In this project, I thoroughly clean bike-share data from 2014-2015 and build a simplistic ARIMA model to forecast daily revenue per bike station in 2016. (Repo in progress)

Analyzing and predicting the demand for bikes using a Spatio-Temporal Graph Convolutional Network (STGCN) model.

London Bike Sharing Dataset

This is my First Viz Project using Tableau . I have done this project with the help of the video done by youtuber data with mo. https://www.youtube.com/@datawithmo

Combining journey data with community ethnicity data to evaluate Capital Bikeshare's performance on inclusion goals in Washington D.C.

Having some fun with Capital Bikeshare's data

🚲 Bike Share Route Planner

The Udacity US Bikeshare Data Analysis project is a hands-on project that involves using Python to explore and analyze bike share data from three major cities in the United States: Chicago, New York City, and Washington DC. You will gain insights into trends in bike share usage in different demographics, locations, and times of the year.

Predict near-term Capital Bikeshare availability using a random forest and Poisson regression. Display current status and predictions with leaflet.js map visualization.

Developing a business strategy to meet the demand levels and meet the customer's expectations.

Tartu smart bikes

Collect and pre-process historical trip data from major bike sharing companies

Hubway Bike Share was a SQLite3 analytics project focusing on traffics of the bike utilizations in each station and across stations. The project also illustrated user patterns and preference to strategize user experience enhancement.

In this project, the dataset provided by Motivate (https://www.motivateco.com/), a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. It is designed to be interactive and allows you to compare usage between three large cities: Chicago, New York City, and Washington, DC.

Repositório com dados utilizados para elaboração do estudo intitulado "Sistema de Bicicletas Compartilhadas em Manaus: Desafios e oportunidades"

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

This project demostrates my SQL and Excel skills, tools common for any organization. The datasets were too big to analyse in Excel alone and so I used SQL to do much of the heavy lifting and did visualizations in excel.

This application explores ridership and station usage in Pittsburgh's Bike Share System.

This repository is done as part of my Data Analyst Nanoodegree at Udacity, a modular program written in python 3 to help users interact with and explore US Bike-Share data of 3 major cities .

Analyzing the bike-share data of US from Motivate, for three popular cities Washington, New York, and Chicago and showing statistics for different users, stations, and times of travel. Also filters the data sets according to the user's choice and shows statistics on the filtered data.