python pandas dataframe slicing by date conditions

Question

I am able to read and slice pandas dataframe using python datetime objects, however I am forced to use only existing dates in index. For example, this works:

Answer 1

Short answer: Sort your data (data.sort()) and then I think everything will work the way you are expecting.

Yes, you can slice using datetimes not present in the DataFrame. For example:

In [12]: df
Out[12]: 
                   0
2013-04-20  1.120024
2013-04-21 -0.721101
2013-04-22  0.379392
2013-04-23  0.924535
2013-04-24  0.531902
2013-04-25 -0.957936

In [13]: df['20130419':'20130422']
Out[13]: 
                   0
2013-04-20  1.120024
2013-04-21 -0.721101
2013-04-22  0.379392

As you can see, you don't even have to build datetime objects; strings work.

Because the datetimes in your index are not sequential, the behavior is weird. If we shuffle the index of my example here...

In [17]: df
Out[17]: 
                   0
2013-04-22  1.120024
2013-04-20 -0.721101
2013-04-24  0.379392
2013-04-23  0.924535
2013-04-21  0.531902
2013-04-25 -0.957936

...and take the same slice, we get a different result. It returns the first element inside the range and stops at the first element outside the range.

In [18]: df['20130419':'20130422']
Out[18]: 
                   0
2013-04-22  1.120024
2013-04-20 -0.721101
2013-04-24  0.379392

This is probably not useful behavior. If you want to select ranges of dates, would it make sense to sort it by date first?

df.sort_index()