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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:

  • No functional difference between the two.

  • The choice to use one over the other is just a matter of preference or convention.

  • isna() is more common in NumPy and other libraries, while isnull() is historically more common in Pandas, but both are perfectly valid.

posted on 2025-11-09 17:11  ZhangZhihuiAAA  阅读(0)  评论(0)    收藏  举报