Error when updating dataframe with empty filter

[Sereger13]

df = pd.DataFrame({'a': ['1', '2', '3'], 
               'b': ['11', '22', '33'], 
               'c': ['111', '222', '333']})
df.loc[df.b.isnull(), 'a'] = df.b

The filtering condition is always false (b is never null) and the above code produces this error:
Array is not broadcastable to correct shape.

If, however, I change the type for column 'c' - which is not even mentioned in the assignment expression (!) - from str to int,

df = pd.DataFrame({'a': ['1', '2', '3'], 
               'b': ['11', '22', '33'], 
               'c': [111, 222, 333]}) # Type changed to int
df.loc[df.b.isnull(), 'a'] = df.b

No errors are produced.

Would be nice to have consistent behaviour and not have any errors - could not find anything in the documentation saying that applying .loc on empty filter is considered illegal?

[jreback]

pls show pd.show_versions()

this looks like an older fixed bug

[Sereger13]

INSTALLED VERSIONS

commit: None
python: 2.7.5.final.0
python-bits: 32
OS: Linux
OS-release: 2.6.18-238.9.1.el5
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US

pandas: 0.15.0
nose: 1.3.0
Cython: 0.20
numpy: 1.7.1
scipy: 0.13.0
statsmodels: 0.5.0
IPython: 2.2.0
sphinx: 1.1.3
patsy: 0.2.1
dateutil: 1.5
pytz: 2013b
bottleneck: None
tables: 3.1.0
numexpr: 2.2.2
matplotlib: 1.3.1
openpyxl: 1.6.2
xlrd: 0.9.2
xlwt: 0.7.5
xlsxwriter: 0.5.5
lxml: None
bs4: 4.3.1
html5lib: None
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.8.3
pymysql: None
psycopg2: None

[chrisgilmerproj]

I can reproduce the bug:

In [51]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: 3e7f21ceaf9b456ab3e7c2b76166d580e321bed1
python: 2.7.9.final.0
python-bits: 64
OS: Darwin
OS-release: 14.1.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.16.0-110-g3e7f21c
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: None
statsmodels: None
IPython: 3.1.0
sphinx: None
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.2
bottleneck: 1.0.0
tables: 3.1.1
numexpr: 2.4
matplotlib: 1.4.3
openpyxl: 2.2.1
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.2
lxml: 3.4.2
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 0.9.9
pymysql: 0.6.6.None
psycopg2: None

Here's how I reproduced with python code in ipython notebook:

df = pd.DataFrame({'a': ['1', '2', '3'], 
                   'b': ['11', '22', '33'], 
                   'c': ['111', '222', '333']})


print(df.loc[df.b.isnull(), 'a'])
print(df.b)
print('')

new_s = df.loc[df.b.isnull(), 'a']
print(new_s)

new_s = df.b
print(new_s)

Output:

Series([], Name: a, dtype: object)
0    11
1    22
2    33
Name: b, dtype: object

Series([], Name: a, dtype: object)
0    11
1    22
2    33
Name: b, dtype: object

Now to show the error:

df = pd.DataFrame({'a': ['1', '2', '3'], 
                   'b': ['11', '22', '33'], 
                   'c': ['111', '222', '333']})


print(df.loc[df.b.isnull(), 'a'])
print(df.b)
print('')

df.loc[df.b.isnull(), 'a'] = df.b

Output:

Series([], Name: a, dtype: object)
0    11
1    22
2    33
Name: b, dtype: object

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-55-1af2799a791a> in <module>()
      8 print('')
      9 
---> 10 df.loc[df.b.isnull(), 'a'] = df.b

/Users/cgilmer/Projects/pandas-cgilmer/pandas/core/indexing.pyc in __setitem__(self, key, value)
    116     def __setitem__(self, key, value):
    117         indexer = self._get_setitem_indexer(key)
--> 118         self._setitem_with_indexer(indexer, value)
    119 
    120     def _has_valid_type(self, k, axis):

/Users/cgilmer/Projects/pandas-cgilmer/pandas/core/indexing.pyc in _setitem_with_indexer(self, indexer, value)
    500 
    501             # actually do the set
--> 502             self.obj._data = self.obj._data.setitem(indexer=indexer, value=value)
    503             self.obj._maybe_update_cacher(clear=True)
    504 

/Users/cgilmer/Projects/pandas-cgilmer/pandas/core/internals.pyc in setitem(self, **kwargs)
   2473 
   2474     def setitem(self, **kwargs):
-> 2475         return self.apply('setitem', **kwargs)
   2476 
   2477     def putmask(self, **kwargs):

/Users/cgilmer/Projects/pandas-cgilmer/pandas/core/internals.pyc in apply(self, f, axes, filter, do_integrity_check, **kwargs)
   2449                                                  copy=align_copy)
   2450 
-> 2451             applied = getattr(b, f)(**kwargs)
   2452 
   2453             if isinstance(applied, list):

/Users/cgilmer/Projects/pandas-cgilmer/pandas/core/internals.pyc in setitem(self, indexer, value)
    603             # set
    604             else:
--> 605                 values[indexer] = value
    606 
    607             # coerce and try to infer the dtypes of the result

ValueError: shape mismatch: value array of shape (3,) could not be broadcast to indexing result of shape (0,)

I can also verify the other behavior:

df = pd.DataFrame({'a': ['1', '2', '3'], 
                   'b': ['11', '22', '33'], 
                   'c': [111, 222, 333]}) # Type changed to int

print(df.loc[df.b.isnull(), 'a'])
print(df.b)
print('')

df.loc[df.b.isnull(), 'a'] = df.b

print('')
new_s = df.loc[df.b.isnull(), 'a']
print(new_s)
new_s = df.b
print(new_s)

Output:

Series([], Name: a, dtype: object)
0    11
1    22
2    33
Name: b, dtype: object


Series([], Name: a, dtype: object)
0    11
1    22
2    33
Name: b, dtype: object

[chrisgilmerproj]

This bug appears only when I assign df.b directly to a newly created Series object using the .loc method. It does not show when I've already assigned the new Series object to a variable. I need to perhaps know a bit more about the internals of python here but I think that assignment isn't working here. Also, what is the use case for doing this particular assignment?

[chrisgilmerproj]

Useful links:

• http://pandas.pydata.org/pandas-docs/version/0.16.0/indexing.html#different-choices-for-indexing
• http://pandas.pydata.org/pandas-docs/version/0.16.0/indexing.html#indexing-label

[chrisgilmerproj]

Something I can't do:

pd.Series([], name='a', dtype=object) = df.b

Output:

  File "<ipython-input-73-2e69376bea41>", line 1
    pd.Series([], name='a', dtype=object) = df.b
SyntaxError: can't assign to function call

[chrisgilmerproj]

I'm going to pass this over. I can't seem to make traction on it.