[FIX] Table: Ensure correct dtype in _compute_distributions

[ales-erjavec]

Issue

import Orange.data
from Orange.statistics import distribution

domain = Orange.data.Domain(
    [], [],
    [Orange.data.StringVariable("S"),
     Orange.data.DiscreteVariable("D", ["a", "b"])])

data = Orange.data.Table(domain, [["", 1], ["", float("nan")]])
distribution.get_distribution(data, domain.metas[1])

results in

Traceback (most recent call last):
  File "<stdin>", line 10, in <module>
  File "/Users/aleserjavec/workspace/orange3/Orange/statistics/distribution.py", line 295, in get_distribution
    return Discrete(dat, variable, unknowns)
  File "/Users/aleserjavec/workspace/orange3/Orange/statistics/distribution.py", line 39, in __new__
    return cls.from_data(dat, variable)
  File "/Users/aleserjavec/workspace/orange3/Orange/statistics/distribution.py", line 63, in from_data
    dist, unknowns = data._compute_distributions([variable])[0]
  File "/Users/aleserjavec/workspace/orange3/Orange/data/table.py", line 1317, in _compute_distributions
    dist, unknowns = bincount(m, len(var.values) - 1, W)
  File "/Users/aleserjavec/workspace/orange3/Orange/statistics/util.py", line 50, in bincount
    return (np.bincount(X.astype(np.int32, copy=False),
ValueError: cannot convert float NaN to integer

Description of changes

Ensure correct dtype in _compute_distributions when the column data comes from the metas array.

Includes

• Code changes
• Tests
• Documentation

[codecov-io]

Current coverage is 89.53% (diff: 100%)

Merging #1969 into master will increase coverage by <.01%

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