Y-Axis is always shared when using subplots together with twiny
#### Code Sample, a copy-pastable example if possible

```python
import matplotlib.pyplot as plt
import pandas as pd

df1 = pd.DataFrame([1, 2, 3])
df2 = pd.DataFrame([4, 5, 6])

fig, axes = plt.subplots(nrows=1, ncols=2)
df1.plot(ax=axes[0])
ax_twin = axes[1].twiny()
df1.plot(ax=axes[1])
df2.plot(ax=ax_twin)

plt.show()
```
#### Problem description

When using multiple subplots together with `twiny()` the ticks on the y-axis are always hidden (at least I could not find an easy way to make them visible).

In the example given above this is especially annoying as both y-axes are not identical:
![pandas_mwe](https://user-images.githubusercontent.com/360180/39055414-7cebcd1e-44b4-11e8-99b2-02d7aee1d820.png)

I use a fully updated anaconda with pandas version 0.22.0.

The bug is probably in the last lines of `_handle_shared_axes` in `_tools.py`, but I don't understand the code well enough to fix the issue myself.

#### Expected Output

The ticks on the y-axis of the second subplot should not be hidden.

Please tell me if there is any way I can help you.