pandas-wizard

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[**Pandas-Wizard (`pandaswizard`)**](https://github.com/sharkutilities/pandas-wizard) is a simple Python module for providing utility functions and wrappers for the `pandas` module. The module is kept simple and use of external dependencies is minimized unless needed to enhance performance. This is a relatively new repository, and if you find any performance or improvement scope please check the [contributing guidelines](https://github.com/sharkutilities/.github/blob/master/.github/CONTRIBUTING.md) for the organization. All help and criticism are appreciated. If you find any additional use cases please create a pull request or submit for a new feature. ## Getting Started The source code is currently hosted at GitHub: [**sharkutilities/pandas-wizard**](https://github.com/sharkutilities/pandas-wizard). The binary installers for the latest release are available at the [Python Package Index (PyPI)](https://pypi.org/project/pandas-wizard/). ```bash pip install -U pandas-wizard ``` The list of changes between each release is available [here](./CHANGELOG.md). The purpose of the below guide is to illustrate the main features of **pandas-wizard** and assume the working knowledge of the [`pandas`](https://pypi.org/project/pandas/) module and use cases. The below example calculates the percentile of `pandas.DataFrameGroupBy` object using [`np.percentile`](https://numpy.org/doc/stable/reference/generated/numpy.percentile.html). ```python import pandaswizard as pdw # attempt to create an ubiquitous naming # let's calculate the 50th-percentile, i.e. the median for each group percentiles = df.groupby("group").agg({"A" : pdw.percentile(50)}) percentiles.head() # or, preferred usage is to use in conjunture with other aggregation function like statistics = df.groupby("group").agg({"A" : [sum, pdw.percentile(50), pdw.quantile(0.95)]}) statistics.head() ``` The above function calculates the 50th percentile, i.e., the median of the feature "A" based on the grouped column "group" from the data frame. --- **Footnote:** The [favicon](./favicon.png) is designed from the original [`pandas`](https://pandas.pydata.org/static/img/pandas.svg) logo and no copyright infringement is intended. Since the main objective is to provide a utility function for `pandas` the logo is re-used and developed using [canva](https://www.canva.com/).