MAHA 1.3

Performing ETL using Machine Learning

MAHA

MAHA is an in-progress ETL package which uses machine learning to clean your dataset with one line command. Features of MAHA include :-

• Drop all the index columns
• Drop columns with too many missing values
• Using Regression to find the missing values in the data and then replacing them

Prerequisites

• Data is in pandas DataFrame format
• All the categorical variables are label encoded
• All the columns are in the desired data type of the output

You can also:

• Find the mean and mode of every column
• Fill the NA values with mean and mode of the columnns depending on the datatype
• Find a model for every column with all other columns being the independent variables

Dependencies

MAHA uses a number of open source projects to work properly:

• [NumPy] - NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
• [Pandas] - Pandas is a software library written for the Python programming language for data manipulation and analysis.
• [Sklearn] - Machine Learning library which includes various classification, regression and clustering algorithms

Installation

MAHA requires pandas, numpy and sklearn

Use pip to install the packages

$ pip3 install pandas

$ pip3 install numpy

$ pip3 install sklearn

If you have not installed pip, you can do it by

$ curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py

Then run the following command where you have installed get-pip.py

$ python get-pip.py

Development

Developed By :- [Mithesh R], [Arth Akhouri], [Heetansh Jhaveri], [Ayaan Khan]

Want to contribute? Navigate to our GitHub for more information GitHub Repository - [MAHA]

License

MIT