An end-to-end data pipeline which extracts divvy bikeshare data from web loads it into data lake and datawarehouse transforms it using dbt and finally , a dashboard to visualize the data using looker studio, the pipeline is orchestrated using prefect

Scripts to combine various Chicago transit data feeds

A Python utility to scrape and export your Divvy bike data to .csv

Portfolio

Regression and Decision Tree Analysis of Divvy bike dataset to estimate bike demand based on weather conditions

Analysis of Chicago's rideshare biking service, Divvy, in Q3 of 2019.

This project is to use Tableau to visualize the usage patterns of Divvy bikes in Chicago. By analyzing the trip data provided, we can gain insights into when, where, and how bikes are being used. This information can be useful for Divvy and the City of Chicago in planning future bike infrastructure and promoting sustainable transportation options.

A case study on the fictional bike-share company Cyclistic's trip data, based on Chicago Divvy public dataset.

Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago.

Several classifier models to predict non-member vs member rider status based off of ride data for Divvy Bikes users. Trained off of 13 months of past ride data.

Developed a relational database that will enable quick response and analysis on the current state of Divvy’s operations in regard to ridership, station locations, other factors affecting them. Then built a scoring model to optimize the number of stations and bikes allocated by zip codes

Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago via Flask application. Must be run locally to use.

A comprehensive analysis and insights derived from the Google Data Analytics Capstone Project focused on Cyclistic, a bike-share program.

This case study is about a fictitious company, Cyclistic. Where I will answer business questions, following the steps of the data analysis process: Ask, Prepare, Process, Analyze, Share and Act.