Inconsistency when using .to_numpy()

[arnocandel]

Linux 0.8.0.dev561

X = dt.fread("weather_missing.csv")[-15:, 'EvapMM']
A = X.to_pandas().values
B = X.to_numpy()
print(A)
print(B)
assert np.equal(A, B).all()

[[6.6]
 [7. ]
 [9.6]
 [3.8]
 [6.8]
 [8.4]
 [5.8]
 [nan]
 [nan]
 [6.8]
 [2.4]
 [nan]
 [9.8]
 [9.2]
 [8.2]]
[[6.6]
 [7.0]
 [9.6]
 [3.8]
 [6.8]
 [8.4]
 [5.8]
 [nan]
 [nan]
 [6.8]
 [2.4]
 [--]
 [9.8]
 [9.2]
 [8.2]]

AssertionError: assert False
 +  where False = <bound method MaskedArray.all of masked_array(\n  data=[[True],\n        [True],\n        [True],\n        [True],\n       ...     [False],\n        [False],\n        [ True],\n        [False],\n        [False],\n        [False]],\n  fill_value=True)>()
 +    where <bound method MaskedArray.all of masked_array(\n  data=[[True],\n        [True],\n        [True],\n        [True],\n       ...     [False],\n        [False],\n        [ True],\n        [False],\n        [False],\n        [False]],\n  fill_value=True)> = masked_array(\n  data=[[True],\n        [True],\n        [True],\n        [True],\n        [True],\n        [True],\n        ...      [False],\n        [False],\n        [ True],\n        [False],\n        [False],\n        [False]],\n  fill_value=True).all
 +      where masked_array(\n  data=[[True],\n        [True],\n        [True],\n        [True],\n        [True],\n        [True],\n        ...      [False],\n        [False],\n        [ True],\n        [False],\n        [False],\n        [False]],\n  fill_value=True) = <ufunc 'equal'>(array([[6.6],\n       [7. ],\n       [9.6],\n       [3.8],\n       [6.8],\n       [8.4],\n       [5.8],\n       [nan],\n       [nan],\n       [6.8],\n       [2.4],\n       [nan],\n       [9.8],\n       [9.2],\n       [8.2]]), masked_array(\n  data=[[6.6],\n        [7.0],\n        [9.6],\n        [3.8],\n        [6.8],\n        [8.4],\n        [5.8],...     [False],\n        [False],\n        [ True],\n        [False],\n        [False],\n        [False]],\n  fill_value=1e+20))
 +        where <ufunc 'equal'> = np.equal

[arnocandel]

weather_missing.csv.gz