Code
In [33]: df = pd.DataFrame({'date1': [Timestamp('2017-05-25 14:02:23'), NaT],
'date2': [Timestamp('2017-05-25 14:34:43'), Timestamp('2017-05-16 19:37:43')]})
In [34]: df2 = df.apply(lambda x: x.dt.tz_localize('UTC'), axis=0)
In [35]: df3 = df2.assign(date1=df2.date2)
In [36]: df
Out[36]:
date1 date2
0 2017-05-25 14:02:23 2017-05-25 14:34:43
1 NaT 2017-05-16 19:37:43
In [37]: df2
Out[37]:
date1 date2
0 2017-05-25 14:02:23+00:00 2017-05-25 14:34:43+00:00
1 NaT 2017-05-16 19:37:43+00:00
In [38]: df3
Out[38]:
date1 date2
0 2017-05-25 14:34:43+00:00 2017-05-25 14:34:43+00:00
1 2017-05-16 19:37:43+00:00 2017-05-16 19:37:43+00:00
In [39]: df.dtypes
Out[39]:
date1 datetime64[ns]
date2 datetime64[ns]
dtype: object
In [40]: df2.dtypes
Out[40]:
date1 datetime64[ns, UTC]
date2 datetime64[ns, UTC]
dtype: object
In [41]: df3.dtypes
Out[41]:
date1 datetime64[ns, UTC]
date2 datetime64[ns, UTC]
dtype: object
In [42]: df.T
Out[42]:
0 1
date1 2017-05-25 14:02:23 NaT
date2 2017-05-25 14:34:43 2017-05-16 19:37:43
In [43]: df2.T
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-43-7d2317a1beae> in <module>()
----> 1 df2.T
e:\github\pandas\pandas\core\frame.pyc in transpose(self, *args, **kwargs)
1876 """Transpose index and columns"""
1877 nv.validate_transpose(args, dict())
-> 1878 return super(DataFrame, self).transpose(1, 0, **kwargs)
1879
1880 T = property(transpose)
e:\github\pandas\pandas\core\generic.pyc in transpose(self, *args, **kwargs)
600
601 nv.validate_transpose_for_generic(self, kwargs)
--> 602 return self._constructor(new_values, **new_axes).__finalize__(self)
603
604 def swapaxes(self, axis1, axis2, copy=True):
e:\github\pandas\pandas\core\frame.pyc in __init__(self, data, index, columns, dtype, copy)
350 else:
351 mgr = self._init_ndarray(data, index, columns, dtype=dtype,
--> 352 copy=copy)
353 elif isinstance(data, (list, types.GeneratorType)):
354 if isinstance(data, types.GeneratorType):
e:\github\pandas\pandas\core\frame.pyc in _init_ndarray(self, values, index, columns, dtype, copy)
522 values = maybe_infer_to_datetimelike(values)
523
--> 524 return create_block_manager_from_blocks([values], [columns, index])
525
526 @property
e:\github\pandas\pandas\core\internals.pyc in create_block_manager_from_blocks(blocks, axes)
4378 placement=slice(0, len(axes[0])))]
4379
-> 4380 mgr = BlockManager(blocks, axes)
4381 mgr._consolidate_inplace()
4382 return mgr
e:\github\pandas\pandas\core\internals.pyc in __init__(self, blocks, axes, do_integrity_check, fastpath)
2880 raise AssertionError('Number of Block dimensions (%d) '
2881 'must equal number of axes (%d)' %
-> 2882 (block.ndim, self.ndim))
2883
2884 if do_integrity_check:
AssertionError: Number of Block dimensions (1) must equal number of axes (2)
Problem description
Transpose on dataframe with timestamps columns work. But, if columns consist of timestamps with time-zone, it fails.
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.21.0.dev+413.g7f93d2d
pytest: 3.2.0
pip: 9.0.1
setuptools: 36.2.7
Cython: 0.24.1
numpy: 1.12.1
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2017.2
blosc: None
bottleneck: 1.2.0
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: 0.999999999
sqlalchemy: 1.0.13
pymysql: 0.7.9.None
psycopg2: 2.7.3.1 (dt dec pq3 ext lo64)
jinja2: 2.8
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
Comment From: pratapvardhan
Another case, where error indicates ValueError: the 'axes' parameter is not supported in the pandas implementation of transpose(), this operation works fine on non-timezone set timestamp columns.
In [64]: pd.DataFrame(pd.date_range(pd.to_datetime('now'), periods=2, freq='D'))
Out[64]:
0
0 2017-09-15 10:49:12
1 2017-09-16 10:49:12
In [65]: pd.DataFrame(pd.date_range(pd.to_datetime('now'), periods=2, freq='D', tz='UTC'))
Out[65]:
0
0 2017-09-15 10:49:14+00:00
1 2017-09-16 10:49:14+00:00
In [66]: pd.DataFrame(pd.date_range(pd.to_datetime('now'), periods=2, freq='D')).T
Out[66]:
0 1
0 2017-09-15 10:49:16 2017-09-16 10:49:16
In [67]: pd.DataFrame(pd.date_range(pd.to_datetime('now'), periods=2, freq='D', tz='UTC')).T
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-67-3ba6caaa2c38> in <module>()
----> 1 pd.DataFrame(pd.date_range(pd.to_datetime('now'), periods=2, freq='D', tz='UTC')).T
e:\github\pandas\pandas\core\frame.pyc in transpose(self, *args, **kwargs)
1876 """Transpose index and columns"""
1877 nv.validate_transpose(args, dict())
-> 1878 return super(DataFrame, self).transpose(1, 0, **kwargs)
1879
1880 T = property(transpose)
e:\github\pandas\pandas\core\generic.pyc in transpose(self, *args, **kwargs)
595 new_axes = self._construct_axes_dict_from(self, [self._get_axis(x)
596 for x in axes_names])
--> 597 new_values = self.values.transpose(axes_numbers)
598 if kwargs.pop('copy', None) or (len(args) and args[-1]):
599 new_values = new_values.copy()
e:\github\pandas\pandas\core\base.pyc in transpose(self, *args, **kwargs)
782 def transpose(self, *args, **kwargs):
783 """ return the transpose, which is by definition self """
--> 784 nv.validate_transpose(args, kwargs)
785 return self
786
e:\github\pandas\pandas\compat\numpy\function.pyc in __call__(self, args, kwargs, fname, max_fname_arg_count, method)
52 validate_args_and_kwargs(fname, args, kwargs,
53 max_fname_arg_count,
---> 54 self.defaults)
55 else:
56 raise ValueError("invalid validation method "
e:\github\pandas\pandas\util\_validators.pyc in validate_args_and_kwargs(fname, args, kwargs, max_fname_arg_count, compat_args)
215
216 kwargs.update(args_dict)
--> 217 validate_kwargs(fname, kwargs, compat_args)
218
219
e:\github\pandas\pandas\util\_validators.pyc in validate_kwargs(fname, kwargs, compat_args)
154 kwds = kwargs.copy()
155 _check_for_invalid_keys(fname, kwargs, compat_args)
--> 156 _check_for_default_values(fname, kwds, compat_args)
157
158
e:\github\pandas\pandas\util\_validators.pyc in _check_for_default_values(fname, arg_val_dict, compat_args)
66 "supported in the pandas "
67 "implementation of {fname}()".
---> 68 format(fname=fname, arg=key)))
69
70
ValueError: the 'axes' parameter is not supported in the pandas implementation of transpose()
Comment From: jreback
this is a manifestation and duplicate of https://github.com/pandas-dev/pandas/issues/13287
Comment From: jreback
pull requests to fix are welcome
Comment From: pratapvardhan
Ah, thanks, apologies didn't search enough. Is that issue also causing max(axis=1) on tz-aware timestamps to goof up?
In [108]: pd.DataFrame(pd.date_range('2014', periods=2, freq='D')).max(axis=1)
Out[108]:
0 2014-01-01
1 2014-01-02
dtype: datetime64[ns]
In [109]: pd.DataFrame(pd.date_range('2014', periods=2, freq='D', tz='UTC')).max(axis=1)
Out[109]:
0 NaN
1 NaN
dtype: float64