Previously in pandas, if a Series had missing values, its data type would be converted to float, resulting in a potential loss of precision for the original data.
With the integration of Apache Arrow in pandas 2.0, this issue is solved.
Say Goodbye to Data Type Conversion in pandas 2.0
4 thoughts on “Say Goodbye to Data Type Conversion in pandas 2.0”
Thanks, If doing science computing, this may involve potential bugs.
What are some potential bugs that you are thinking of?
Sorry, I didn’t make my ideal clear, the method in your note is really helpful. “Pandas default type converting sometime damage to the original data’s precision.” This will make some potential bugs.
Ah I see. Thanks for the clarification
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