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In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.
Scripts to combine various Chicago transit data feeds
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.
Alexa Skills to check the status of stations in the Chicago Divvy or Columbus CoGo bike sharing systems
Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago.
Interactive visualization of available bikes and e-bikes at Divvy stations across Chicago via Flask application. Must be run locally to use.
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.