The propose of this library is to allow the data analysis process more easy and automatic.
Project description
===============================
SciKit Data
===============================
.. image:: https://img.shields.io/pypi/v/scikit-data.svg
:target: https://pypi-hypernode.com/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.
This library is based on some important libraries as:
- pandas;
- jupyter;
- matplotlib;
- scikit-learn;
* Free software: MIT license
* Documentation: https://skdata.readthedocs.io.
Features
--------
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
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
This project contemplates the follow features:
- Data conversions:
- soon ...
- Data collection:
- soon ...
- Data cleaning:
- ...
- Data storage:
- soon ...
- Data integration:
- soon ...
- Data manipulation:
- ...
- Outliers removal:
- ...
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/
=======
History
=======
0.1.0 (2016-08-14)
------------------
* First release on PyPI.
SciKit Data
===============================
.. image:: https://img.shields.io/pypi/v/scikit-data.svg
:target: https://pypi-hypernode.com/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.
This library is based on some important libraries as:
- pandas;
- jupyter;
- matplotlib;
- scikit-learn;
* Free software: MIT license
* Documentation: https://skdata.readthedocs.io.
Features
--------
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
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
This project contemplates the follow features:
- Data conversions:
- soon ...
- Data collection:
- soon ...
- Data cleaning:
- ...
- Data storage:
- soon ...
- Data integration:
- soon ...
- Data manipulation:
- ...
- Outliers removal:
- ...
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/
=======
History
=======
0.1.0 (2016-08-14)
------------------
* First release on PyPI.
Project details
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