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Name: Juan Camilo Ospino
Type: User
Company: Universidad EAFIT
Bio: Jack of all trades, master of none. Into Data Science.
Location: Medellín, Colombia
Name: Juan Camilo Ospino
Type: User
Company: Universidad EAFIT
Bio: Jack of all trades, master of none. Into Data Science.
Location: Medellín, Colombia
The code processes a dataset containing information about crimes, including dates, times, and victim demographics. It performs exploratory data analysis to uncover insights such as peak crime hours, crime occurrences over time, and crime frequency across various victim age groups.
In-depth analysis of the Colombian vehicle market, focusing on sales trends and safety evaluation. The analysis is conducted using popular Python libraries such as Pandas, NumPy, and Matplotlib, which provide powerful tools for data manipulation, analysis, and visualization.
The primary goal is to combine these datasets into a cohesive DataFrame, enabling comprehensive analysis and insights into Airbnb listings. Initially, the datasets are individually read into separate DataFrames: one from a CSV file, another from an Excel file, and the third from a tab-separated value file (TSV).
The primary objective is to conduct an in-depth analysis of SAT scores across schools, identifying top-performing institutions and understanding the performance trends. The analysis involves computing total scores, identifying schools with exceptional performance, and exploring variations among different educational institutions.
This study aims to analyze and compare homicide rates (both gun-related and total) in the United States with other developed countries within the G20, using Human Development Index (HDI) as a measure of development.
This GitHub repository contains a collection of Python codes showcasing various interpolation numerical methods. These methods leverage popular libraries such as NumPy, SymPy, Pandas, Matplotlib, and Seaborn to perform interpolation tasks efficiently and visualize the results effectively.
Matlab codes for Numerical methods, including Interpolation, Non Linear Equations, Systems of equations
This project revolves around building a predictive model to estimate car insurance claim outcomes based on various factors related to policyholders. The dataset contains comprehensive information about insurance policies, policyholders' demographics, vehicle details, claim history...
This self-guided project focuses on analyzing the Netflix Movies database to uncover valuable insights and relationships between various variables. By applying basic statistical concepts, conducting exploratory data analysis, and leveraging data manipulation techniques, this project offers a comprehensive exploration of the Netflix Movies dataset.
This repo showcases a self-guided project that explores and analyzes the Nobel Prize Database using Python's data analysis and visualization libraries such as NumPy, Seaborn, and Pandas.
Here, some methods for solving nonlinear equations, offering a collection of solvers including Bisection, Newton-Raphson, Secant, Fixed Point Iteration, and Newton's Method with Multiple Roots are found. These numerical techniques provide versatile and efficient approaches to finding solutions for nonlinear equations
The project involves working with a dataset containing information about students and their job-related attributes. This dataset encompasses various columns such as student ID, city, gender, education level, experience, company size, and more. The objective is to clean and process this data to analyze job-related trends and patterns.
The repository showcases different methods for solving systems of equations, including Successive Over-Relaxation (SOR), Jacobi-Gauss Seidel, and Gaussian Elimination. These numerical methods provide efficient solutions to systems of linear equations and can be utilized in a wide range of scientific, engineering, and mathematical applications.
Google Play Store Apps and Reviews Analysis: Exploratory Data Analysis, Data Cleaning, and Visualization
This project is an interactive implementation of the popular game "Who Wants to be a Billionaire" using Python. The game is designed using object-oriented programming principles, making it easy to understand, extend, and maintain.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.