polars.Expr.diff#

Expr.diff(n: int = 1, null_behavior: NullBehavior = 'ignore') → Self[source]#

Calculate the first discrete difference between shifted items.

Parameters:

n: Number of slots to shift.
null_behavior{‘ignore’, ‘drop’}: How to handle null values.

Examples

>>> df = pl.DataFrame({"int": [20, 10, 30, 25, 35]})
>>> df.with_columns(change=pl.col("int").diff())
shape: (5, 2)
┌─────┬────────┐
│ int ┆ change │
│ --- ┆ ---    │
│ i64 ┆ i64    │
╞═════╪════════╡
│ 20  ┆ null   │
│ 10  ┆ -10    │
│ 30  ┆ 20     │
│ 25  ┆ -5     │
│ 35  ┆ 10     │
└─────┴────────┘

>>> df.with_columns(change=pl.col("int").diff(n=2))
shape: (5, 2)
┌─────┬────────┐
│ int ┆ change │
│ --- ┆ ---    │
│ i64 ┆ i64    │
╞═════╪════════╡
│ 20  ┆ null   │
│ 10  ┆ null   │
│ 30  ┆ 10     │
│ 25  ┆ 15     │
│ 35  ┆ 5      │
└─────┴────────┘

>>> df.select(pl.col("int").diff(n=2, null_behavior="drop").alias("diff"))
shape: (3, 1)
┌──────┐
│ diff │
│ ---  │
│ i64  │
╞══════╡
│ 10   │
│ 15   │
│ 5    │
└──────┘