Metadata-Version: 2.1
Name: scatterd
Version: 0.1.2
Summary: scatterd is an easy and fast way of creating scatter plots.
Home-page: https://github.com/erdogant/scatterd
Author: Erdogan Taskesen
Author-email: erdogant@gmail.com
License: UNKNOWN
Download-URL: https://github.com/erdogant/scatterd/archive/0.1.2.tar.gz
Description: # scatterd
        
        [![Python](https://img.shields.io/pypi/pyversions/scatterd)](https://img.shields.io/pypi/pyversions/scatterd)
        [![PyPI Version](https://img.shields.io/pypi/v/scatterd)](https://pypi.org/project/scatterd/)
        [![License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/erdogant/scatterd/blob/master/LICENSE)
        [![Downloads](https://pepy.tech/badge/scatterd/week)](https://pepy.tech/project/scatterd/week)
        [![Coffee](https://img.shields.io/badge/coffee-black-grey.svg)](https://erdogant.github.io/donate/?currency=USD&amount=5)
        
        * Easy and fast manner of creating scatter plots.
        
        ## Contents
        - [Installation](#-installation)
        - [Quick Start](#-quick-start)
        - [Contribute](#-contribute)
        - [Maintainers](#-maintainers)
        - [License](#-copyright)
        
        ## Installation
        * Install scatterd from PyPI (recommended). scatterd is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows. 
        * It is distributed under the MIT license.
        
        ## Quick Start
        ```
        pip install scatterd
        ```
        
        * Alternatively, install scatterd from the GitHub source:
        ```bash
        git clone https://github.com/erdogant/scatterd.git
        cd scatterd
        python setup.py install
        ```  
        
        ### Import scatterd package
        ```python
        from scatterd import scatterd
        ```
        
        ### Example:
        ```python
        # Import some example data
        from sklearn import datasets
        iris = datasets.load_iris()
        X = iris.data[:, :2]  # we only take the first two features.
        y = iris.target
        
        # Make simple scatterplot
        scatterd(X[:,0], X[:,1])
        # Color based on labels
        scatterd(X[:,0], X[:,1], label=y, s=100)
        # Set labels
        scatterd(X[:,0], X[:,1], label=y, s=100, norm=True, cmap='Set2', xlabel='xlabel', ylabel='ylabel', title='Title')
        # Change sizes
        s=np.random.randint(10,200,len(y))
        scatterd(X[:,0], X[:,1], label=y, s=s, cmap='Set2', xlabel='xlabel', ylabel='ylabel', title='Title', fontsize=25, figsize=(15,10))
        # Change figure size
        scatterd(X[:,0], X[:,1], figsize=(25,15))
        
        ```
        <p align="center">
          <img src="https://github.com/erdogant/scatterd/blob/master/docs/figs/fig1.png" width="600" />
          <img src="https://github.com/erdogant/scatterd/blob/master/docs/figs/fig2.png" width="600" />
          <img src="https://github.com/erdogant/scatterd/blob/master/docs/figs/fig3.png" width="600" />
          <img src="https://github.com/erdogant/scatterd/blob/master/docs/figs/fig4.png" width="600" />
        </p>
        
        
        ### Maintainer
        * Erdogan Taskesen, github: [erdogant](https://github.com/erdogant)
        * Contributions are welcome.
        * If you wish to buy me a <a href="https://erdogant.github.io/donate/?currency=USD&amount=5">Coffee</a> for this work, it is very appreciated :)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
