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_dtype: bool = True,
check_exact: bool = False,
rtol: float = 1e-05,
atol: float = 1e-08,
categorical_as_str: bool = False,
) → None[source]#

Assert that the left and right frame are not equal.

This function is intended for use in unit tests.

Parameters:
left

The first DataFrame or LazyFrame to compare.

right

The second DataFrame or LazyFrame to compare.

check_row_order

Require row order to match.

Note

Setting this to False requires sorting the data, which will fail on frames that contain unsortable columns.

check_column_order

Require column order to match.

check_dtype

Require data types to match.

check_exact

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

rtol

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

atol

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 string cache.

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: frames are equal