I have the following `DataFrame`:

```
df_1 = DataFrame({
        "alpha" : [1,1,1,2,2,2,3,3,3] ,
        "beta" : [3,4,5,3,4,5,3,4,5] ,
        "val_1" : ["x", "y" , "z", "w", "a", "b", "v1" , "v2" , "v3" ] ,
        "val_2" : ["z1", "z2" , "z3", "w1", "w2", "w3" , "zz1" , "zz2" , "zz3" ]
    })
df_1.set_index(["alpha", "beta"], inplace=True)

```

I am trying to select the following highlighted rows:

[![enter image description here](https://i.stack.imgur.com/uGM8C.png)](https://i.stack.imgur.com/uGM8C.png)

That is, every row where `beta` is either 3 or 5.

I have gone through the pandas documentation multiple times and cannot find a way to do this. The closest I've come to what I think must be the answer is:

```
df_1.xs((3,5), level="beta", drop_level=False)

```

Which now currently fails. What is the proper indexing/slicing way to get this?