nyc-open-data

Data Analysis Using Python: A Beginner’s Guide Featuring NYC Open Data.

Buying a home in NYC, what Neighborhoods are the best value? This project seeks to understand the fundamental factors that explain differences in residential real estate prices across NYC.

NYC 311 complaint heatmaps built with Jev: reproducible pipeline and interactive geographic visualizations

[WIP] Building a New York City job portal using the NYC OpenData Jobs API:

End-to-end pandas project: pulling, cleaning and analysing NYC 311 service requests to find which complaint types and boroughs take longest to resolve.

Agent-ready apartment research for any city: rank listings on your own criteria and true monthly cost, map door-to-door commutes, audit prices, read building records, and see each unit's light, view and your furniture in 3D.

Data cleaning, transformation, and exploratory analysis of NYC pregnancy-associated mortality data using Python.

Open tools to pull every NYC apartment's real price and history out of the walled gardens, plus a standardized public record of every building. Point your AI agent at it and build. The rent is price-fixed; we unfix it.

Conducting geodemographic classification for ethnic groups in NYC using K-means algorithm available in sklearn.cluster module.

Early-warning system for NYC senior-care dispatchers — flags elevator outages and heat-driven failure risk before routes go out

Select an official NYC street intersection and get a sourced safety report — live NYPD collision data plus Vision Zero Priority Zone overlap, with an optional AI explanation. EZStreet, built for the NYPL/MLH Built for NYC AI Hackathon.

How long does New York City take to fix things? Survival analysis of 1.77M 311 service requests: Kaplan-Meier for right-censored open requests, direct standardization for complaint mix

CrashLens analyzes traffic accident data through visualizations (histograms, pie charts, line plots, scatter plots) and DBSCAN clustering to identify accident hotspots. It includes data cleaning and supports datasets from various locations, with a focus on NYC crash data.

MCP server that puts Socrata open data on tap for LLM clients — catalog search, schema inspection, and guarded SoQL queries, with a live in-browser demo

NYC 311 response times: Tableau dashboard generated from code, embedded in a data-story page with a local-LLM copilot that drives it (Embedding API v3 + Ollama tool calling)

NEW YORKERS // BY MLOW

Identified data types for each distinct column value on 1900 data sets. For each column, summarized semantic types present in the column, using Fuzzy Logic, Levenshtein distance. Identified & derived inference the 3 most frequent 311 complaint types by borough.

a map showing the positions of subways and ferries in NYC

Same 1.9M NYC crashes, same question: r=0.05 between crashes, 0.55 across community districts, 0.71 across boroughs -- and equal-size contiguous redistricting alone spans 0.07 to 0.83. A measured audit of the modifiable areal unit problem.

MSc capstone: NYC office-building vacancy risk prediction from six municipal datasets (XGBoost, SHAP, Streamlit)