PrePy - A Customize Library for Data Preprocessing in Python

When it comes to machine learning data preprocessing is a crucial prerequisite step. It is because any machine learning model trained or tested on an imbalanced data set can lead to inaccurate results. Data preprocessing is a process that takes raw imbalanced data set as input and converts it into a form that is more structured and cleaner which is easily understood and analyzed by machine learning models. This raw data can be in the form of images, videos, text, etc. It includes techniques such as feature extraction, normalization, transformation, data cleaning and selection, etc. For performing data preprocessing data science enthusiasts must import and use many different libraries. There is no such library which consists of every data preprocessing required function in it. Therefore, in this paper, we have proposed a customized library called “PrePy” which has different functions that a user can import and call the specific function to perform a task.