Metadata-Version: 2.1
Name: qnorm
Version: 0.1.0
Summary: Quantile normalization
Home-page: https://github.com/Maarten-vd-Sande/qnorm
Author: ['Maarten van der Sande <maartenvandersande@hotmail.com>']
License: MIT
Description: # qnorm
        [![PyPI version](https://badge.fury.io/py/qnorm.svg)](https://badge.fury.io/py/qnorm)
        [![Anaconda version](https://anaconda.org/conda-forge/qnorm/badges/version.svg)](https://anaconda.org/conda-forge/qnorm/badges/version.svg)
        ![tests](https://github.com/Maarten-vd-Sande/qnorm/workflows/tests/badge.svg)
        
        quantile normalization made easy.
        
        ## Quick example
        
        We recreate the example of [Wikipedia](https://en.wikipedia.org/wiki/Quantile_normalization):
        
        ```
        import pandas as pd
        import qnorm
        
        df = pd.DataFrame({'C1': {'A': 5, 'B': 2, 'C': 3, 'D': 4},
                           'C2': {'A': 4, 'B': 1, 'C': 4, 'D': 2},
                           'C3': {'A': 3, 'B': 4, 'C': 6, 'D': 8}})
        
        print(qnorm.quantile_normalize(df))
        ```
        
        which is what we expect:
        
        ```
                 C1        C2        C3
        A  5.666667  5.166667  2.000000
        B  2.000000  2.000000  3.000000
        C  3.000000  5.166667  4.666667
        D  4.666667  3.000000  5.666667
        ```
        
        The function quantile_normalize also accepts numpy arrays. 
        
        ## Installation
        
        ### pip
        
        ```
        pip install qnorm
        ```
        
        ### conda
        
        Installing qnorm from the conda-forge channel can be achieved by adding conda-forge to your channels with:
        
        ```
        conda config --add channels conda-forge
        ```
        
        Once the conda-forge channel has been enabled, qnorm can be installed with:
        
        ```
        conda install qnorm
        ```
        
        ### local
        
        clone the repository
        
        ```
        git clone https://github.com/Maarten-vd-Sande/qnorm
        ```
        
        And install it
        
        ```
        cd qnorm
        pip install .
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >3.6
Description-Content-Type: text/markdown
