.drop() reacts differently when lables changed
panads version is 0.20.2

```python
df=pd.DataFrame({'0':['x',np.nan,np.nan],'col':range(3)})
     0  col
0    x    0
1  NaN    1
2  NaN    2

df.set_index('0',inplace=True)
df
     col
0       
x      0
NaN    1
NaN    2

#df.drop(df.index[[0]])  #this can drop  reminded by TomAugspurger 
df.drop(df.index[[1]])  #this cannot
     col
0       
x      0
NaN    1
NaN    2

df.drop(df.index[[0,1]]) #drop all 
Empty DataFrame
Columns: [col]
Index: []


```
and if replace NaN(which is np.nan ) in the df with float('nan') , it will get other weirder results 

could you please tell me what leads to the problem above? Thx