mixed type dataframe loses type info
I have a situation where joining objects of different types creates object where info() and dtypes disagree, and generally all datatypes revert to object:

In [630]: a=DataFrame(['aa','bb','cc','dd','ee'],index=[1,2,3,4,5],columns=['a'])

In [631]: b=DataFrame(randn(5,1),index=[1,2,3,4,5],columns=['b'])

In [632]: a.dtypes
Out[632]: a    object

In [633]: b.dtypes
Out[633]: b    float64

In [636]: a.info()
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, 1 to 5
Data columns:
a    5  non-null values
dtypes: object(1)

In [637]: b.info()
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, 1 to 5
Data columns:
b    5  non-null values
dtypes: float64(1)

In [638]: b['b']
Out[638]: 
1    0.182455296775
2    0.341883955748
3    -1.47860506557
4    0.227912752553
5    -0.393452694936
Name: b

In [639]: b['b'].dtype
Out[639]: dtype('float64')

In [640]: a['b']=b['b']

In [641]: a
Out[641]: 
   a   b  
1  aa  0.1825
2  bb  0.3419
3  cc -1.479 
4  dd  0.2279
5  ee -0.3935

In [642]: a.dtypes
Out[642]: 
a    object
b    object

In [643]: a.info()
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, 1 to 5
Data columns:
a    5  non-null values
b    5  non-null values
dtypes: float64(1), object(1)
In [644]: 
