Metadata-Version: 1.1
Name: data_science_utilities
Version: 0.2.3
Summary: Data Science utilities in python.
Home-page: https://github.com/truocphamkhac/data-science-utilities
Author: Truoc Pham
Author-email: truoc.phamkhac@asnet.com.vn
License: MIT license
Description: ======================
        Data Science Utilities
        ======================
        
        
        .. image:: https://img.shields.io/pypi/v/data_science_utilities.svg
                :target: https://pypi.python.org/pypi/data_science_utilities
        
        .. image:: https://img.shields.io/travis/truocphamkhac/data-science-utilities.svg
                :target: https://travis-ci.org/truocphamkhac/data-science-utilities
        
        .. image:: https://readthedocs.org/projects/data-science-utilities/badge/?version=latest
                :target: http://data-science-utilities-python.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        
        
        
        Data Science utilities in python.
        
        
        * Free software: MIT license
        * Documentation: http://data-science-utilities-python.readthedocs.io.
        
        
        Features
        --------
        
        * Missing Data Statistic::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> # make statistic
            >>> missing_data = data_science_utilities.missing_data_stats(df)
            >>> # display statistic
            >>> missing_data
        
        
        * Read CSV files from path::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> train_path = '../data/raw/train.csv'
            >>> test_path = '../data/raw/test.csv'
            >>>
            >>> X_train, X_test = data_science_utilities.read_csv_files(train_path, test_path)
        
        
        * Plotting distribution normal::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_dist_norm(dist, 'distribution normal')
        
        
        * Plotting correlation matrix::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_corelation_matrix(data)
        
        
        * Plotting top attributes correlation matrix::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_top_corelation_matrix(data, target, k=10, cmap='YlGnBu')
        
        
        * Plotting attributes by scatter chart::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_scatter(data, column_name, target)
        
        
        * Plotting attributes by box bar::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_box(data, column_name, target)
        
        
        * Plotting category by box bar::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_category_columns(data, limit_bars=10)
        
        
        * Generate a simple plot of the test and traning learning curve::
        
            >>> from data_science_utilities import data_science_utilities
            >>>
            >>> data_science_utilities.plot_learning_curve(estimator, title, X, y, ylim=None,
            >>>                     cv=None, train_sizes=np.linspace(.1, 1.0, 5))
        
        
        Credits
        -------
        
        This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
        
        =======
        History
        =======
        
        0.2.3 (2018-05-21)
        ------------------
        
        * Fixed render docs on https://pypi.org/.
        
        
        0.2.2 (2018-05-21)
        ------------------
        
        * Fix render docs con't.
        
        
        0.2.1 (2018-05-21)
        ------------------
        
        * Fix render docs.
        
        
        0.2.0 (2018-05-14)
        ------------------
        
        * Adds utils about visualization.
        
        
        0.1.0 (2018-05-11)
        ------------------
        
        * First release on PyPI.
        
Keywords: data_science_utilities
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
