polars.DataFrame.mean#

DataFrame.mean(*, axis: Literal[0] = 0, null_strategy: NullStrategy = 'ignore') → Self[source]#

DataFrame.mean(*, axis: Literal[1], null_strategy: NullStrategy = 'ignore') → Series

DataFrame.mean( *, axis: int = 0, null_strategy: NullStrategy = 'ignore', ) → Self | Series

Aggregate the columns of this DataFrame to their mean value.

Parameters:

axis: Either 0 or 1.
null_strategy{‘ignore’, ‘propagate’}: This argument is only used if axis == 1.

Examples

>>> df = pl.DataFrame(
...     {
...         "foo": [1, 2, 3],
...         "bar": [6, 7, 8],
...         "ham": ["a", "b", "c"],
...         "spam": [True, False, None],
...     }
... )
>>> df.mean()
shape: (1, 4)
┌─────┬─────┬──────┬──────┐
│ foo ┆ bar ┆ ham  ┆ spam │
│ --- ┆ --- ┆ ---  ┆ ---  │
│ f64 ┆ f64 ┆ str  ┆ f64  │
╞═════╪═════╪══════╪══════╡
│ 2.0 ┆ 7.0 ┆ null ┆ 0.5  │
└─────┴─────┴──────┴──────┘
>>> df.mean(axis=1)
shape: (3,)
Series: 'foo' [f64]
[
    2.666667
    3.0
    5.5
]