| Name | pandas-wizard JSON |
| Version |
1.1.0a0
JSON |
| download |
| home_page | https://github.com/sharkutilities/pandas-wizard |
| Summary | Utility Functions, Wrappers for pandas Module |
| upload_time | 2024-04-21 12:29:48 |
| maintainer | None |
| docs_url | None |
| author | shark-utilities developers |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2024 Debmalya Pramanik Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
pandas
utility
utilities
util
utils
wrappers
data science
data analysis
data scientist
data analyst
statistics
percentile
quantile
probability
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
numpy
pandas
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<h1 align = "center">
<img alt = "favicon" src = "favicon.png" height = 250px><br>
pandas-wizard
</h1>
<div align = "justify">
[**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/).
</div>
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