Falsy values in Python, like None and empty sequences, are useful for checking missing data. They can be used in conditionals and comparisons. However, assigning special meanings to falsy values can lead to confusion. To compare for None, use "is" instead of "==". In Pandas, use "isna" or "isnull" to detect missing values.
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