Correction in DatetimeIndex in Time Series documentation

[kentwait]

In the Time Series documentation (http://pandas.pydata.org/pandas-docs/stable/timeseries.html), DatetimeIndex is said to have the following functionality:

In [1118]: ts['2011']
Out[1118]: 
2011-01-31   -1.281247
2011-02-28   -0.727707
2011-03-31   -0.121306
2011-04-29   -0.097883
2011-05-31    0.695775
2011-06-30    0.341734
2011-07-29    0.959726
2011-08-31   -1.110336
2011-09-30   -0.619976
2011-10-31    0.149748
2011-11-30   -0.732339
2011-12-30    0.687738
Freq: BM

In [1119]: ts['2011-6']
Out[1119]: 
2011-06-30    0.341734
Freq: BM

I have tried it out in pandas 0.9.1 but it doesn't work.

What does work is ts.ix['2011'] and ts.ix['2011-6]. I hope you correct this misleading mistake. There are a couple more examples of these on that page so please check it out.

[changhiskhan]

This works on master and 0.9.1 for me. Can you show me a standalone reproduction of how it's not working for you?

[kentwait]

Now I see where I misunderstood it. The examples were all <class 'pandas.core.series.TimeSeries'> objects and naturally Series['filter'] will work for a Series but it will not work for a DataFrame.

I guess I just assumed that it the example was true for any data structure with a Datetime index.

[changhiskhan]

Ah i see. Yeah, DataFrame[label] assume you want to access a column.

[e9t]

It would be wonderful to have this feature for data frames as well.

[jreback]

this is in 0.11.0 via #3137