polars.testing.assert_frame_equal#

polars.testing.assert_frame_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, rtol: float = 1e-05, atol: float = 1e-08, categorical_as_str: bool = False, ) → None[source]#

Assert that the left and right frame are equal.

Raises a detailed AssertionError if the frames differ. 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.
check_column_order: Require column order to match.
check_dtypes: 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_series_equal
assert_frame_not_equal

Notes

When using pytest, it may be worthwhile to shorten Python traceback printing by passing --tb=short. The default mode tends to be unhelpfully verbose. More information in the pytest docs.

Examples

>>> from polars.testing import assert_frame_equal
>>> df1 = pl.DataFrame({"a": [1, 2, 3]})
>>> df2 = pl.DataFrame({"a": [1, 5, 3]})
>>> assert_frame_equal(df1, df2)  
Traceback (most recent call last):
...
AssertionError: Series are different (value mismatch)
[left]:  [1, 2, 3]
[right]: [1, 5, 3]

The above exception was the direct cause of the following exception:

Traceback (most recent call last): … AssertionError: values for column ‘a’ are different