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,
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 (seertol
andatol
). 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.
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: DataFrames are different (value mismatch for column 'a') [left]: [1, 2, 3] [right]: [1, 5, 3]