Enhancement 1792: Use float64 as the result type for all division operations in the processing pipeline #1794
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…rations in the processing pipeline
alexowens90
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…rations in the processing pipeline (#1794) #### Reference Issues/PRs Closes #1792 Fixes #1791 #### What does this implement or fix? Previously, dividing integers by integers in the processing pipeline (e.g. with `apply`) would perform integer division. This is true for all of `column/column`, `column/value`, and `value/column`. This is not the same as the behaviour of Pandas or Polars. Worse, if the denominator was zero, this would cause a floating point exception on linux, and an integer overflow exception (#1791) on Windows. This change makes the result a `float64` in all cases. If we want the previous behaviour to be accessible again, we should implement the integer division operator `//` in Python.
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Reference Issues/PRs
Closes #1792
Fixes #1791
What does this implement or fix?
Previously, dividing integers by integers in the processing pipeline (e.g. with
apply) would perform integer division. This is true for all ofcolumn/column,column/value, andvalue/column.This is not the same as the behaviour of Pandas or Polars. Worse, if the denominator was zero, this would cause a floating point exception on linux, and an integer overflow exception (#1791) on Windows.
This change makes the result a
float64in all cases. If we want the previous behaviour to be accessible again, we should implement the integer division operator//in Python.