polars.Series.is_close#

Series.is_close( other: IntoExpr, *, abs_tol: float = 0.0, rel_tol: float = 1e-09, nans_equal: bool = False, ) → Series[source]#

Get a boolean mask of the values being close to the other values.

Two values a and b are considered close if the following condition holds:

\[|a-b| \le max \{ \text{rel_tol} \cdot max \{ |a|, |b| \}, \text{abs_tol} \}\]

Parameters:

abs_tol: Absolute tolerance. This is the maximum allowed absolute difference between two values. Must be non-negative.
rel_tol: Relative tolerance. This is the maximum allowed difference between two values, relative to the larger absolute value. Must be non-negative.
nans_equal: Whether NaN values should be considered equal.

Returns:

Series: Series of data type Boolean.

Notes

The implementation of this method is symmetric and mirrors the behavior of math.isclose(). Specifically note that this behavior is different to numpy.isclose().

Examples

>>> s = pl.Series("s", [1.0, 1.2, 1.4, 1.45, 1.6])
>>> s.is_close(1.4, abs_tol=0.1)
shape: (5,)
Series: 's' [bool]
[
    false
    false
    true
    true
    false
]