polars.testing.assert_frame_equal#

polars.testing.assert_frame_equal(left: DataFrame | LazyFrame, right: DataFrame | LazyFrame, *, check_dtype: bool = True, check_exact: bool = False, rtol: float = 1e-05, atol: float = 1e-08, nans_compare_equal: bool = True, check_column_order: bool = True, check_row_order: bool = True) → None[source]#

Raise detailed AssertionError if left does NOT equal right.

Parameters:

left: the dataframe to compare.
right: the dataframe to compare with.
check_dtype: if True, data types need to match exactly.
check_exact: if False, test if values are within tolerance of each other (see rtol & atol).
rtol: relative tolerance for inexact checking. Fraction of values in right.
atol: absolute tolerance for inexact checking.
nans_compare_equal: if your assert/test requires float NaN != NaN, set this to False.
check_column_order: if False, frames will compare equal if the required columns are present, irrespective of the order in which they appear.
check_row_order: if False, frames will compare equal if the required rows are present, irrespective of the order in which they appear; as this requires sorting, you cannot set on frames that contain unsortable columns.

Examples

>>> from polars.testing import assert_frame_equal
>>> df1 = pl.DataFrame({"a": [1, 2, 3]})
>>> df2 = pl.DataFrame({"a": [2, 3, 4]})
>>> assert_frame_equal(df1, df2)  
AssertionError: Values for column 'a' are different.