PERF: Possible performance regression for indexing from 0.12 to 0.13.1
Hey all,

Just upgraded my pandas version from 0.12 to 0.13.1 and noticed a significant performance regression for indexing operations (get, set, and windowing). 

Here is my test setup code:

``` python
import pandas as pd

ts1 = pd.TimeSeries(data=100.0, index=pd.date_range('2000-01-01', periods=1000))
ts2 = pd.TimeSeries(data=200.0, index=pd.date_range('2000-01-01', periods=1000))
ts3 = pd.TimeSeries(data=300.0, index=pd.date_range('2000-01-01', periods=1000))
df = pd.DataFrame({'ts1': ts1, 'ts2': ts2, 'ts3': ts3})

dt = ts1.index[500]
```

Here is a table showing the results of IPython's %timeit function. 

| test | 0.12 | 0.13.1 |
| --- | --- | --- |
| ts1[dt] | 3.78 | 8.5 |
| ts1.ix[dt] | 11.8 | 30.7 |
| ts1.loc[dt] | 12.7 | 37.7 |
| ts1[dt]=1 | 1.86 | 4.32 |
| ts1.ix[dt]=1 | 12.5 | 65.9 |
| ts1.loc[df]=1 | 36.2 | 65.7 |
| ts1[:dt] | 78.2 | 101 |
| ts1.ix [:dt] | 53.1 | 106 |
| ts1.loc [:dt] | 59.5 | 101 |
| df.ix[dt] | 45.3 | 77.9 |
| df.ix [:dt] | 63.3 | 85.9 |

I did not see up-to-date data on http://pandas.pydata.org/pandas-docs/vbench/vb_indexing.html - am I looking at the right benchmark data? Most charts end in June 2012. 

Can someone confirm this slowdown?

I am using numpy 1.8.1 by the way - let me know if you need any other version numbers.

Thanks in advance!
