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CHANGELOG

All notable changes to this project will be documented in this file. The format is based on Keep a Changelog, and this project adheres to PEP0440 styling guide. For full details, see the commit logs.

PEP0440 Styling Guide

Click to open PEP0440 Styilng Guide

Packaging for PyPI follows the standard PEP0440 styling guide and is implemented by the packaging.version.Version class. The other popular versioning scheme is semver, but each build has different parts/mapping. The following table gives a mapping between these two versioning schemes:

PyPI Version semver Version
epoch n/a
major major
minor minor
micro patch
pre prerelease
dev build
post n/a

One can use the packaging version to convert between PyPI to semver and vice-versa. For more information, check this link.

Release Note(s)

The release notes are documented, the list of changes to each different release are documented. The major.minor patch are indicated under h3 tags, while the micro and "version identifiers" are listed under h4 and subsequent headlines.

Click to open Legend Guidelines for the Project CHANGELOG.md File
  • 🎉 - Major Feature : something big that was not available before.
  • ✨ - Feature Enhancement : a miscellaneous minor improvement of an existing feature.
  • 🛠️ - Patch/Fix : something that previously didn’t work as documented – or according to reasonable expectations – should now work.
  • ⚙️ - Code Efficiency : an existing feature now may not require as much computation or memory.
  • 💣 - Code Refactoring : a breakable change often associated with major version bump.

Version 1.2.0 | WIP

The version brings various bug fixes, improvements and new features on top of the previous stable version release v1.1.0 as below:

  • 🎉 Introducing stattistics which can be used to calculate outliers on a dataframe window object using groupApply() method.

Version 1.1.0 | Stable Release, Release Date - 29-07-2024

We're pleased to annouce the first major release and preview-built for pandaswizard! This version mainly focuses on enduser feedback and basic setup for the module.

The module pandas-wizard was developed as an initiative to provide additional functionalities on top of pandas. I've spent years in developing projects involving the use of pandas and have always used snippets or redundant GitHub Gists to keep track of additional functionalities that can be used alongside and later, decided to compile some of the code snippets directly into one file and publish the same as a package in PyPI/pandas-wizard.

Moving from alpha release to stable release. The following features are updated for the release as below:

  • 🎉 Added a wrapper function timeit to print executed time for a function that returns a pandas dataframe object.
  • 🎉 Added a new module called pdw.functions which introduces or provides functionalities like "collation" of a series based on some popular metrics like "weighted moving average" dynamically.
  • 🎉 Introduced a new module window which acts as a wrapper to the pd.DataFrame.rolling() function.

Version 1.1.0a0 | Release Date: 21.04.2024

Moving from development release to alpha testing release, the version brings the additional new features and/or enhancements for the module:

  • 🎉 Added pdw.wrappers module housing useful decorators,
  • 🛠️ (#7) For legacy/np < 1.22 try to return the aggregated value using "interpolation" attribute.
  • 🎉📃 Basic code documentation is now available, hosted using readthedocs/pandas-wizard

Version 1.1.0.dev0 | Release Date: 20.04.2024

Major enhancement of the preview built, also created an favicon and logo for the project. The logo is modified from the original pandas logo.

  • ⚙️ Added two new functions __set_method__() and __calculate_quantile__() to reduce code duplicacy,
  • ✨ (#3) Added the ability to choose from either pandas or numpy to calculate grouped result:
    • ✨ allows the user to choose any of the method to calculate based on numpy documentations,
    • 💣 numpy version requirement is numpy >= 1.22 due to argument change interpolation to method more details.

Version 1.0.1.dev0 | Release Date: 19.04.2024

The first dev or preview-build for v1.0.0 focusing on function development and objective documentation. The version focuses on providing basic features like:

  • 🎉 pandaswizard.quantile: A simple function to calculate the quantile of a grouped data series,
  • 🎉 pandaswizard.percentile: A simple function to calculate the percentile of a grouped data series.