feat: mean_horizontal
#843
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Ok, so this ended up being a bit more than initially expected on the polars side 😂 |
FBruzzesi
commented
Aug 22, 2024
| @@ -85,11 +88,28 @@ def lit(self, value: Any, dtype: dtypes.DType | None = None) -> PolarsExpr: | |||
| return PolarsExpr(pl.lit(value, dtype=narwhals_to_native_dtype(dtype))) | |||
| return PolarsExpr(pl.lit(value)) | |||
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| def mean(self, *column_names: str) -> Any: | |||
| def mean(self, *column_names: str) -> PolarsExpr: | |||
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We should return PolarsExpr to be able to keep chaining and interacting with other narwhals exprs if needed
FBruzzesi
commented
Aug 22, 2024
| n_non_zero = reduce( | ||
| lambda x, y: x + y, ((1 - e.is_null()) for e in polars_exprs) | ||
| ) | ||
| return PolarsExpr(total._native_expr / n_non_zero._native_expr) |
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__div__ is not currently implemented and I did not want to make the PR even larger
MarcoGorelli
approved these changes
Aug 22, 2024
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As
meancan only be numeric, unlike #825, it is safe to fill nulls with zeros for the sum, and count the number of non-nulls summands.