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Checking for NaN Values in Python
blog.finxter.com/check-for-nan-values-in-python/Yapay zekadan makale özeti
- Understanding NaN
- NaN indicates that a value is not a number
- NaN is a floating-point value that cannot be converted to other types
- NaN differs from Null, which indicates something that doesn't exist
- Main Methods
- math.isnan() function checks for NaN in float objects
- != operator can be used to check NaN by comparing to itself
- numpy.isnan() function checks NaN in Numpy arrays
- pandas.isna() detects missing values in array-like objects
- NaN values don't fall within the range of -inf to infinity
- Additional Features
- NumPy provides methods like np.nansum() and np.nanmax() for array operations
- NaN values can be eliminated from arrays using specific functions