This project gives an overview of crime time analysis in New York City . We have created Python Jupyter notebooks for spatial analysis of different crime types in the city using Pandas, Numpy, Plotly and Leaflet packages. As a second part to this analysis, we worked on ARIMA model on R for predicting the crime counts across various localities in the city based on correlations of various demographics correlation in each locality.
UrbanScout is a web application that helps you find landmarks in your local city. Built with the Google Maps API and NYC Open Data at the Hack@CEWIT Hackathon.
🗣 Renters Speak gives users a peek behind the curtain of the New York City rental market. Designed for renters looking for more information about their current or prospective landlords, this app provides a platform for users to write and share reviews of landlords and also presents data related to building ownership and building maintenance violations from NYC housing datasets. Users can search for information by address and Renters Speak provides reviews and housing data in an easy to understand, visually appealing format.
NYC School Monitor is an Education-based app that uses data from NYC Open Data ingested into a multi-model Rails API backend that serves data to a multi-page React/Redux frontend. The application includes Semantic UI for styling, Google Maps, JSON Web Tokens and localStorage to store encrypted user information.