benfordslaw.fit doesn't work on pandas Series with Int64Dtype (nullable)

[ThomasOfferman]

Hi Erdogan,

I was recently working with a pandas DataFrame that had a column with a Int64Dtype, which is nullable. The column didn't actually have any null-values. This gave me the following error:

  File "/usr/local/lib/python3.8/dist-packages/benfordslaw/benfordslaw.py", line 293, in _count_digit
    digits[Iloc] = list(map(lambda x: int(str(x)[d]), data[Iloc]))
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid `indices`

I looked into it and it's because the nullable int also produces a nullable boolean series. So the variable Iloc was actually a nullable boolean, which I guess isn't supported by numpy. See below for a small reproducable example.

import pandas 
from benfordslaw import benfordslaw

bl = benfordslaw(alpha=0.05)

data = pandas.DataFrame({'value': [1,2,3,4,5]})
bl.fit(data['value'].astype(int)) # this works fine 
bl.fit(data['value'].astype(pandas.Int64Dtype())) #this throws an error

I feel like something like this would solve it (not tested):

# Get the ith digit
digits = np.zeros_like(data)
Iloc = data>=np.power(10, d)
# ignore nulls and cast to non-nullable dtype just in case
Iloc = Iloc.fillna(False).astype(bool)
digits[Iloc] = list(map(lambda x: int(str(x)[d]), data[Iloc]))

I wouldn't mind making a pull request with some test cases. But I'll leave it up to you, I can also imagine this is not a high priority since I think the nullable IntDtype is still pretty experimental.

Kind regards,
Thomas

[erdogant]

Thank you! I implemented your solution.
update with: pip install -U benfordslaw