Metadata-Version: 2.2
Name: dataramp
Version: 0.1.9
Summary: A Data science library for data science / data analysis teams
Home-page: https://github.com/Kimxons/dataramp
Author: Meshack Kitonga
Author-email: Meshack Kitonga <kitongameshack9@gmail.com>
Maintainer-email: Meshack Kitonga <kitongameshack9@gmail.com>
Project-URL: Documentation, https://github.com/Kimxons/dataramp/tree/main/docs
Project-URL: Source Code, https://github.com/Kimxons/dataramp
Project-URL: Changes, https://github.com/dataramp/en/latest/release_notes.html
Project-URL: Issue Tracker, https://github.com/Kimxons/dataramp/issues
Keywords: data science,machine learning,data analysis
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.11
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# Dataramp

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Pylint](https://img.shields.io/badge/pylint-enabled-brightgreen.svg)](https://github.com/PyCQA/pylint)
[![Flake8](https://img.shields.io/badge/flake8-enabled-blue.svg)](https://flake8.pycqa.org/en/latest/)
[![Scikit-learn](https://img.shields.io/badge/scikit--learn-v0.24.2-blue)](https://scikit-learn.org/stable/)

Welcome to the Dataramp documentation! Here you will find information about Dataramp, including some examples to get you started.

## Dataramp

Dataramp is a Python library designed to streamline data science and data analysis workflows. It offers a collection of utility functions and tools tailored to assist data science teams in various aspects of their projects.

By providing a range of functionalities, Dataramp aims to enhance productivity and efficiency in data science projects, empowering teams to focus on deriving meaningful insights from their data.

## Getting Started

Read the quick start guide [here](docs/quickstart.md).

If you want to see some examples, you can look at the examples in the [examples](examples/) directory.

You can install Dataramp and learn more from [PyPi](https://pypi.org/project/dataramp/).
