osl-pocs/skdata

Python tools for data analysis

SciKit Data

Conda package current release info

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:

$ conda config --add channels conda-forge

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

$ conda install scikit-data

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

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

Using pip

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

$ pip install skdata

If you don't have pip installed, this Python installation guide can guide you through the process.

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