Introduction

Your company is a non-profit whose purpose is to advocate for equity in handling and providing long term solutions to city maintenance problems (trash collection, potholes, etc.) in Kansas City, MO.

The goal of this assignment is to identify the areas with a higher number and density of such requests, understand what types of requests are the most common for those areas, and analyze the degree of equity in the way the city addresses the issues in neighborhoods with respect to their socio-economic profiles. To address the latter, your goal is to identify whether the discrepancy in maintenance needs and the time it takes to resolve issues differs between neighborhoods and whether this difference (if observed) is indicative of inequity in city maintenance.

Directions

Use this public dataset on 311 calls: https://data.kcmo.org/311/311-Call-Center-Service-… Use appropriate tools (e.g. Python, SAS, Tableau, or a combination of those) to conduct the analysis using the dataset. Once you have identified any areas that have clusters of requests of a certain type, align those areas with the socio-economic profiles of those neighborhoods. To do so you can use any publicly available source: https://datausa.io/profile/geo/kansas-city-mo/