KeyError after resampling - pandas

Question

I have two dataframes df indexed by Datetime and df2 which has column Date (Series).
Before resampling I can run:
>>>> df[df2['Date'][0]]
and obtain all rows corresponding to day df2['Date'][0] which is 2013-08-07 in this example. However after resampling by day I can no longer obtain the row corresponding to that day as:
>>>> df.resample('D', how=np.max)[df2['Date'][0]]
KeyError: u'no item named 2013-08-07'
although that day is in the dataset
>>>> df.resample('D', how=np.max).head()
| Temp | etc
Date | |
---------------------------
2013-08-07 | 26.1 |
---------------------------
2013-08-08 | 28.2 |
---------------------------
etc

Answer 1

I am not sure whether it is a bug or it is designed to be like this, or, if the latter is true, why. But you can do this to get the desired result:
In [168]:
df1=pd.DataFrame(np.random.random(100), columns=['Temp'])
df1.index=pd.date_range('2013-08-07',periods=100,freq='5H')
df1.index.name='Date'
In [169]:
df2=pd.DataFrame(pd.date_range('2013-08-07',periods=23, freq='D'), columns=['Date'])
In [170]:
#You can do this
df3=df1.resample('D', how=np.max)
print df3[df3.index==df2['Date'][0]]
Temp
Date
2013-08-07 0.8128
[1 rows x 1 columns]
In [171]:
df3[df2['Date'][0]]
#Error