Not possible to find first element in non-monotonic DateTimeIndex if string is used

[tjader]

There is an inconsistency when you look for dates in a DateTimeIndex if you query using strings and the index is non-monotonic. The first element in the index cannot be found in this way, but if you manually convert it to a timestamp object, or if you look for elements other than the first, then the lookup is successful.

Code Sample, a copy-pastable example if possible

>>> import pandas as pd
>>> idx = pd.to_datetime(['2015-01-01', '2015-01-02', '2015-01-05', '2015-01-04'])
>>> idx
Out[38]: DatetimeIndex(['2015-01-01', '2015-01-02', '2015-01-05', '2015-01-04'], dtype='datetime64[ns]', freq=None)
>>> idx.is_monotonic
Out[29]: False
>>> idx = pd.to_datetime(['2015-01-01', '2015-01-02', '2015-01-05', '2015-01-04'])
>>> '2015-01-01' in idx  # This should work
Out[31]: False
>>> pd.Timestamp('2015-01-01') in idx
Out[32]: True
>>> '2015-01-02' in idx
Out[33]: True
>>> '2015-01-04' in idx
Out[34]: True

Expected Output

>>> '2015-01-01' in idx
Out[31]: True

output of pd.show_versions()

>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-573.7.1.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: 1.3.7.commod
pip: 8.1.2
setuptools: 23.0.0
Cython: 0.24
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
xarray: 0.7.2
IPython: 4.1.2
sphinx: 1.3.5
patsy: 0.4.1
dateutil: 2.5.2
pytz: 2016.4
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5.2
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.3.2
html5lib: 0.999
httplib2: 0.9.2
apiclient: 1.5.0
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
pandas_datareader: None

[TomAugspurger]

Thanks for the report.

The cause seems to be somewhere around here where DatetimeIndex._get_string_slice('2015-01-01') returns a np.array([0]), we return that, which gets np.any called on it, which is False since bool(0) is False.

So the monotonicity is a bit of a red herring, the real problem is that the matching key is in the 0th position.

Interested in submitting a fix? Shouldn't be too bad.

[jreback]

this is already clearly documented here: http://pandas.pydata.org/pandas-docs/version/0.18.1/gotchas.html#label-based-slicing-conventions

[TomAugspurger]

@jreback This seems strange though, right (on the original idx)

In [88]: '2015-01-02' in idx
Out[88]: True

In [89]: '2015-01-01' in idx
Out[89]: False

The only difference being that the '2015-01-01' happened to be the first element. I think that we can fix this at least for __contains__ in the non-monotonic case.

[tjader]

@TomAugspurger The code takes quite a different path if the index is monotonic, starting when a KeyError is raised inside DatetimeIndex._partial_date_slice, so I wouldn't say it's a complete red herring.
Anyway, I think it looks reasonable to swap np.any for np.size in contains instead.

[TomAugspurger]

Right, red herring was probably the wrong phrase to use since non-monotonicity is necessary for the bug to occur 😄

[harshit-ag]

can i work on this issue?

[toobaz]

This was apparently fixed:

In [1]: import pandas as pd                                                                                                                                                                                                                   

In [2]: idx = pd.to_datetime(['2015-01-01', '2015-01-02', '2015-01-05', '2015-01-04'])                                                                                                                                                        

In [3]: '2015-01-01' in idx                                                                                                                                                                                                                   
Out[3]: True

Please reopen if it still can be reproduced.