Releases: sharkutilities/pandas-wizard
Version 1.1.0 | Stable Release
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.
The consolidated functionalities of the modules are as follows:
- Statistical Functions to use alongside
pd.groupby(...).agg({})
as below:- 🎉
pandaswizard.quantile
: A simple function to calculate the quantile of a grouped data series, and - 🎉
pandaswizard.percentile
: A simple function to calculate the percentile of a grouped data series.
- 🎉
- The wrappers utility that prints useful information like memory usage and time taken that can be useful in function development and optimization,
- The window module which acts as a wrapper to the
pd.DataFrame(...).rolling(...)
method to apply additional user-defined functions.- Additionally, the submodule
pandas-wizard/functions
captures basic functions likeweightedMA
that can be applied directly in a rolling window without explicitly defining a custom function.
- Additionally, the submodule
v1.1.0a0
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
v1.1.0.dev0
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
ornumpy
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 changeinterpolation
tomethod
more details.
- ✨ allows the user to choose any of the method to calculate based on
v1.0.1.dev0
The first dev
or preview-build
for v1.0.0
focuses on function development and objective documentation. The version
focuses on providing basic features like:
- 🎉
pandaswizard.quantile
: A simple function to calculate quantile of a grouped data series, - 🎉
pandaswizard.percentile
: A simple function to calculate percentile of a grouped data series.