Converting numpy array of strings to Series is much slower than with a list
#### Code Sample, a copy-pastable example if possible

```python
>>> a_list = ['string'] * 1000000
>>> arr = np.array(a_list)

>>> %timeit pd.Series(a_list)
15.5 ms ± 254 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

>>> %timeit pd.Series(arr)
83.8 ms ± 5.22 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

>>> arr2 = np.random.rand(1000000)
>>> %timeit pd.Series(arr2)
24.8 µs ± 970 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```
#### Problem description

Usually converting a Numpy array to a Series is much faster than the same data in a list, but with strings, it's much slower (5x in this example).

Converting an array of 1 million random numbers to a Series is 3000x faster.