The isna() and isnull() functions in Pandas are essentially identical in functionality. Both are used to detect missing or NA (Not Available) values in a DataFrame or Series. They return the same result and are often interchangeable.
Key Takeaway:
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No functional difference between the two.
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The choice to use one over the other is just a matter of preference or convention.
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isna()is more common in NumPy and other libraries, whileisnull()is historically more common in Pandas, but both are perfectly valid.
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