Comparing missing values

Pandas uses the NumPy NaN (np.nan) object to represent a missing value. This is an unusual object, as it is not equal to itself. Even Python's None object evaluates as True when compared to itself:

>>> np.nan == np.nan
False
>>> None == None
True

All other comparisons against np.nan also return False, except not equal to:

>>> np.nan > 5
False
>>> 5 > np.nan
False
>>> np.nan != 5
True

Getting ready

Series and DataFrames use the equals operator, ==, to make element-by-element comparisons that return an object of the same size. This recipe shows you how to use the equals operator, which is very different from the equals method.

As in the previous recipe...