Comments (3)
dpinol
commented on July 20, 2024
I can reproduce it with polars 0.20.13, but not on 0.20.10.
Both with python 3.11.5
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stinodego
commented on July 20, 2024
This was reported in #14771 and fixed in #14778
It will be included in the next release.
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PierreAttard
commented on July 20, 2024
Ok, thanks, I'll look better in the issues next time.
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Related Issues (20)
- exception thrown if converting arrow Table with struct and dictionary columns to polar dataframe
- converting pandas to Polars drops column if its name, when converted to string, matches another column's name
- pl.format should be clear it will return null when one of the arguments is null
- Off-by-one error when casting to Decimal with set precision
- Importing pyarrow after polars causes `SIGSEGV` HOT 4
- Polars assumes microseconds instead of reading numpy timedelta units
- Cannot create Array column containing large u64 value
- Multipling a Decimal by Int returns Int type HOT 2
- Split out `Expr.top_k` from `Expr.top_k_by`
- `pl.Datetime` `time_zone` parameter has no type or value check HOT 5
- Cast from `pl.Date` to `pl.Datetime` silently returns incorrect value when new dtype cannot hold value HOT 2
- exception thrown if converting chunked arrow Table with struct and dictionary columns to polar Dataframe
- Panic when constructing Series with dtype `Duration('ms')` with large `timedelta` objects
- Can the separator of the read csv function support regular splitting? HOT 5
- Casting float to Decimal fails silently HOT 2
- Use parquet statistics when collecting column statistics from scanned parquet HOT 2
- Excessive Memory Consumption During Rolling Operations on Large DataFrames
- write_database() - Insert many rows with sql server using fast_executemany HOT 3
- fill_null doesn't support expr HOT 6
- `dt.total_nanoseconds` and `dt.total_microseconds` may overflow silently
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