QST: Why does reading CSV dates return datetime instead of Timestamp?
_Problem description:_
I'm reading CSV historical prices data with `pandas.read_csv(...),` but the problem is with reading the dates column - I want the values to be in `pandas.Timestamp` type, but the method returns them in `datetime` instead.

_Question:_
**What's wrong here?**
Why does pandas return `<class 'datetime.datetime'>` instead of `<class 'pandas._libs.tslibs.timestamps.Timestamp'>`, and how could I read in the Timestamp?

_Data example:_
```
Local time | Open | High | Low | Close | Volume
28.02.2014 02:00:00.000 GMT+0200 | 1.37067 | 1.3825 | 1.36943 | 1.38042 | 176839
```

_Reading attempts:_
1. 

```
data = pd.read_csv(fp, parse_dates = ["Local time"], dtype={'Local time': pd.Timestamp})
#data = pd.read_csv(fp, dtype={'Local time': pd.Timestamp})
```
Result: `TypeError: dtype '<class 'pandas._libs.tslibs.timestamps.Timestamp'>' not understood`.

2. 
```
data = pd.read_csv(fp, parse_dates = ["Local time"])
print(type(data['Local time'][0]))
```
Result: `<class 'datetime.datetime'>`.

3.
```
data = pd.read_csv(fp, parse_dates = ["Local time"])
print(type(pd.Timestamp(data['Local time'][0])))
```
Result: `<class 'pandas._libs.tslibs.timestamps.Timestamp'>`.