Comments (4)
import polars as pl
from polars import col
df = pl.DataFrame({
"a": ["a", "a", "a", "b", "b", "c", "c"],
"ii": [1, 3, 5, 7, 9, 11, 13],
})
def shift_many(value_col, shift_col):
return col(value_col).gather(
(pl.int_range(pl.len()).alias("len") + col(shift_col))
.clip(0, pl.len() - 1)
)
print(df.with_columns(shift_many("a", "ii").alias("shifted")))
shape: (7, 3)
┌─────┬─────┬─────────┐
│ a ┆ ii ┆ shifted │
│ --- ┆ --- ┆ --- │
│ str ┆ i64 ┆ str │
╞═════╪═════╪═════════╡
│ a ┆ 1 ┆ a │
│ a ┆ 3 ┆ b │
│ a ┆ 5 ┆ c │
│ b ┆ 7 ┆ c │
│ b ┆ 9 ┆ c │
│ c ┆ 11 ┆ c │
│ c ┆ 13 ┆ c │
└─────┴─────┴─────────┘
from polars.
What do you mean a varying n
. A column can only be shifted once?
from polars.
I mean that n can be different in every row. See provided example.
from polars.
I think you just want to do a gather in such a case.
from polars.
Related Issues (20)
- The memory could not be written unhandled exception crash python.exe HOT 4
- polars >= `0.20.23` does no longer raise `FileNotFoundError` immediately for non-existing files HOT 1
- Filter always exclude null values HOT 1
- Can't create series from `list[numpy | None]`
- Write parquet panics on nested struct: "RecordBatch requires all its arrays to have an equal number of rows" HOT 2
- Support CSE on python UDFs HOT 10
- wirte_parquet() and write_delta() panics when writing large dataset sizes HOT 3
- Add `pl.Config(tbl_max_col_width_chars=20)`
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- SQLContext support for accessing Struct type key/value column
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- Missing doc entry for new `polars.sql` top level function HOT 2
- Date/Datetime inference should allow format to change between `Y-M-D` / `D-M-Y` HOT 2
- Full support for TPCH 22 SQL Queries HOT 3
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- `pl.exclude` + `.struct.field("*")` PanicException no exclude at this point HOT 1
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- `.pivot` should offer a column prefix option.
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from polars.