polars.Expr.shift#

Expr.shift(n: int | IntoExprColumn = 1, *, fill_value: IntoExpr | None = None) → Self[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

backward_fill
forward_fill

Notes

This method is similar to the LAG operation in SQL when the value for n is positive. With a negative value for n, it is similar to LEAD.

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   │
└─────┴───────┘