polars.testing.assert_frame_not_equal

polars.testing.assert_frame_not_equal(
    left: DataFrame | LazyFrame,
    right: DataFrame | LazyFrame,
    *,
    check_row_order: bool = True,
    check_column_order: bool = True,
    check_dtypes: bool = True,
    check_exact: bool = False,
    rel_tol: float = 1e-05,
    abs_tol: float = 1e-08,
    categorical_as_str: bool = False,
) → None

Assert that the left and right frame are not equal.

This function is intended for use in unit tests.

Changed in version 0.20.31: The check_dtype parameter was renamed check_dtypes.

Changed in version 1.32.3: The rtol and atol parameters were renamed to rel_tol and abs_tol, respectively.

Parameters:

left

The first DataFrame or LazyFrame to compare.

right

The second DataFrame or LazyFrame to compare.

check_row_order

Requires row order to match.

check_column_order

Requires column order to match.

check_dtypes

Requires data types to match.

check_exact

Requires float values to match exactly. If set to False, values are considered equal when within tolerance of each other (see rel_tol and abs_tol). Only affects columns with a Float data type.

rel_tol

Relative tolerance for inexact checking. Fraction of values in right.

abs_tol

Absolute tolerance for inexact checking.

categorical_as_str

Cast categorical columns to string before comparing. Enabling this helps compare columns that do not share the same categories.

See also

assert_frame_equal

assert_series_not_equal

Examples

>>> from polars.testing import assert_frame_not_equal
>>> df1 = pl.DataFrame({"a": [1, 2, 3]})
>>> df2 = pl.DataFrame({"a": [1, 2, 3]})
>>> assert_frame_not_equal(df1, df2)
Traceback (most recent call last):
...
AssertionError: DataFrames are equal (but are expected not to be)