Got Heat? Tenant Heating Complaints and a Civic-Tech Solution

Posted on Feb 6, 2017


Every year, hundreds of thousands of New York City residents file complaints with 311, a non-emergency call service that serves as the catch-all access point to all New York City agencies. Throughout the year, approximately two hundred different types of complaints are logged, ranging from excessive noise to rude taxi cab drivers to dangerous road conditions. The biggest offender, however, has historically been heating complaints. On average, the temperature from October to May in New York City is in the low-to-mid-40s and many tenants, who often have no control over their heat or hot water, are at the mercy of their landlords to provide adequate heat.

The New York City Department of Housing Preservation and Development ("HPD") is tasked with making sure that landlords and property owners provide heat and hot water to their tenants. The required heating season runs from October 1st through May 31st of each year. Landlords are required to provide heat if the outdoor temperature is below 55ºF during the day (6 a.m. to 10 p.m.) or below 40ºF at night. When it is that cold out, your landlord is simply required, by law, to ensure that your apartment is at least 68ºF during the day or at least 55ºF at night. Failure to comply with this law can result in fines up to $1,000 per day for non-compliance.



Unfortunately, HPD struggles to enforce the law, with both long wait times for inspections and slow, bureaucratic processes slowing down timely enforcement. All the while, landlords ignore their tenant’s complaints, and the city’s fines, and fail to adequately heat their buildings.


Fortunately, Heat Seek, a civic-tech focused, NYC based not-for-profit, is trying to solve this problem using 21st century IoT technologies. Full disclosure here; I didn't just stumble upon this cool non-profit, in fact, I am on the board. Heat Seek uses web-connected temperature sensors which can be installed in any number of apartments throughout a building. Sensors take hourly temperature readings and send them through an onboard internet connection to secure servers, where we store the data all winter long. To ensure data custody, the Heat Seek team conducts all installs and protects the devices from potential tampering.

The Heat Seek application analyzes sensor data, alongside with outdoor temperature data, in order to record each hour whether the temperature falls below the legal limit as defined by the NYC Housing Code. Data is displayed in a graph as well as a comprehensive heat log, so that tenants and their advocates have robust data to take to court and to use in landlord-tenant negotiations.

Armed with this data, public interest attorneys, community organizers, and even city officials can advocate on behalf of at-risk tenants, and better hold landlords accountable for their negligence and harassment. Our data can demonstrate patterns of landlord abuse: manipulating the heat before, during, and after city inspections; targeting specific tenants; using heat as a harassment tactic; and more.


Data and Project Goals

For my project, I wanted to meet two primary goals:

  • Visualize the 311 complaint data, updated daily on the NYC Open Data platform
  • Building a dashboard for HPD using anonymized Heat Seek sensor data

311 Heat Complaints Visualized

Complaints by year:


Complaints by Borough:


Complaints by Winter:


HPD Dashboard

A map of NYC sensor locations:


A scatter plot of sensor readings over time:


About Author

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp