Metadata-Version: 2.1
Name: datasist
Version: 1.5
Summary: A Machine learning library that abstracts repetitve functions used by data scientist and machine learning engineers
Home-page: https://github.com/risenW/datasist
Author: Rising Odegua
Author-email: risingodegua@gmail.com
License: MIT
Download-URL: https://github.com/risenW/datasist/archive/v1.5.tar.gz
Keywords: Data Analysis,Feature Engineering,Visualization
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: numpy
Requires-Dist: jupyter
Requires-Dist: scikit-learn

# Getting Started

![datasist](https://risenw.github.io/datasist/datasist.png)

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

| Latest Release |  [![latest release](https://img.shields.io/badge/pip-v1.5-blue.svg)](https://pypi.org/project/datasist/) |
| :--- | :--- |
| Release Status |  [![status](https://img.shields.io/badge/status-stable-brightgreen.svg)](./) |
| License |  [![license](https://img.shields.io/badge/license-MIT-orange.svg)](./) |
| Build Status |  [![build status](https://travis-ci.org/risenW/datasist.svg?branch=master)](./) |

### 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

```bash
pip install datasist
```

### Installation from source (Developers)

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

Run the following command in a terminal/command prompt

```bash
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 \[development mode\]:

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

### Documentation

API documentation can be found [here](https://risenw.github.io/datasist/index.html)

### 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**](https://risenw.github.io/datasist/contributing.html).

If you are simply looking to start working with the datasist codebase, navigate to the [GitHub "issues"tab](https://github.com/risenW/datasist/issues) and start looking through interesting issues. There are a number of issues listed under good first issue where you could start out.

### Using Datasist

#### Articles

Detailed articles covering some of the important features of datasist and can be found [here](https://towardsdatascience.com/https-medium-com-risingdeveloper-easy-data-analysis-visualization-and-modeling-using-datasist-part1-8b26526dbe01) and [here](https://towardsdatascience.com/easy-data-analysis-visualization-and-modeling-using-datasist-part-2-d2ce7fbf79e3)

[Basic classification example using Xente fraud dataset](https://risenw.github.io/datasist/classification_example.html)

[Basic example using the Iris dataset](https://github.com/risenW/datasist/blob/master/datasist/examples/Example_irisdata.ipynb)

#### Youtube Videos

Introduction to using Datasist, presented at NeuRips Meetup - PH. [Click Here](https://youtu.be/WYxSz6WBn-M)

Introduction to Datasist by DataKnight [Click Here](https://youtu.be/ErWa_WWu7vM)

List of contributors [here](https://github.com/risenW/datasist/graphs/contributors)

Logo design by [Heybee](https://twitter.com/therealheybee)



