DataFrame.loc[n] = dict(..) fails with some type combinations

Code Sample, a copy-pastable example if possible

This one fails:

# Your code here
In [9]: d = pd.DataFrame(columns=['time', 'value'])                    
In [9]: d.loc[0] = dict(time=pd.to_timedelta(5, unit='s'), value='foo')
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-9-b557eb950858> in <module>()
----> 1 d.loc[0] = dict(time=pd.to_timedelta(5, unit='s'), value='foo')

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/indexing.py in __setitem__(self, key, value)
    177             key = com._apply_if_callable(key, self.obj)
    178         indexer = self._get_setitem_indexer(key)
--> 179         self._setitem_with_indexer(indexer, value)
    180 
    181     def _has_valid_type(self, k, axis):

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/indexing.py in _setitem_with_indexer(self, indexer, value)
    423                                        name=indexer)
    424 
--> 425                     self.obj._data = self.obj.append(value)._data
    426                     self.obj._maybe_update_cacher(clear=True)
    427                     return self.obj

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/frame.py in append(self, other, ignore_index, verify_integrity)
   4628             other = DataFrame(other.values.reshape((1, len(other))),
   4629                               index=index,
-> 4630                               columns=combined_columns)
   4631             other = other._convert(datetime=True, timedelta=True)
   4632             if not self.columns.equals(combined_columns):

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy)
    304             else:
    305                 mgr = self._init_ndarray(data, index, columns, dtype=dtype,
--> 306                                          copy=copy)
    307         elif isinstance(data, (list, types.GeneratorType)):
    308             if isinstance(data, types.GeneratorType):

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/frame.py in _init_ndarray(self, values, index, columns, dtype, copy)
    481             values = maybe_infer_to_datetimelike(values)
    482 
--> 483         return create_block_manager_from_blocks([values], [columns, index])
    484 
    485     @property

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/internals.py in create_block_manager_from_blocks(blocks, axes)
   4294                                      placement=slice(0, len(axes[0])))]
   4295 
-> 4296         mgr = BlockManager(blocks, axes)
   4297         mgr._consolidate_inplace()
   4298         return mgr

/home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/pandas/core/internals.py in __init__(self, blocks, axes, do_integrity_check, fastpath)
   2790                     raise AssertionError('Number of Block dimensions (%d) '
   2791                                          'must equal number of axes (%d)' %
-> 2792                                          (block.ndim, self.ndim))
   2793 
   2794         if do_integrity_check:

AssertionError: Number of Block dimensions (1) must equal number of axes (2)

But this one succeeds:

In [11]: d.loc[0] = dict(time=pd.to_timedelta(5, unit='s'), value=5)

In [12]: d
Out[12]: 
      time value
0 00:00:05     5

This one also succeeds:

In [13]: d = pd.DataFrame(columns=['time', 'value'])

In [14]: d.loc[0] = dict(time=3, value='foo')

In [15]: d
Out[15]: 
  time value
0    3   foo

Problem description

[this should explain why the current behaviour is a problem and why the expected output is a better solution.]

The current behavior is a problem because it is inconsistent, and depends on the type of data provided. Mixing timedelta with str fails, but timedelta with int works, as does int with str.

I believe this is related to aggressive type inference previously noted in #13829.

Expected Output

Not crashing.

Output of pd.show_versions()

In [16]: pd.show_versions() /home/bmcfee/miniconda/envs/py35/lib/python3.5/site-packages/xarray/core/formatting.py:16: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version. from pandas.tslib import OutOfBoundsDatetime

INSTALLED VERSIONS

commit: None python: 3.5.3.final.0 python-bits: 64 OS: Linux OS-release: 4.4.0-77-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8

pandas: 0.20.1 pytest: 3.0.7 pip: 9.0.1 setuptools: 35.0.2 Cython: 0.25.2 numpy: 1.12.1 scipy: 0.19.0 xarray: 0.9.5 IPython: 6.0.0 sphinx: 1.5.5 patsy: 0.4.1 dateutil: 2.6.0 pytz: 2017.2 blosc: None bottleneck: 1.2.0 tables: None numexpr: 2.6.0 feather: None matplotlib: 2.0.1 openpyxl: None xlrd: 1.0.0 xlwt: None xlsxwriter: None lxml: None bs4: None html5lib: 0.999 sqlalchemy: 1.0.9 pymysql: None psycopg2: None jinja2: 2.9.5 s3fs: 0.1.0 pandas_gbq: None pandas_datareader: None

[jorisvandenbossche]

Ah, yes, I see that as well (so when the label already exists). This already is raising in 0.19.2, so not a new bug …

[phofl]

Works now, setting once and setting twice