dataframe.appy behavior changed between 0.20.0 and 0.20.3
```python
import pandas as pd
from pyspark.ml.linalg import Vectors

df = pd.DataFrame({'A': [1,2,3,4], 
                   'B': [1,2,3,4], 
                   'C': [1,2,3,4],
                   'D': [1,2,3,4]},
                   index=[0, 1, 2, 3])
df.apply(lambda x: pd.Series(Vectors.dense([x["A"], x["B"]])), axis=1)
```
#### Problem description

This produces from pandas 0.20.0:

                0
    0  [1.0, 1.0]
    1  [2.0, 2.0]
    2  [3.0, 3.0]
    3  [4.0, 4.0]

but it is different in pandas 0.20.3:

         0    1
    0  1.0  1.0
    1  2.0  2.0
    2  3.0  3.0
    3  4.0  4.0

How can I achieve the first behavior in 0.20.3?
I am not saying the current behavior is worse than the old one. I don't see any description in "What's New".
I need the old behavior to work with DenseVector in PySpark MLlib.
Thanks,
