This is a constant overhead of 1 microsecond, independent of the size of the array:
```
import pandas as pd
import numpy as np

x = pd.date_range('2000-01-01', periods=1000000, freq='H').values

import pandas as pd
import numpy as np

x = pd.date_range('2000-01-01', periods=1000000, freq='H').values

%timeit np.asarray(x, 'datetime64[ns]')
%timeit x.copy()
%timeit np.asarray(x, 'datetime64[us]')
```
```
1000000 loops, best of 3: 1.37 µs per loop
1000 loops, best of 3: 816 µs per loop
100 loops, best of 3: 9.81 ms per loop
```
Unlikely to be a bottleneck for anyone :).