Exploratory Data Analysis in Engineering Admission Prediction for Indian Universities

The main aim of every student and parent belonging to the current generation is to gain best education to have bright future and best career opportunities. Undoubtedly there are multiple career opportunities these days which are boosting up among students because of high-pay packages and good careers. Engineering is one of the career opportunities that is attracting too many youngsters but getting admission to the country’s best colleges is very tough. To pass various admission tests, students often devise the most difficult technique such as enrolment in coaching centres. The purpose of this study is to identify the importance and contribution of multiple factors such as 10th and 12th percentage of marks, school board, coaching centers, preparation strategy, online content, family background, effect of social media, drop cases, etc. By identifying the major and important factors, students will be highly benefited at an early stage of their preparation and therefore can improve their overall chances of admission. Students will be able to design their strategy for cracking the entrance examinations easily and shall be able to improve their overall chances of getting high ranks in various entrance examinations with the aid of this research. The suggested approach uses a data analytics approach to visualize the data and displays an exploratory data analysis of the admission-affecting elements. Box charts, bar charts, scatter charts, and heat maps are different ways to represent the relationship between components. Hence, this study attempts to assist the ways to students in raising their chances of admission to the desired college as well as their academic performances.