read_csv getting TypeError with decimal.Decimal type
#### Code sample

We read in a two column, two row file test_data.csv, 
that looks like the following:
x, y
1, 2

```python
import decimal

import pandas as pd

d = pd.read_csv("test_data.csv", dtype={'y': decimal.Decimal})
```
#### Problem description

I have been using pandas.read_csv and passing `dtype={'some_column': decimal.Decimal}` as a keyword argument with pandas version 0.19.2. In pandas version 0.20.x, this no longer works and I receive the following error: 

`TypeError: dtype <class 'decimal.Decimal'> not understood`

I can get around this error by instead reading in with the str data type, e.g. `dtype={'some_column': str}`. The end result is the same, as I have to manually cast the numeric data to the decimal.Decimal type after reading. However, I think the former approach is better as it is more explicit that the particular column's data should be treated as the decimal.Decimal. 

Is this expected behavior? It seems like a regression. Any additional general thoughts on working with decimal.Decimal data in pandas DataFrame (and numpy array) objects are also welcome. 