In this document we analyze the most frequent travel routes that have been in use over almost 10 years of operation. By doing this, we expect to comprehend travel patterns and provide an initial interpretation about the role of MiBici in providing a solution to daily urban mobility needs.

MiBici public bike share system data collecting, cleaning and initial processing.

Wines K-means clustering project from Udemy course

Caso de Estudio de script de consulta y visualización de datos en R aplicado a las bases de datos de padron vehicular de INEGI. El Script permite visualizar la evolución del registro de automóviles para una entidad federativa y período temporal que se indique. En este caso de pone como ejemplo el Estado de Jalisco, para el período comprendido entre 2010 y 2020.

Guadalajara Metro Area Bike Sharing System map. Data sources: MiBici Open Data porta, Open Street Map.

This project is an exercise prepared within UDEMY's course: "R for Data Science and Machine Learning". In this project we will be working with the UCI adult dataset. We will be attempting to predict if people in the data set belong in a certain class by salary, either making <=50k or >50k per year. Most of this project is focus on the different issues that may arise when cleaning data.

This project is based on the Bike Sharing Demand Kaggle challenge. The main point of this project is to practice Exploratory Data Analysis and begin to get an understanding the power and limitations of Linear Regression to build prediction models.

Capstone Project for UDEMY's Data Science and Machine Learning Bootcamp with R.

Analiza información procedente de tres fuentes distintas para integrar una base de datos con la densidad de población de las ciudades del Sistema Urbano Nacional

Histogram of urban density in inhabitants per hectare. Data used: INEGI 2020

Simple plot, population vs. urban surface of Mexican Cities Data population: INEGI 2020

Simple plot, population vs. urbanized surface of Mexican cities.

Plot sesión capacitación 2 - WRI

Storm data proccessing and analysis project. Project #2 from the Reproducible Research course.