BUG: Possible Regression in DatetimeIndex Slicing

[stefmolin]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

>>> import pandas as pd
>>> df = pd.DataFrame(
...     {'col1': ['a', 'b', 'c'], 'col2': [1, 2, 3]}, 
...     index=pd.to_datetime(['2020-08-01', '2020-07-02', '2020-08-05'])
... )
>>> df['2020-08']
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-82-c8d0440364af> in <module>
----> 1 df['2020-08']

~/book_env/lib/python3.7/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2880             # either we have a slice or we have a string that can be converted
   2881             #  to a slice for partial-string date indexing
-> 2882             return self._slice(indexer, axis=0)
   2883 
   2884         # Do we have a (boolean) DataFrame?

~/book_env/lib/python3.7/site-packages/pandas/core/generic.py in _slice(self, slobj, axis)
   3546         Slicing with this method is *always* positional.
   3547         """
-> 3548         assert isinstance(slobj, slice), type(slobj)
   3549         axis = self._get_block_manager_axis(axis)
   3550         result = self._constructor(self._mgr.get_slice(slobj, axis=axis))

AssertionError: <class 'numpy.ndarray'>

You now have to run sort_index() before slicing:

>>> df.sort_index()['2020-08']
           col1  col2
2020-08-01    a     1
2020-08-05    c     3

Problem description

Before 1.1.0, you didn't have to sort the index before slicing. Now, you have to run sort_index() and the error message is not helpful at all.

Expected Output

>>> df['2020-08']
           col1  col2
2020-08-01    a     1
2020-08-05    c     3

Output of pd.show_versions()

INSTALLED VERSIONS

commit : d9fff27
python : 3.7.3.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.40-04224-g891a6cce2d44
Version : #1 SMP PREEMPT Tue Jun 23 20:21:29 PDT 2020
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.0
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 18.1
setuptools : 40.8.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: 0.9.0
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : 1.3.18
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[arw2019]

xref #26206

Also - confirming this is still an issue on master.

Ouput of pd.show_versions()

INSTALLED VERSIONS

commit : 9cbc3e8
python : 3.8.3.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-42-generic
Version : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine : x86_64
processor :
byteorder : little
LC_ALL : C.UTF-8
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.2.0.dev0+17.g9cbc3e811
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.1.0.post20200704
Cython : 0.29.21
pytest : 5.4.3
hypothesis : 5.19.0
sphinx : 3.1.1
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : None
psycopg2 : 2.8.5 (dt dec pq3 ext lo64)
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fsspec : 0.7.4
fastparquet : 0.4.0
gcsfs : 0.6.2
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.0
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.50.1

[simonjayhawkins]

The assertion was added in #31938 cc @jbrockmendel

can confirm expected output prior to that change.

>>> pd.__version__
'1.1.0.dev0+460.g56cc7f4f3'
>>> df = pd.DataFrame(
...     {"col1": ["a", "b", "c"], "col2": [1, 2, 3]},
...     index=pd.to_datetime(["2020-08-01", "2020-07-02", "2020-08-05"]),
... )
>>> df["2020-08"]
           col1  col2
2020-08-01    a     1
2020-08-05    c     3
>>>

[dsaxton]

As far as I can tell this assertion can be removed (the method works fine with lists and numpy arrays it seems). In which case are the annotations for this and related arguments not correct?

[jbrockmendel]

Another fix is to add in DataFrame.__getitem__

        indexer = convert_to_index_sliceable(self, key)
        if indexer is not None:
            # either we have a slice or we have a string that can be converted
            #  to a slice for partial-string date indexing
+            if isinstance(indexer, np.ndarray):
+                indexer = lib.maybe_indices_to_slice(indexer, len(self))
            return self._slice(indexer, axis=0)