4 Strategies to Deal With Large Datasets Using Pandas Codementor

Every data scientist knows that data pre-processing and feature engineering is paramount for a successful data science project. Often, however, these steps are time-consuming and involve you waiting for computations to finish, keeping you from creating that awesome model. In this post we will look at a few tricks that intend to speed up your pandas data-crunching workflows by enabling Pandas to use your machine in an optimal way. Pandas is a powerful, versatile and easy-to-use Python library for manipulating data structures. For many data scientists like me, it has become the go-to tool when it comes to exploring and pre-processing data, as well as for engineering the best predictive features.