October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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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.nanFalse>>> None == NoneTrue
All other comparisons against np.nan also return False, except not equal to:
>>> np.nan > 5False>>> 5 > np.nanFalse>>> np.nan != 5True
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