okay, then we should update the docs to reflect that. It's weird that
df.iloc[[15, 20, 1000]] on a 16 element dataframe doesn't fail.

[jreback]

iloc will fail with an out-of-range, while loc won't (the reason loc will not fail as it other wise would have to scan the entire index to look for each element), its essentially a reindex, which does exactly that. You can make an argument both ways though.

In [1]: df = DataFrame(np.arange(20).reshape(20,1))

In [2]: df
Out[2]: 
     0
0    0
1    1
2    2
3    3
4    4
5    5
6    6
7    7
8    8
9    9
10  10
11  11
12  12
13  13
14  14
15  15
16  16
17  17
18  18
19  19

In [4]: df.iloc[[1,3,4,60]]
IndexError: index 60 is out of bounds for size 20

In [5]: df.loc[[1,3,4,60]]
Out[5]: 
     0
1    1
3    3
4    4
60 NaN

[jtratner]

It clearly has to scan the entire index for each element anyways, right?
Otherwise how could it know to produce nan values?

[jreback]

no its doing a hash lookup, get_indexer

[jtratner]

why would a label not be in the hash if it's in the index?

[jreback]

not sure I understand the question?

it would be in the hash if it's in the index

but remember that's only calculated once

it doesn't scan when doing lookups

just hits the index for the locs

[jtratner]

If I say, df.loc[["A", "B", "C"]], it has to do a hash lookup for each of "A", "B", "C". If it's not in the hash, then it's pretty obvious it's not in the index - right? So this would just be something like:

if (ind.get_indexer(<whatever>) == -1).any():
    raise KeyError(...)

[jreback]

not sure I understand the question

that is true but what's the point?

[jtratner]

from the docs:

.loc is strictly label based, will raise KeyError when the items are not found

[jreback]

not in a list though (guess the docs need to be updated)