Using scipy's entropy function with "string" dtype
Hello, 

I calculate entropies of real valued random variables thanks to `pandas` and `scipy.stats`. For some practical reason, I bin my df's values with `pd.cut` and the `labels` I assign to these binned valued has to be a string. I wanted to use the new "string" dtype introduced in 1.0.0, but there seems to be an issue, here is a code sample : 

```
import pandas as pd 
import numpy as np 
from scipy.stats import entropy 
 
df = pd.DataFrame({'val': np.random.rand(1000)}) 
bins = np.linspace(0, 1, 11)
labels = [str(int(10*i)) for i in bins[:-1]] 
 
df['bin_val'] = pd.cut(df['val'], bins=bins, labels=labels) 
# This works
print(entropy(df['bin_val'].value_counts())) 
 
df['bin_val'] = df['bin_val'].astype("string") 
# This raises an error
print(entropy(df['bin_val'].value_counts()))
```

The error raised is `TypeError: ufunc 'entr' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''`