How to select a row in a pandas DataFrame datetime index using a datetime variable?

Question

I am not a Professional programmer at all and slowly accumulating some experience in python. This is the issue I encounter.

On my dev machine I had a python3.7 installed with pandas version 0.24.4

the following sequence was working perfectly fine.

 >>> import pandas as pd
 >>> df = pd.Series(range(3), index=pd.date_range("2000", freq="D", periods=3))

>>> df
2000-01-01    0
2000-01-02    1
2000-01-03    2
Freq: D, dtype: int64

>>> import datetime
>>> D = datetime.date(2000,1,1)
>>> df[D]
0

in the production environnent the pandas version is 1.1.4 and the sequence described does not work anymore.

>>> df[D]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/ec2-user/.local/lib/python3.7/site-packages/pandas/core/series.py", line 882, in __getitem__
    return self._get_value(key)
  File "/home/ec2-user/.local/lib/python3.7/site-packages/pandas/core/series.py", line 989, in _get_value
    loc = self.index.get_loc(label)
  File "/home/ec2-user/.local/lib/python3.7/site-packages/pandas/core/indexes/datetimes.py", line 622, in get_loc
    raise KeyError(key)
KeyError: datetime.date(2000, 1, 1)

Then, unexpectedly, by transforming D in a string type the following command did work :

>>> df[str(D)]
0

Any idea of why this behaviour has changed in the different versions ? Is this behaviour a bug or will be permanent over time ? should I transform all the selections by datetime variables in the code in string variables or is there a more robust way over time to do this ?

jezrael · Accepted Answer · 2021-09-02 08:33:54Z

1

It depends of version. If need more robust solution use datetimes for match DatetimeIndex:

import datetime
D = datetime.datetime(2000,1,1)

print (df[D])
0

answered Sep 2, 2021 at 8:33

jezrael

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