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Dora module in Python

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  • Last Updated : 11 Oct, 2020
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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:

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