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This is occurring because _round_dataframe applies to all numeric columns, regardless of whether or not they are integers. This has some unfortunate consequences, such as rounding 988 to 990, 999 to 1000, and so on. As a solution, rounding should probably only be applied to specific columns that need it, ie it should be applied within the type-specific functions (eg _string_variable_summary_table) to only the relevant columns.
Hi,
first of all thank you for this great tool.
If I run skimpy on this 999 rows CSV I have 1000 NA rows.
Thank you
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