Skip to content

Repository files navigation

Admission Exam Results Analysis – Public University in Lima

Project Overview

This project analyzes the admission exam results for the 2025-I intake of the UNMSM, Peru's oldest and most prestigious public university. The data was obtained through Web Scraping from the university's official website, which provides public access to exam results.
By extracting, processing, and visualizing this data, the project aims to uncover key insights into applicant performance, career competitiveness, and score distribution.

Web Scraping with Selenium in Python

Automating the extraction of exam results:

  • Accessing the main page listing all academic programs.
  • Automatically navigating to each program’s link to extract results.
  • Extracting data from tables while handling pagination.
  • Implementing error handling to prevent disruptions if a program page fails to load.
  • Structuring and storing data for further analysis.

Data Wrangling in Python to Enhance Data Quality

  • Formatting corrections.
  • Creating new columns to optimize analysis.
  • Standardizing variables such as category names and campus locations.

Analysis & Visualization in Power BI

With clean data, I developed a Power BI dashboard to uncover key insights into applicant performance:

  • Minimum and maximum scores per program and overall.
  • Ranking of the top 10 programs with the highest scores.
  • Total applicants vs. admitted students, categorized by program.
  • Global ranking based on exam scores.
  • Interactive filters to analyze trends by faculty and admission type.

About

A project covering data extraction, analysis, and visualization of admission exam results from a public university in Lima (2025-I). It includes Web Scraping for data collection, exploratory data analysis, and Power BI dashboards. It provides insights into career competitiveness, applicant performance, and score distribution.

Resources

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages