Drop with boolean raises a ValueError

[jseabold]

Shouldn't this work?

>>> pd.version.version
'0.13.0-472-g9109812'

>>> df = pd.DataFrame(np.random.random((10,4)))

>>> df = df.drop(df[0] > .5)

>>> df.drop(df[0] < .2)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-23-5df7f56de272> in <module>()
----> 1 df.drop(df[0] > .5)

/usr/local/lib/python2.7/dist-packages/pandas-0.13.0_472_g9109812-py2.7-linux-x86_64.egg/pandas/core/generic.pyc in drop(self, labels, axis, level, inplace, **kwargs)
   1397                 new_axis = axis.drop(labels, level=level)
   1398             else:
-> 1399                 new_axis = axis.drop(labels)
   1400             dropped = self.reindex(**{axis_name: new_axis})
   1401             try:

/usr/local/lib/python2.7/dist-packages/pandas-0.13.0_472_g9109812-py2.7-linux-x86_64.egg/pandas/core/index.pyc in drop(self, labels)
   1621         mask = indexer == -1
   1622         if mask.any():
-> 1623             raise ValueError('labels %s not contained in axis' % labels[mask])
   1624         return self.delete(indexer)
   1625 

ValueError: labels [False False  True  True  True  True  True False] not contained in axis

[jreback]

AFAICT this is not supported, labels has to be a label of the axis; I think the first one 'happens' to work. That said I don't think this is hard to fix.

[jseabold]

That's what I suspected. I was wondering if boolean for drop was supported given that I couldn't for the life of me reproduce the error. Then I realized it was on the second one and it had to do with the labels being different. Consider this a feature request then. Drop is nice and expressive. Would be nice if it supported boolean indexing.

[jreback]

yep...its really just a front end to ix...so pretty easy (it just needs to NOT convert a boolean indexer from labels)

[jreback]

I believe #6599 should take care of this