Pandas Variable visibility issue with Pandas and IPython

I get a NameError exception when I try to filter DataFrame by selected index values (inside IPython session). You can see that valid is numpy.array while lab is a pandas.DataFrame object. Both of them are initialized and accessible. However I cannot put them together. Here is the error:

In [51]: valid
Out[51]: 
array([38661, 44593, 38705, 38918, 38727, 38757, 38751, 38777, 38787,
       ...,    
       45328, 45337, 43645, 43694, 43701])

In [52]: lab
Out[52]: 
         0
39333   -1
39173   -1
42756   -1
39633   -1
38661   -1
44801   81
...    ...
39379   -1
39742   -1
44765  108
44279   -1
40584   -1
41047   -1
41833   98

[3299 rows x 1 columns]

In [53]: lab[lab.index.map(lambda x: x in valid)]
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
/home/vitaly/progs/vnii_gochs/venv/lib/python2.7/site-packages/django/core/management/commands/shell.pyc in <module>()
----> 1 lab[lab.index.map(lambda x: x in valid)]

/home/vitaly/progs/vnii_gochs/venv/lib/python2.7/site-packages/pandas/core/index.pyc in map(self, mapper)
   1558 
   1559     def map(self, mapper):
-> 1560         return self._arrmap(self.values, mapper)
   1561 
   1562     def isin(self, values, level=None):

/home/vitaly/progs/vnii_gochs/venv/lib/python2.7/site-packages/pandas/algos.so in pandas.algos.arrmap_int64 (pandas/algos.c:78469)()

/home/vitaly/progs/vnii_gochs/venv/lib/python2.7/site-packages/django/core/management/commands/shell.pyc in <lambda>(x)
----> 1 lab[lab.index.map(lambda x: x in valid)]

NameError: global name 'valid' is not defined

What's wrong with this code? I use pandas 0.15.1. (This issue is a duplicate of SO's question http://stackoverflow.com/questions/27637825/variable-visibility-issue-with-pandas-and-ipython/27643446#27643446)

Comment From: jreback

looks like its trying to call a shell command (you usually need ! to do that).

In [16]: valid = np.array([100,0,300])

In [17]: lab = Series([-1,2,-1],[100,200,300])

In [18]: lab[lab.index.map(lambda x: x in valid)]
Out[18]: 
100   -1
300   -1
dtype: int64

# you should just do this in any event
In [19]: lab[lab.index.isin(valid)]
Out[19]: 
100   -1
300   -1
dtype: int64