Comments (4)
aemorina
commented on May 31, 2024
2
This would be a great feature. It may sound counterintuitive to want to compare two dataframes but it comes up often.
For example, if I want to compare data read from a blob file and data from a database table the read statements will often times infer the schemas differently. It is a pain having to mainly define the schemas just so the assert statement will pass.
Would love to see this feature merged.
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arunvelsriram
commented on May 31, 2024
@MrPowers would you like to share your thoughts on this?
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backtrackbaba
commented on May 31, 2024
@MrPowers Any updates on this? Seems to be pretty useful
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MrPowers
commented on May 31, 2024
I merged this, thanks for the contribution. Try out v0.9.2 and let me know if it works as intended. Thanks!
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Related Issues (20)
- Flatten dataframe HOT 2
- Highlight mismatching values
- Fix the badges in the project README HOT 1
- The it_does_not_throw_with_different_schema test exposes a bug HOT 17
- pkg_resources is deprecated, prettytable produces warning HOT 1
- Reconfigure CI to run tests on pull requests
- Run tests for multiple PySpark versions in CI HOT 5
- Refactor code to conform to PEP8 HOT 5
- Font colors in error messages are bad in some terminals HOT 1
- ignore_schema in assert_df_equality removed in 9.3? HOT 6
- assert_df_equality throws SchemasNotEqualError when the dataframes are identical (except for the metadata) HOT 3
- Replace poetry dev-dependencies with dependency groups HOT 2
- Add unit tests to highlight limitations of this library HOT 1
- Make proper StructField comparer and DataType comparer abstractions
- Give user control to customize output formatting HOT 2
- SchemaNotEqualError not showing the difference in metadata
- Issues on Python 3.10 due to six 1.15.0 HOT 4
- Unit tests are only run against a single version of Python on the `main` branch.
- underline_cells failing if dataframes are different lengths HOT 1
- assert None while ignore_metadata=True
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