https://github.com/osl-pocs/skdata

Python tools for data analysis
https://github.com/osl-pocs/skdata

data data-analysis data-science open-data python

Last synced: about 2 months ago
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Python tools for data analysis

• Host: GitHub
• URL: https://github.com/osl-pocs/skdata
• Owner: osl-pocs
• License: mit
• Created: 2016-08-14T20:28:05.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2019-05-21T14:03:59.000Z (over 6 years ago)
• Last Synced: 2025-04-23T06:49:22.472Z (9 months ago)
• Topics: data, data-analysis, data-science, open-data, python
• Language: Jupyter Notebook
• Size: 387 KB
• Stars: 19
• Watchers: 4
• Forks: 2
• Open Issues: 5
• Metadata Files:
  • Readme: README.rst
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

Awesome Lists containing this project

README

          
===============================

SciKit Data

===============================

.. image:: https://img.shields.io/pypi/v/scikit-data.svg

        :target: https://pypi.python.org/pypi/scikit-data

.. image:: https://img.shields.io/travis/OpenDataScienceLab/skdata.svg

        :target: https://travis-ci.org/OpenDataScienceLab/skdata

.. image:: https://readthedocs.org/projects/skdata/badge/?version=latest

        :target: https://skdata.readthedocs.io/en/latest/?badge=latest

        :alt: Documentation Status

Conda package current release info

==================================

.. image:: https://anaconda.org/conda-forge/scikit-data/badges/version.svg

        :target: https://anaconda.org/conda-forge/scikit-data

        :alt: Anaconda-Server Badge

.. image:: https://anaconda.org/conda-forge/scikit-data/badges/downloads.svg

        :target: https://anaconda.org/conda-forge/scikit-data

        :alt: Anaconda-Server Badge

About SciKit Data

=================

The propose of this library is to allow the data analysis process more easy and automatic.

General objectives:

* reduce boilerplate code;

* reduce time spent on data analysis tasks and;

* offer a reproducible data analysis workflow.

Generally, there is a lot of boilerplate code on data analysis task that could be resolved with reproducible mechanisms and easy data visualization methods. Another point is related to data publish. A lot of data analysts doesn't know about open data repositories or doesn't consider that in his/her scientific workflow communication.

Specifics objectives:

* optimize data visualization;

* integration with open data repositories to publish data;

* reproducibility on data analysis tasks through storing and recovery operations;

SkData should integrate with Pandas library (Python).

Books used as reference to guide this project:

----------------------------------------------

- https://www.packtpub.com/big-data-and-business-intelligence/clean-data

- https://www.packtpub.com/big-data-and-business-intelligence/python-data-analysis

- https://www.packtpub.com/big-data-and-business-intelligence/mastering-machine-learning-scikit-learn

- https://www.packtpub.com/big-data-and-business-intelligence/practical-data-analysis-second-edition

Some other materials used as reference:

---------------------------------------

- https://github.com/rsouza/MMD/blob/master/notebooks/3.1_Kaggle_Titanic.ipynb

- https://github.com/agconti/kaggle-titanic/blob/master/Titanic.ipynb

- https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/kaggle/titanic.ipynb

Installing scikit-data

======================

Using conda

-----------

Installing `scikit-data` from the `conda-forge` channel can be achieved by adding `conda-forge` to your channels with:

.. code-block:: console

   $ conda config --add channels conda-forge

Once the `conda-forge` channel has been enabled, `scikit-data` can be installed with:

.. code-block:: console

   $ conda install scikit-data

It is possible to list all of the versions of `scikit-data` available on your platform with:

.. code-block:: console

   $ conda search scikit-data --channel conda-forge

Using pip

---------

To install scikit-data, run this command in your terminal:

.. code-block:: console

    $ pip install skdata

If you don't have `pip`_ installed, this `Python installation guide`_ can guide

you through the process.

.. _pip: https://pip.pypa.io

.. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/

More Information

----------------

* License: MIT

* Documentation: https://skdata.readthedocs.io

References

----------

* CUESTA, Hector; KUMAR, Sampath. Practical Data Analysis. Packt Publishing Ltd, 2016.

**Electronic materials**

* [1] http://www.datasciencecentral.com/profiles/blogs/introduction-to-outlier-detection-methods