Data-quality-kit

New functionalities.
Added
- Added `assert_that_values_in_catalog` function to check if all values in a specified DataFrame column are present in a catalog (list).
- Added test cases to validate the behavior of `assert_that_values_in_catalog` in various scenarios:
- All values are in the catalog.
- Not all values are in the catalog.
- Column not present in the DataFrame.
- Empty catalog handling.

Changed
- No changes in this release.

New functionalities.
Added

Changed
- Renamed the function check_type_format to assert_that_type_value
- Added a new acurracy module to the data_quality_kit for enhanced data acurracy checks.
- Rename corresponding test cases for the acurracy module in the test suite.

Fixed

New functionalities.
Added

Changed
- Renamed the function check_column_match to assert_that_columns_values_match
- Renamed the function check_no_duplicates to assert_that_there_are_not_duplicates
- Added a new consistency module to the data_quality_kit for enhanced data consistency checks.
- Rename corresponding test cases for the consistency module in the test suite.

Fixed

New functionalities.
Added

Changed
- Renamed the function chech_nulls to assert_that_there_are_not_nulls
- Added a new validity module to the data_quality_kit for enhanced data validity checks.
- Rename corresponding test cases for the validity module in the test suite.

Fixed

New functionalities.
Added

Changed
- Renamed the function df_is_empty to assert_that_dataframe_is_empty
- Added a new completeness module to the data_quality_kit for enhanced data completeness checks.
- Rename corresponding test cases for the completeness module in the test suite.

Fixed

New functionalities.
Added
- **check_column_match** : Check if all values in column2 of df2 are present in column1 of df1.
Changed
- Project aligned to the PEP8 guidelines
Fixed