MultiIndex DataFrame saving to csv and loading breaks its structure.
When you save MultiIndex DataFrame to csv and then loading it with no additional parameters pandas not able to read multiindices properly and reconstructed dataframe is incorrect, however all MultiIndices are stored. Creating MultiIndex DataFrame:

``` python
>>> import pandas as pd
>>> arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux']),
np.array(['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two'])]
>>> tuples = list(zip(*arrays))
>>> index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
>>> df = pd.DataFrame(np.random.randn(6, 6), index=index[:6], columns=index[:6])
```

``` python
>>> df
first              bar                 baz                 foo          
second             one       two       one       two       one       two
first second                                                            
bar   one     0.608879 -1.128122 -0.238610  1.089921  0.521766  1.116998
      two     1.161840  0.876528 -1.417781 -1.150305 -1.043776  0.458298
baz   one     1.761382  0.634688 -1.146492 -0.082379  0.414079 -0.520011
      two     1.079547  0.667917  0.122468 -1.112053  0.408232  0.703068
foo   one    -1.031256  1.439310  0.604550 -0.275087 -0.316610 -0.589309
      two     1.730061 -1.213560 -0.581617 -0.260879  0.069140  0.970397
```

Now saving to .csv

``` python
>>> df.to_csv('test.csv')
```

File content:

```
first,,bar,bar,baz,baz,foo,foo
second,,one,two,one,two,one,two
first,second,,,,,,
bar,one,-0.218970051706,-0.37813933444,-0.7634843365,-0.704262374956,-0.839464555892,0.541422908532
bar,two,0.681850126209,-0.12138626844,0.361273042684,0.143076786043,0.89542332917,-1.4010526032
baz,one,-0.818985292735,-1.09454292831,0.162462638192,-1.03231385607,0.553385654032,0.585854960842
baz,two,-1.54054784208,1.00696690064,0.976815889071,-1.39618300884,0.283526891003,-0.942377368698
foo,one,1.08113073993,-0.29494275034,0.738820962724,-1.62865612926,1.10227198603,-0.628396328368
foo,two,0.135391399079,0.410272615409,0.59806563553,0.172448276698,0.11403085441,1.47679237362
```

Loading file:

``` python
>>> df = pd.read_csv('test.csv')
```

```
    first Unnamed: 1             bar           bar.1              baz  \
0  second        NaN             one             two              one   
1   first     second             NaN             NaN              NaN   
2     bar        one  0.608879221531  -1.12812151143  -0.238610193059   
3     bar        two   1.16184022363  0.876527615412   -1.41778054545   
4     baz        one   1.76138211998  0.634687797737   -1.14649190565   
5     baz        two    1.0795474718  0.667917354209   0.122468371132   
6     foo        one  -1.03125632895   1.43930972259   0.604550496274   
7     foo        two   1.73006141389  -1.21356047236  -0.581617481203   

              baz.1              foo            foo.1  
0               two              one              two  
1               NaN              NaN              NaN  
2     1.08992073325   0.521766323704    1.11699823915  
3    -1.15030481312   -1.04377642582   0.458297920053  
4  -0.0823790312557   0.414078987249  -0.520010569472  
5    -1.11205302607    0.40823221543   0.703068488788  
6    -0.27508709062  -0.316610246209  -0.589308900542  
7   -0.260878563358  0.0691397545038     0.9703965012 
```

Yes, I know that I need to specify columns and index parameters, but why I should do this? All information needed to restore original DataFrame with MultiIndex are already in the file. Is it possible to make it default to parse MultiIndices in csv, for example, using multiple separators in a row:

```
first,second,,,,,,
```
