How do I convert numpy NaN objects to SQL nulls?

This answer is an alternate version of Gregory Arenius's Answer. I have replaced the conditional statement to work on any Nan value by simply checking if the value is equal to itself.

def nan_to_null(f,
         _NULL=psycopg2.extensions.AsIs('NULL')
         _Float=psycopg2.extensions.Float)):
    if f != f:
        return _NULL
    else:
         return _Float(f)

 psycopg2.extensions.register_adapter(float, nan_to_null)

If you check if a nan value is equal to itself you will get False. The rational behind why this works is explained in detail in Stephen Canon's answer.

I believe the easiest way is:

df.where(pd.notnull(df), None)

Then None is "translated": to NULL when imported to Postgres.

The code I was trying previously fails because it assumes that np.Nan is its own type when it is actually a float. The following code, courtesy of Daniele Varrazzo on the psycopg2 mailing list, does the job correctly.

def nan_to_null(f,
        _NULL=psycopg2.extensions.AsIs('NULL'),
        _Float=psycopg2.extensions.Float):
    if not np.isnan(f):
        return _Float(f)
    return _NULL

 psycopg2.extensions.register_adapter(float, nan_to_null)