datasist 1.3

A Machine learning library that abstracts repetitve functions used by data scientist and machine learning engineers

datasist: Python library for easy data modeling, visualization, exploration and analysis.

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What is it?

datasist is a python package providing fast, quick, and an abstracted interface to popular and frequently used functions or techniques relating to data analysis, visualization, data exploration, feature engineering, Computer, NLP, Deep Learning, modeling, model deployment etc.

Install

pip install datasist

Dependencies

• Numpy
• pandas
• seaborn
• matplotlib
• scikit-learn
• spacy

Installation from source

To install datasist from source you need python 3.6> in addition to the normal dependencies above.

Run the following command in a terminal/command prompt

git clone https://github.com/risenW/datasist.git
cd datasist
python setup.py install

Alternatively, you can use install with pip after cloning, if you want all the dependencies pulled in automatically (the -e option is for installing it in [development mode]:

git clone https://github.com/risenW/datasist.git
cd datasist
pip install -e .

Documentation

API documentation can be found here

Contributing to datasist

All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.

A detailed overview on how to contribute can be found in the contributing guide.

If you are simply looking to start working with the datasist codebase, navigate to the GitHub "issues"tab and start looking through interesting issues. There are a number of issues listed under good first issue where you could start out.

Example Usage

Detailed articles covering some of the important features of datasist and can be found here and here

Basic classification example using Xente fraud dataset

Basic example using the Iris dataset

List of contributors here

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