gistfile1.txt

import numpy as np
import pandas as pd
nan = np.nan

def array_equivalent(a1, a2):
     try:
         a1, a2 = np.asarray(a1), np.asarray(a2)
     except (TypeError, ValueError):
         return False
     a1_mask = pd.isnull(a1)
     a2_mask = pd.isnull(a2)
     if np.isscalar(a1_mask):
         return (np.isscalar(a2_mask)
                 and ((a1_mask and a2_mask)       # both are nans
                      or a1 == a2))               # they compare equal
     else:
         result = (a1.shape == a2.shape
                 and (a1_mask == a2_mask).all()
                 and np.array_equal(a1[~a1_mask], a2[~a2_mask]))
         return result

def array_equivalent2(a1, a2):
    try:
        a1, a2 = np.asarray(a1), np.asarray(a2)
    except (TypeError, ValueError):
        return False
    result = (a1.shape == a2.shape) and ((a1 == a2) | ((a1 != a1) & (a2 != a2))).all()
    return result

left = pd.Float64Index([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, nan], dtype='object')
right = pd.Float64Index([1.0, 2.0, 3.0, 4.0, 5.0, 6.0, nan], dtype='object')

print(array_equivalent(left, right))
# True
print(array_equivalent2(left, right))
# False

print(left != left)
# [False False False False False False False]