Comments (2)
I see you point and it makes sense!
Ideally you would use the Decimal
type which maps exactly to those database types with a specific precision and scale!
Unfortunately this is still experimental and has lots of limitations and I just checked and its not possible to write a Decimal to csv 😆
example for Decimal
type
(
pl.DataFrame(
{
"x": ["0.123", "0.234", "0.345"],
"y": ["0.123", "0.234", "0.345"],
}
)
.with_columns(
pl.col("x").cast(pl.Decimal(precision=19, scale=6)),
pl.col("y").cast(pl.Decimal(precision=5, scale=3)),
)
# .write_csv("decimal.csv") # not working
)
# shape: (3, 2)
# ┌───────────────┬──────────────┐
# │ x ┆ y │
# │ --- ┆ --- │
# │ decimal[19,6] ┆ decimal[5,3] │
# ╞═══════════════╪══════════════╡
# │ 0.123000 ┆ 0.123 │
# │ 0.234000 ┆ 0.234 │
# │ 0.345000 ┆ 0.345 │
# └───────────────┴──────────────┘
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Yes @JulianCologne , I agree that that would be the ideal solution.
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