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pandas-profiling v1.4.1

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@romainx romainx released this 10 Jan 15:09

Enhancements

  • Performance enhancement. It is now possible to disable some heavy resource operations and achieve better performances (see also #76):
    • Correlation checking by turning check_correlation to False (#43)
    • Recoded checking by turning check_recoded to False.
  • Possibility to install using conda
  • Implementation of a new Boolean variable type (#25)
  • Add new badges for zeros and highly skewed (#63)
  • Code refactoring (internal improvement) to split on main modules in 4 modules (#65)
  • Improve types handling
    • types like list, tuple and dict are now officially unsupported until we improve them
    • mixed columns are also correctly handled
    • New Binary variable type supporting native boolean type and also binary numeric values (#77)
  • Warnings column names have link to corresponding detail in variables section in order to ease the navigation (#66)
  • Spearman and Pearson Correlation matrix diagrams added in the report (#83)

Bug fixes

  • #56 Incorrect calculation for % unique for variables with missing values bug
  • #11 Avoid to throw an error when calling get_rejected_variables while correlation has not been computed
  • #68 Avoid to set the matplotlib backend if not necessary