Data Exploration, Manipulation, and Evaluation

Abstract

This paper explores various methods for analyzing, manipulating, and evaluating survey data. Using a Jupyter notebook, we examine trends such as the increase in the number of published survey articles over the years. Additionally, we categorize each article into different taxonomy topics. Through data manipulation, we create a TF-IDF matrix, enabling us to predict an article’s taxonomy category based on key words from its title, summary, and associated categories