I want to merge two Pandas DataFrames, but anywhere an index matches I only want to merge in the row from a specific `df`.

So if I have

```
df1
             A  B
type   model
apple  v1    10 xyz
orange v2    11 pqs

df2
             A  B
type   model
apple  v3    11 xyz
grape  v4    12 def

```

I would get

```
df3 
             A  B
type   model
apple  v1    10 xyz
orange v2    11 pqs
grape  v4    12 def

```

Because `df1.ix['apple']` takes precedence over `df2.ix['apple']`, and `orange` and `grape` are unique.

I have been trying to make some index comparison work, but `df2.drop(df1.index[[0]])` is just removing the entire contents of `df2`.

Both data frames are multi-indexed with a similar structure, created by:

`pd.read_csv(..., index_col=[3, 1])`

Which results in an index like this:

```
MultiIndex(
  levels=[[u'apple', u'orange', u'grape', ...], [u'v1', u'v2', u'v3', ... ]],
  labels=[[0, 1, 2, 3, 4, 6, 7, 8, 9, 10, ...]],
  names=[u'type', u'model']
)

```