Add support for NaN equality within Arrays

When trying to assert_df_equality with allow_nan_equality=True, if the both DataFrames hold an array that contains some nan values then the comparer fails, even if the nans are in the same place.

An additional check should take place here to compare the array elements.

chispa/chispa/row_comparer.py

Lines 16 to 20 in 500793e

    
           if allow_nan_equality: 
        
               for key in d1.keys() & d2.keys(): 
        
                   if not(nan_safe_equality(d1[key], d2[key])): 
        
                       return False 
        
               return True

Again, I can help contribute to this one but it won't be until next week.

Here's a comparison example:

Yes, this would be a good addition, and no rush, whenever you get around to it! Thanks so much for the help!!

@MrPowers

Hi @MrPowers , just a note to say I have a pull request on this sitting ready to go. I branched off the changes on #29 though because it made sense to get that one through first. I'm just wondering what your timeline might be for a further review of the impact of #29? Some of the features would be useful to me currently.

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Add support for NaN equality within Arrays #27

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	if allow_nan_equality:
	for key in d1.keys() & d2.keys():
	if not(nan_safe_equality(d1[key], d2[key])):
	return False
	return True

Add support for NaN equality within Arrays #27

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MrPowers commented on Apr 22, 2021

mitches-got-glitches commented on May 10, 2021

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