Skip to content
Related Articles

Related Articles

Improve Article

Dora module in Python

  • Last Updated : 11 Oct, 2020

Dora is a library designed to simplify the exploratory data analysis which is such a painful part. It automates the repetitive tasks that consume most of the time. 

The library has functions that are very convenient for data cleaning, visualization, feature extraction and selection, visualization. Apart from this, it is also used for model validation by partitioning data, and transformations of data.

This library uses scikit-learn, pandas, and matplotlib. The intention of this library is to add additional features to general library mentioned before for exploratory data analysis. 

Installation:

pip install Dora

Usage:



In-order to implement it in datasets use the below syntax:

Python3




from Dora import Dora

It can be used for :

  • Reading Data & Configuration
  • Cleaning
  • Feature Selection & Extraction
  • Visualization
  • Model Validation
  • Data Versioning

Below is the most basic implementation of Dora module on a dataset in Python: 

Python




# Import required module
from Dora import Dora
  
# Create object
dora = Dora()
  
# Add dataset path as argument 
dora.configure(output = 'A', data = 'data.csv'
  
# Display dataset
dora.data

Output:

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up
Recommended Articles
Page :