polars.Expr.shift#
- Expr.shift(n: int | IntoExprColumn = 1, *, fill_value: IntoExpr | None = None) Expr [source]#
Shift values by the given number of indices.
- Parameters:
- n
Number of indices to shift forward. If a negative value is passed, values are shifted in the opposite direction instead.
- fill_value
Fill the resulting null values with this value.
See also
Notes
This method is similar to the
LAG
operation in SQL when the value forn
is positive. With a negative value forn
, it is similar toLEAD
.Examples
By default, values are shifted forward by one index.
>>> df = pl.DataFrame({"a": [1, 2, 3, 4]}) >>> df.with_columns(shift=pl.col("a").shift()) shape: (4, 2) ┌─────┬───────┐ │ a ┆ shift │ │ --- ┆ --- │ │ i64 ┆ i64 │ ╞═════╪═══════╡ │ 1 ┆ null │ │ 2 ┆ 1 │ │ 3 ┆ 2 │ │ 4 ┆ 3 │ └─────┴───────┘
Pass a negative value to shift in the opposite direction instead.
>>> df.with_columns(shift=pl.col("a").shift(-2)) shape: (4, 2) ┌─────┬───────┐ │ a ┆ shift │ │ --- ┆ --- │ │ i64 ┆ i64 │ ╞═════╪═══════╡ │ 1 ┆ 3 │ │ 2 ┆ 4 │ │ 3 ┆ null │ │ 4 ┆ null │ └─────┴───────┘
Specify
fill_value
to fill the resulting null values.>>> df.with_columns(shift=pl.col("a").shift(-2, fill_value=100)) shape: (4, 2) ┌─────┬───────┐ │ a ┆ shift │ │ --- ┆ --- │ │ i64 ┆ i64 │ ╞═════╪═══════╡ │ 1 ┆ 3 │ │ 2 ┆ 4 │ │ 3 ┆ 100 │ │ 4 ┆ 100 │ └─────┴───────┘