Adds ignore_metadata option to assert_approx_df_equality#100
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Adds ignore_metadata option to assert_approx_df_equality function, to avoid some wrong dataframe comparisons
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…df_equality The MrPowers#100 started to add support for `ignore_metadata` in `assert_approx_df_equality`, but most of the work was already merged in MrPowers#182. This PR fixes the missing piece in the `assert_approx_df_equality` implementation
alexott
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…df_equality The MrPowers#100 started to add support for `ignore_metadata` in `assert_approx_df_equality`, but most of the work was already merged in MrPowers#182. This PR fixes the missing piece in the `assert_approx_df_equality` implementation
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Adds ignore_metadata option to assert_approx_df_equality function, to avoid some wrong dataframe comparisons.
For example, when I have two dataframes with this schemas:
root
|-- FORMA_ID: decimal(38,0) (nullable = true)
|-- START_DATE: timestamp (nullable = true)
|-- TYPE: string (nullable = true)
|-- AMOUNT: decimal(38,10) (nullable = true)
|-- datalake_ingestion_timestamp: timestamp (nullable = false)
root
|-- FORMA_ID: decimal(38,0) (nullable = true)
|-- START_DATE: timestamp (nullable = true)
|-- TYPE: string (nullable = true)
|-- AMOUNT: decimal(38,10) (nullable = true)
|-- datalake_ingestion_timestamp: timestamp (nullable = true)
And I perform an approx comparison as:
assert_approx_df_equality(df, expected_df, ignore_nullable=True, precision=1e-8)Currently I get an error regarding nullable, despite
ignore_nullableoption. By passing ignore_metadata option the test is success