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Link to documentation or specify exactly what non-null means. In particular, for float64s NaN are considered "null". And does it also represent NULLs in the Nullable integer types? https://pandas.pydata.org/docs/user_guide/integer_na.html
Pandas is not consistent with its terminology of NA, NULL, and NaN.
NaN is a floating point value that is not in the IEEE standard as a missing value.
R uses NA consistently and SQL uses NULL consistently in 3VL.
The text was updated successfully, but these errors were encountered:
Pandas version checks
main
hereLocation of the documentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.info.html
Documentation problem
Non-null is not specific
Suggested fix for documentation
Link to documentation or specify exactly what non-null means. In particular, for float64s NaN are considered "null". And does it also represent NULLs in the Nullable integer types? https://pandas.pydata.org/docs/user_guide/integer_na.html
Pandas is not consistent with its terminology of NA, NULL, and NaN.
NaN is a floating point value that is not in the IEEE standard as a missing value.
R uses NA consistently and SQL uses NULL consistently in 3VL.
The text was updated successfully, but these errors were encountered: