NYC 311 Request Delay Prediction — Phase I Proof of Concept

Problem

Predict whether a NYC 311 service request will experience an unusually long resolution time based on request characteristics.

Dataset

NYC Open Data: 311 Service Requests

Phase I Proof of Concept

This repository contains:

we focused on data, cleaning, exploratory analysis, and establishing a baseline modeling pipeline.

Specifically, we have:

• Collected a sample of NYC 311 Service Request data from NYC Open Data
• Computed resolution time for each request using Created Date and Closed Date
• Removed requests without valid closure information
• Filtered out invalid or extreme resolution times (negative values and top 1% outliers)
• Dropped columns with excessive missing values or low relevance to the initial model
• Explored request volume across complaint types
• Constructed a cleaned dataset of closed requests suitable for modeling
• Outlined a baseline classification approach to distinguish long vs. typical resolution times

How to Run

1. Download the data:

   • Go to https://www.kaggle.com/datasets/new-york-city/ny-311-service-requests
   • Click Download - this will download a .zip file
   • Unzip the file and place 311-service-requests-from-2010-to-present.csv in the data/ folder

2. Install dependencies:

pip install -r requirements.txt

3. Open notebook:

notebooks/phase1_poc.ipynb

4. Run all cells

Repository Structure

• data/ — sample dataset
• notebooks/ — exploratory work + POC model
• src/ — preprocessing and modeling scripts, for later phases
• results/ — saved outputs